rheological and thermo-mechanical properties of pla-based miscible blends … · 2016. 3. 29. ·...

Rheological and thermo-mechanical properties

of PLA-based miscible blends and composites

Rheologische und thermomechanische

Eigenschaften von PLA-basierten mischbaren

Blends und Kompositen

Der Technischen Fakultät

der Friedrich-Alexander-Universität

Erlangen Nürnberg

zur

Erlangung des Doktorgrades Dr.-Ing.

vorgelegt von

Xiaoqiong Hao

aus Henan, China

Als Dissertation genehmigt

von der Technischen Fakultät

der Friedrich-Alexander-Universität Erlangen Nürnberg

Tag der mündlichen Prüfung: 08.03.2016

Vorsitzender des Promotionsorgans: Prof. Dr. Peter Greil

Gutachter: Prof. Dr.-Ing. habil. Dirk W. Schubert

Prof. Dr.-Ing. Volker Altstädt

Table of Contents

1. Introduction ......................................................................................................................................... 1

2. Literature review ................................................................................................................................. 3

2.1 Biopolymer and PLA ..................................................................................................................... 3

2.2 Current approach to improve PLA properties ............................................................................... 5

2.2.1 PLA based nanocomposites .................................................................................................... 5

2.2.2 PLA based blends ................................................................................................................... 7

2.3 Effect of particles on polymer blends ............................................................................................ 9

2.3.1 Nanoparticles in the miscible polymer blends ........................................................................ 9

2.3.2 Nanoparticles in the immiscible polymer blends ................................................................. 10

2.4 Rheological properties of polymer composites ........................................................................... 11

2.4.1 Dynamic mechanical experiment ......................................................................................... 12

2.4.2 Creep and creep recovery experiment .................................................................................. 14

2.5 Shape memory polymer ............................................................................................................... 16

2.5.1 Classification of SMPs ......................................................................................................... 17

2.5.2 Structure and mechanism of semi-crystalline SMPs ............................................................ 18

2.6 Entanglements and the tube model .............................................................................................. 21

2.7 Motivation ................................................................................................................................... 26

3. Material and sample preparation ....................................................................................................... 28

3.1 Matrix polymers .......................................................................................................................... 28

3.2 Filler materials ............................................................................................................................. 29

3.3 Sample preparation ...................................................................................................................... 29

3.3.1 Preparation samples for rheological measurements ............................................................. 30

3.3.2 Preparation of cast films for biaxial stretching ..................................................................... 32

3.3.2 Preparation of biaxially stretched films ................................................................................ 32

4. Characterization methods .................................................................................................................. 33

4.1 Analytical characterization .......................................................................................................... 33

4.1.1 Size exclusion chromatography (SEC) ................................................................................. 33

4.1.2 Thermogravimetric analysis (TGA) ..................................................................................... 33

4.1.3 Differential scanning calorimetry (DSC) ............................................................................. 33

4.2 Morphological characterization ................................................................................................... 34

4.3 Rheological characterization ....................................................................................................... 34

4.3.1 Dynamic mechanical thermal analysis (DMTA) .................................................................. 34

4.3.2 Oscillatory shear rheology .................................................................................................... 34

4.4 Shape memory characterization .................................................................................................. 36

II Table of contents

5. PLA/silica composites ....................................................................................................................... 39

5.1 Morphological characterization ................................................................................................... 39

5.2 Thermal behavior ........................................................................................................................ 41

5.3 Rheological investigation ............................................................................................................ 43

5.3.1. Linear viscoelastic region .................................................................................................... 43

5.3.2. Thermal stability .................................................................................................................. 44

5.3.3. Dynamic mechanical experiments ....................................................................................... 45

5.3.4. Creep-recovery experiments ................................................................................................ 48

5.3.5. Zero shear viscosity and steady-state compliance ............................................................... 54

5.4 A model to describe the interactions in PLA/silica composites .................................................. 55

5.4.1 Interaction between silica particles and PLA matrix ............................................................ 55

5.4.2 Interaction between silica particles ...................................................................................... 58

5.5 Conclusions ................................................................................................................................. 62

6. PLA/PMMA blends ........................................................................................................................... 64

6.1 PLA/PMMA 7N blends with different compositions .................................................................. 64

6.1.1 Thermo-mechanical properties of PLA/PMMA blends ....................................................... 65

6.1.2 Melt rheology of PLA/PMMA blends .................................................................................. 71

6.1.3 Interactions of PLA and PMMA via molecular entanglements............................................ 79

6.2 PLA/PMMA 50/50 blends with different molecular structures .................................................. 84

6.2.1 Molecular Characterization of PMMA 6N, 7N and 8N ....................................................... 84

6.2.2 Thermal behavior of PMMA and PLA/PMMA 50/50 blends .............................................. 85

6.2.3 Rheological properties of neat PMMA ................................................................................. 86

6.2.4 Interactions of PLA and PMMA via molecular entanglements in symmetrical PLA/PMMA

blends............................................................................................................................................. 88

6.3 Shape memory property of PLA/PMMA blends and the underlying mechanism ....................... 90

6.3.1 Influence of stretching parameters on the shape memory properties ................................... 91

6.3.2 Influence of molecular structure of PMMA and blend composition on the shape memory

properties ....................................................................................................................................... 98

6.3.3 The shape memory mechanism of PLA/PMMA blend system .......................................... 100

6.4 Conclusions ............................................................................................................................... 105

7. PLA/PMMA/silica nanocomposites ................................................................................................ 107

7.1 Morphological characterization ................................................................................................. 108

7.1.1 Dispersion of nanosilica in PLA and PMMA ..................................................................... 108

7.1.2 Dispersion of nanosilica in PLA/PMMA blends ................................................................ 108

7.2 Preferential adsorption on nanosilica by one of the components of PLA/PMMA blends ......... 111

7.3 Thermo-mechanical properties .................................................................................................. 114

7.3.1 DSC .................................................................................................................................... 114

III

7.3.2 Dynamic mechanical analysis (DMTA) ............................................................................. 115

7.4 Rheological properties of PLA/PMMA/silica nanocomposites ................................................ 116

7.4.1 Oscillatory strain sweep ..................................................................................................... 116

7.4.2 Oscillatory time sweep ....................................................................................................... 117

7.4.3 Oscillatory frequency sweep .............................................................................................. 118

7.4.4 Molecular entanglement ..................................................................................................... 122

7.4.5 Creep and recovery experiment .......................................................................................... 124

7.5 The influence of nanosilica on the shape memory properties of uniaxially stretched PLA/PMMA

blends .............................................................................................................................................. 125

7.6 The shape memory of biaxially stretched films......................................................................... 127

7.7 Conclusions ............................................................................................................................... 133

8. Summary and Outlook ..................................................................................................................... 135

9. Summary (in German) ..................................................................................................................... 139

10. Appendix ....................................................................................................................................... 143

10.1 Reproducibility of rheological measurements ......................................................................... 143

10.2 The melt density of PLA and PMMA at 200 °C ..................................................................... 144

10.3 Thermogravimetric analysis (TGA) of nanocomposites ......................................................... 145

10.4 The stress-strain curves of semi-crystalline polymers during cold or hot-deformation .......... 147

Abbreviations and symbols ................................................................................................................. 149

References ........................................................................................................................................... 152

Acknowledgements ............................................................................................................................. 166

List of Publication ............................................................................................................................... 168

1. Introduction

Nowadays, polymers have been widely used in our daily life and play more important roles in

many application fields due to the unique structure, low density, easy processability and

modification [Millich and Carraher (1977)]. Nonetheless, the inherent properties in their pure

state usually cannot meet the rapid growing demands. With the development of science and

technology, many modification methods have been developed to extend their range of

applications. The often used methods include blending, filling, surface and chemical

modification [Hamielec and Tobita (1992), Meister (2000)].

Blending polymers is the most versatile and economic method to obtain balanced properties

based on two or more polymers [Paul and Barlow (1979), Roland and Ngai (1991)].

Depending on the interactions between the components, the blends can be classified into fully

miscible blends, partially miscible blends and immiscible blends. The strong interaction

between the components in miscible blends will result in good physical properties. Another

usually used modification method is adding fillers into the polymer matrix which can

influence the mechanical, electrical, magnetically properties, especially for fillers in nanoscale.

Polylactide (PLA), as one of the most promising linear aliphatic thermoplastic polyester, has

attracted attentions not only in academia but also in industry [Garlotta (2001), Singh and Ray

(2007)]. It can be synthesized by ring opening polymerization of lactides which are typically

derived from renewable biomass via fermentation [Sawyer (2003)], and be considered as

“Green plastic”. Since PLA is biodegradable, biocompatible and nontoxic to the human body

and the environment [John et al. (2000), Lim et al. (2008), Shao et al. (2013)], it has been

widely used in biomedical, agricultural and industrial fields [Garlotta (2001), Auras et al.

(2004)]. Up to 2010, PLA has owned the second largest consumption volume in all the

bioplastics. Unfortunately, a few drawbacks such as the obvious brittleness, low melt strength,

2 1.Introduction

poor heat resistance limit the expansion and diversification of PLA’s application [Lim et al.

(2008)]. In this work, the properties of PLA were modified by adding silica of different

particle sizes, or alternatively, by blending with PMMA of various molar masses through melt

mixing approach. The influences of silica with various particle size and PMMA on the

thermo-mechanical and rheological properties of PLA were fully investigated.

In addition, the PLA/PMMA blend system is a typical miscible amorphous/semi-crystalline

polymer blend with shape memory potential. To our knowledge, the shape memory properties

of the miscible amorphous/semi-crystalline polymer blends have been extensively studied in

the previous work [Behl and Lendlein (2007)]. However, the underlying shape memory

mechanism needs further investigation. In this work, the entanglement network formed in

miscible PLA/PMMA blend is investigated by a rheological approach, and its influence on the

shape memory performance of PLA/PMMA blends is studied as well. Furthermore, we

systematically studied the influences of stretching parameters, blend composition and

component molar mass on the shape memory properties of PLA/PMMA blends. These results

provide a novel understanding into mechanism underlying shape memory properties for

miscible semi-crystalline/amorphous SMPs.

2. Literature review

2.1 Biopolymer and PLA

Biopolymers are polymers produced by living organisms, and therefore, are biodegradable

and recyclable in the environment [Nair and Laurencin (2007)]. They could be obtained from

renewable resources so it’s also called as “green” polymeric materials. In the past few decades,

extensive research focused on biopolymers of different groups, as well as on their copolymer

and blends. Biopolymers have been well established in the field of medicine [Hollander and

Hatton (2004)], and now they are more and more widely used in economical production [Lim

et al. (2008)]. Due to the strong demand to improve the relationship between environment and

industrial manufacture, biopolymers from renewable resources provide the best way to

maintain sustainable development [Sudesh and Iwata (2008)].

Polylactide (PLA) is one of the most commonly used synthetic aliphatic polyesters that have

the best cost efficiency. In the early research stage of PLA, it is mainly applied for tissue

scaffold or implant devices due to its limited molar mass and high cost [Lim et al. (2008)].

Nowadays, the PLA with high molar mass has been developed and widely used as food

packaging or other industrial products [Auras et al. (2003)].

Figure 2.1 Chemical structures of L-, meso- and D-lactides [Nampoothiri et al. (2010)].

4 2. Literature review

PLA can be synthesized from lactic acid, which is a natural product obtained from

microorganisms through fermentation [Sawyer (2003)]. Lactide, the cyclic dimer of lactic

acid, is formed by the condensation of two lactic acid molecules and gives rise to L-lactide

(LL-lactide), D-lactide (DL-lactide) and meso-lactide (LD-lactide) (as shown in Figure 2.1).

After a ring opening polymerization of lactide by using a catalyst under vacuum or inert

atmosphere, high molar mass PLA (𝑀𝑊 ≥ 100,000) is obtained. By controlling the reaction

time, temperature and catalyst, we can get PLA with different ratio and sequence of L- and D-

lactide units.

Figure 2.2 General structure of PLA [Jamshidi et al. (1988)].

The commercial grades of PLA are copolymer of poly(L-lactide) (PLLA) and poly(D,L-

lactide) (PDLLA), and the general structure of PLA is shown in Figure 2.2. Depending on the

composition of L- and DL-lactide, PLA can crystallize into three forms (, and ) [Auras et

al. (2004)]. PLA polymer with L-enantiomer above 90% tends to form crystallites and reduce

the optical purity [Jamshidi et al. (1988)].

Since PLA is compostable and derived from renewable sources, it is regarded as an ideal

material to fulfill current environmental concerns in view of environmental pollution and

excessive consumption of fossil resources. Generally, unoriented PLA is quite brittle, but

possesses good strength and stiffness. After processing by suitable methods, such as biaxial or

uniaxial stretching, the mechanical properties of oriented PLA are even better than

polystyrene (PS), high density polyethylene (HDPE), polypropylene (PP) [Auras et al. (2005)].

2.1 Biopolymer and PLA 5

However, some shortcomings of PLA hinder its application. Firstly, as a typical of aliphatic

polyester, the melt strength of PLA is relatively poor [Carlson et al. (1999)]. Moreover, the

thermal stability at typical processing conditions is a critical issue for rheological

measurements. The presence of ester groups was responsible for the decrease of PLA molar

mass at high temperature [Murariu et al. (2008)]. In addition, the brittleness and low heat

resistance of PLA also limit its application in industry. Therefore, some modified methods

were proposed to improve PLA’s performance.

2.2 Current approach to improve PLA properties

The primary objective of materials modification is to improve mechanical, thermal properties

and subsequently the flow properties during processing, which could be easily achieved by

blending with other polymers or fillers.

2.2.1 PLA based nanocomposites

Polymer nanocomposites refer to multiphase materials which are formed by polymer and

nanofiller (at least one dimension in the nanoscale, 100nm) [Hussain et al. (2006)]. Various

types of nanofillers have been considered as filler for PLA matrix in order to enhance its

thermo-mechanical and the theological properties, as well to provide functional properties

such as conductivity, fire-resistance and optical property, etc.

PLA/clay nanocomposites are commonly referred to PLA reinforced by aluminosilicate-based

nanofillers, which include layered silicates (montmorillonite), sepiolite and halloysite

nanotubes [Raquez et al. (2013)]. Layered silicate nanocomposites show prominent

thermomechanical, barrier and fire resistance properties even at low filler content [Ray and

Okamoto (2003)]. The improvements of these characteristics by the nanocomposites are

strongly related to the dispersion level of the layered silicates in the polymer matrix.

Therefore, the preparation method is the key factor to influence the final properties.


PLA/cellulose nanocomposites are totally biomaterials as cellulose is the most abundant

biopolymer on earth. Cellulose is a natural polymer, a long chain of linked sugar molecules. It

is an important component of the primary cell wall of green plants, and the basic building

block for many textiles and papers [Atalla (1999)]. Nanocellulose substrates have attracted a

lot of attention in the nanocomposites field due to the excellent properties such as nanoscale

dimensions, low density, unique morphology and good mechanical strength, as well they are

renewable and biodegradable [Raquez et al. (2013)].

PLA/carbonaceous nanocomposites are developed for its exceptional properties in terms of

stiffness and conductivity. Carbon nanotubes (CNT) have gained main interest as nanofiller

due to its exceptional physical properties, high electrical and thermal conductivity [Spitalsky

et al. (2010)]. CNTs are an allotropic form of carbon like diamond, graphite or fullerenes, and

its distribution in the polymer matrix play an important role in its conductivity. CNTs are

usually dispersed in PLA via solvent-evaporation, in situ polymerization and melt blending,

Wu et al. [Wu et al. (2010)] investigated the influence of the aspect ratio of CNTs and the

formation of percolating network in PLA/CNTs nanocomposites on the rheological, electrical

conductivity and mechanical properties of PLA. The results demonstrated that the CNTs with

high or low aspect ratios displayed different structural characteristics in PLA matrix.

PLA/metal and PLA/metallic oxide nanocomposites have attracted interest due to their

distinct optical, magnetic, antibacterial, electrical and catalytic properties, etc. Nanosilver

compounds are usually used for hygienic and healing purposes [Tolaymat et al. (2010)].

PLA/silver nanocomposites are developed mainly for its antibacterial activity. In addition, the

thermal properties and tensile strength are also improved due to the improvement in the

kinetics of PLA crystallization induced by nanosilver.

PLA/silica nanocomposites have been widely studied due to the advantages of silica (SiO2)

such as low cost, great natural abundance, high thermal resistance and surface

2.2 Current approach to improve PLA properties 7

functionalization, etc. Polymer nanocomposites based on silica can be used for many

applications including optical devices, coatings and flame-retardant materials [Zou et al.

(2008)]. In the work of Yan et al. [Yan et al. (2007)], PLA/silica nanocomposites are

synthesized by a sol-gel process. The thermal stability of the samples is improved by silica

loading. In addition, the presence of even small amounts of silica greatly improved the tensile

strength of the samples. Li et al. [Li et al. (2012)] studied the rheology and biodegradation of

melt compounded PLA/silica nanocomposites. A percolated silica network was formed if the

silica loading reached up to 5 wt%. Moreover, the biodegradation rates were enhanced in the

PLA/silica nanocomposites compared to neat PLA.

As discussed above, nanofiller represent an interesting way to improve the properties of PLA

via PLA based nanocomposites. The dispersion of nanofillers in PLA is still a challenge to

achieve the desired performance.

2.2.2 PLA based blends

A blend of two polymers can be characterized as miscible or immiscible, depending on

whether the blend shows a single phase or phase separation. In miscible blends, the two

components form a homogeneous single phase, and the interactions between the component’s

molecules are favorable and result in good physical properties. Miscible blends typically

result in an average of properties of the components, e.g. rheology and appearance.

Immiscible blends usually possess poor physical properties, delaminate upon impact, and

often differ greatly in viscosity, stability or polarity, but may still have very useful properties

[Robeson (2007)].

According to the literature, it is found that just a few polymers are miscible with PLA. Sheth

et al. [Sheth et al. (1997)] found that poly(ethylene glycol) (PEG) with high molar mass

( 𝑀𝑤 = 20,000 g/mol) was miscible with PLA when PEG content was below 50%.


Furthermore, PEG could plasticize PLA, resulting in higher elongations and lower modulus

values. A lower molar mass polyethylene oxide (PEO) (𝑀𝑤 = 300 − 1000 g/mol) is miscible

with PLA as well. However, PLA is immiscible with higher molar mass polypropylene oxide

(PPO).

Polyvinyl acetate (PVA) is also reported to be miscible with PLA [Gajria et al. (1996)] at all

blend ratio. Low level of PVA content (5-30%) can increase the tensile strength and

elongation of PLA probably due to some interactions taking place in that composition region.

A vast difference in the weight loss of pure PLA and 95/5 PLA/PVA blend was observed.

This difference in the thermal degradation was induced by the vast difference in the surface

tension of pure PLA films and the blends.

PLA appears to be miscible with poly(methyl methacrylate) (PMMA), many other acrylates

and copolymers of (meth)acrylates [Eguiburu et al. (1998), Zhang et al. (2003)]. In the blends

of crystalline PLLA and amorphous PDLA with PMMA and poly(methyl acrylate) (PMA)

prepared by solution/precipitation and solution-casting film methods, only one glass transition

temperature 𝑇𝑔 is observed. The values of 𝑇𝑔 follow the Gordon-Taylor theory for miscible

blend systems. In the PLLA/PMMA blend, the crystallization of PLLA is greatly restricted by

the presence of amorphous PMMA. However, for PLLA/PMA blend, the crystallization of

PLLA is largely favored by PMA.

Due to the significant differences in polarity between PLA and other polymers, PLA is

immiscible with polyolefin (polypropylene and polyethylene), styrenic resins (polystyrene

etc.), polycarbonate (PC) and Acrylonitrile butadiene styrene (ABS). Block copolymer

compatibilizers are developed to increase the compatibility between the components in the

blends.

2.2 Current approach to improve PLA properties 9

In this work, miscible PLA/PMMA blends were prepared by melt blending to produce shape

memory polymers. The influence of blend composition on the shape memory performance

will be studied in detail.

2.3 Effect of particles on polymer blends

In the production process of polymeric materials, composites are usually manufactured by

mixing different macromolecules or with solid “fillers” to improve the impact strength,

modulus, processability, conductivity, flammability or appearance [Meijer et al. (1988)]. The

addition of nanofillers can improve the performance significantly due to the small-size effect.

During the processing of polymer blends, the nanofillers can be used as compatibilizers to

improve the stability of the morphology by preventing domain coarsening. Therefore, it is of

great significance to study the how the nanofillers influence the overall phase behavior of the

polymer blends.

2.3.1 Nanoparticles in the miscible polymer blends

According to the previous work [Lipatov (2002), Lipatov et al. (2002), Huang et al. (2005),

Lipatov and Alekseeva (2007)], the addition of filler into a miscible blend can change the

temperature and kinetics of phase separation, or modify the shape of the phase diagram.

Lipatov and co-workers [Lipatov et al. (2002), Lipatov (2006)] found that for nanocomposites

based on blends containing chlorinated polyethylene and copolymers of ethylene with vinyl

acetate, the presence of fumed silica could influence the temperature of phase separation. It

can shift the temperature either up or down, depending on the amount of fillers. When the

filler content is around a value that can transit both components into the state of a border layer,

the phase separation temperature will be increased. At lower filler content, the redistribution

of the blend components may decrease the phase separation temperature. The possible

interpretation for this phenomenon is the change of the thermodynamics of interaction near


the surface of the fillers which is induced by the selective absorption of one of the

components. In addition, a redistribution of the blend components according to their

molecular masses between the boundary region and the matrix happened.

In the work of Huang et al. [Huang et al. (2005)], it was found that the introduction of silica

particles increased the phase separation temperature of PMMA/poly(styrene-stat-acrylonitrile)

(SAN) blends, and the thermodynamic interaction parameter was correspondingly decreased.

The phase stability of PMMA/SAM mixtures was improved by the addition of silica. The

mechanism for this enhancement was related to the preferential adsorption and specific

interactions between fillers and one of the components (PMMA) of the blend.

Composto et al. [Chung et al. (2004), Chung et al. (2007)] found that the incorporation of

silica nanoparticles slowed down the phase separation process in PMMA/SAN blends. It was

found that the nanoparticles were observed to partition into the PMMA-rich phase and stratify

during phase separation. Similar phenomena were observed in PS/PVME

(polystyrene/polyvinyl methyl ether) blends filled with fumed silica [Gharachorlou and

Goharpey (2008)]. Silica nanoparticles acted as an obstacle to the coarsening of the

morphology and segregated in the PVME-rich phase during the phase separation process.

2.3.2 Nanoparticles in the immiscible polymer blends

Adding solid particles to immiscible polymer blends is usually used to improve the

mechanical properties or obtain high electric conductivity [Fenouillot et al. (2009)]. Moreover,

the morphology of the immiscible polymer blends is also significantly influenced.

In the immiscible blend, the distribution of nanoparticles is mainly determined by the physical

interactions between the surface of the nanoparticles and the polymer components, viscosity

ratio of polymers and the compounding conditions. Generally speaking, the particles will

2.3 Effect of particles on polymer blends 11

selectively locate in one of the phase of the immiscible polymer blend and its uneven

distribution can be predicted calculating the wetting coefficient ωa [Fenouillot et al. (2009)],

ωa =γp−A−γp−B

γAB (2.1)

where 𝛾𝑝−𝐴 , 𝛾𝑝−𝐵 and 𝛾𝐴𝐵 are the interfacial tensions between particles and polymer A,

particles and polymer B, polymer A and B, respectively. If 𝜔𝑎˃1 , the particles will be

preferentially distributed in polymer B; when −1˂𝜔𝑎˂1, the particles will be preferentially

distributed at the interface of polymer blend; when 𝜔𝑎˂ − 1 , the particles will be

preferentially distributed in polymer A.

Nanoparticles can also be used a compatibilizer for immiscible blends. One of the early

reports about nanoparticles utilized as compatibilizer is on carbon black dispersed in

elastomers [Callan et al. (1971)]. Elias [Elias et al. (2007)] found that the most pronouncing

compatibilizing effect can be achieved when the particles are present in the interface of two

polymers.

In this thesis, the effect of silica nanoparticles on the phase behavior of miscible PLA/PMMA

blends will be investigated.

2.4 Rheological properties of polymer composites

During the conversion process of PLA and its composites, the rheological properties exhibit a

significant effect on the melt flow of materials. Since the rheological performance of PLA are

highly dependent on molar mass, fillers, processing temperature and shear rate, all these

factors must be taken into account during the optimization of process parameters [Lim et al.

(2008)].

The viscoelastic behavior of polymer melts can be characterized by zero-shear viscosity and

recoverable compliance, which could be determined by dynamic mechanical and creep-

recovery experiments in the linear region of deformation. These characterizations give the


relaxation time for final stress equilibration in the melts and get into insight the interactions

inside [Macosko and Larson (1994)].

2.4.1 Dynamic mechanical experiment

In industrial processes, polymers are usually processed as concentrated solution or melts.

Rheological properties are important in evaluating the processing evolution. The rheology of a

viscoelastic material is intermediate between that of a perfectly elastic solid and a purely

viscos fluid.

In dynamic mechanical measurement, a sinusoidal stress 𝜏(𝑡) is applied to the sample with

the fixed angular frequency 𝜔 and the stress amplitude value 𝜏0, and the response (𝑡) is a

sinusoidal deformation shifted according to /𝜔. The ratio between the viscous and elastic

behavior in polymer melt can be described by the tangent of the phase angle (𝑡𝑎𝑛).

𝑡𝑎𝑛 = 𝐺′′/𝐺′ (2.2)

The complex modulus 𝐺∗(𝜔) can be determined by the ratio of the shear stress amplitude and

the deformation amplitude. The complex viscosity |𝜂∗|(𝜔) can be determined from the

complex modulus from

|𝜂∗(𝜔)| = |𝐺′′(𝜔)|/𝜔 (2.3)

When 𝜔 is getting small, |𝜂∗(𝜔)| becomes independent of 𝜔 . In the terminal regime, the

constant viscosity value is called zero shear viscosity 𝜂0,

lim𝜔→0|𝐺′′(𝜔)|/𝜔 = 𝜂0 (2.4)

The material is said to act as linear viscoelastic when the study of viscoelastic materials is

under very small strain or deformation [Carreau et al. (1997)]. The linear steady-state elastic

compliance 𝐽𝑒0 can be obtained by

2.4 Rheological properties of polymer composites 13

lim𝜔→0|𝐺′′(𝜔)|/𝜔2 = 𝐽𝑒0𝜂0

2 (2.5)

It is well known, that the presence of nanoparticles in polymer matrices can not only change

the physical properties but also can influence the processability of polymer melts significantly

[Bhattacharya et al. (2008)]. Rheology is a powerful tool to investigate the mesoscopic and

microscopic structure of a polymer/filler system, and it can also be used to predict the

processing behavior of various composites [Han (2007)]. Dynamic-mechanical experiments

are constantly used to study the moduli and viscosity of polymer melts over the whole range

of frequencies. For polymer nanocomposites, the storage modulus 𝐺′ and loss modulus 𝐺′′

increase gradually with the increased filler fraction especially at low frequencies. Furthermore,

the moduli become more and more independent on frequency [Münstedt et al. (2010)]. When

the nanofillers fraction exceeds a certain level, the interactions between the particles are very

strong and lead to a solid-like behavior. Cassagnau [Cassagnau (2008)] studied the frequency

dependence of polystyrene/silica nanocomposites and found that percolated silica network

structures formed when the silica loading reaches up to 5 wt%. Wu et al. [Wu et al. (2006)]

found that the percolation threshold φ𝑐 of the PLA/CNTs (carbon nano-tubes)

nanocomposite was about 4 wt%, and the percolated network was very sensitive to both the

quiescent and the large amplitude oscillatory shear deformation. Wu et al. [Wu et al. (2007)]

pointed out that the viscoelastic properties are highly related to the fillers’ dispersion state and

the interactions between the fillers and the polymer matrix. A distinct increase of the moduli

and viscosity was observed in the low angular frequency range with the loading of fillers. In

the paper of Osman et al. [Osman et al. (2004)], this increase was attributed to hydrodynamic

effects caused by the presence of solid particles in the melt stream.

The oscillatory shear measurement can get the short time response of material melts while the

creep recovery test get the long time response [Münstedt et al. (2010), Triebel et al. (2011)].


In order to study the elasticity of polymer melts, creep-recovery experiment up to steady state

was conducted.

2.4.2 Creep and creep recovery experiment

The creep-recovery experiment is the most important rheological tool to measure the elasticity

of polymer melt. The process of creep and creep recovery experiment is shown in Figure 2.3.

In the creep test section, a constant shear stress 𝜏0 is applied to the sample at the creep time

𝑡𝑐𝑟 =0 s and the time-dependent deformation 𝛾(𝑡𝑐𝑟) is measured. The creep compliance

𝐽𝑐𝑟(𝑡𝑐𝑟) can be defined as

𝐽𝑐𝑟(𝑡𝑐𝑟) =𝛾(𝑡𝑐𝑟)

𝜏0= 𝐽0 + 𝜓(𝑡𝑐𝑟) +

𝑡𝑐𝑟

𝜂0 (2.6)

𝐽𝑐𝑟(𝑡𝑐𝑟) is independent of the creep stress 𝜏0 in the linear range of deformation. 𝐽0 is the

instantaneous elastic compliance, 𝜓(𝑡𝑐𝑟) is the creep function and 𝜂0 is the zero shear-rate

viscosity. Here 𝑡𝑐𝑟

𝜂0 is the irreversible viscous term and 𝜓(𝑡𝑐𝑟) is the viscoelastic part. If the

creep time 𝑡𝑐𝑟 is sufficiently long, 𝜓(𝑡𝑐𝑟) and 𝐽0 become negligible, and 𝜂0 can be determined

from experiments conducted at stresses in the linear regime as

lim𝑡𝑐𝑟→∞𝑡𝑐𝑟

𝐽𝑐𝑟(𝑡𝑐𝑟)= 𝜂0 (2.7)

At the time 𝑡𝑐𝑟 =𝑡0, the stress 𝜏0 is set to zero and then the recovery section begins. In this

stage, the recoverable compliance 𝐽𝑟(𝑡𝑟) was defined as

𝐽𝑟(𝑡0, 𝑡𝑟) =𝛾𝑟(𝑡0 ,𝑡𝑟)

𝜏0= 𝐽0 + 𝜓(𝑡0, 𝑡𝑟) (2.8)

𝛾𝑟(𝑡0, 𝑡𝑟) = 𝛾(𝑡0) − 𝛾(𝑡0, 𝑡𝑟) (2.9)

2.4 Rheological properties of polymer composites 15

so in the linear range of deformation, 𝐽𝑟(𝑡𝑟) is a measure of the elasticity of the material

[Triebel and Münstedt (2011)]. If the creep recovery time is long enough in the linear regime,

the steady-state recoverable compliance 𝐽𝑒0

can be obtained:

lim𝑡𝑜→∞𝑡𝑟→∞

𝐽𝑟 (𝑡0, 𝑡𝑟) = 𝐽𝑒0 (2.10)

Figure 2.3 Schematic diagram of a creep-recovery measurement.

Münstedt et al. [Münstedt et al. (2010)] reported that the elastic properties in the linear range

of deformation of a PMMA melt were more significantly influenced by the addition of fillers

than the viscos ones, and this effect was strongest in the steady-state which needs a long time

to reach. Unfortunately, the often used dynamic-mechanical experiments were not very

suitable for this situation due to its short time window. It was also found that the elastic

properties of nanocomposites at long experimental times were a very sensitive tool to get an

insight into the interaction between particles and molecular chains.

Triebel [Triebel et al. (2011)] investigated the influence of matrix polydispersity on the

elasticity of polystyrene (PS) melts filled with nanosilica. It was found that the linear steady-

state recoverable compliance of the broad PS 158K was about one order of magnitude higher

for the narrow aPS. The polydispersity could significantly influence the elasticity of the


matrix. However, the incorporation of nanosilica at the same fraction leads to a more

pronounced increase of elasticity for the narrow sPS compared to the broad PS 158K.

2.5 Shape memory polymer

Blend made from PLA and PMMA is a typical miscible amorphous/semi-crystalline polymer

blends with shape memory potential, which has received increasing interests in recent years.

Understanding the shape memory mechanism would be beneficial for designing novel

polymers with desired shape memory properties.

Among the stimuli sensitive polymers, shape memory polymers (SMPs) have gained

extensive research interest on account of their intrinsic advantages such as low density, large

attainable strain, easy processing and low cost [Xie (2011)], which provide a great potential

for applications in packaging, sensors, switches, smart textiles, drug delivery and medical

devices [Liu et al. (2007), Mather et al. (2009), He et al. (2012), Luo and Mather (2013)].

Generally speaking, SMP can memorize its original shape and, therefore, will return to it from

a temporary shape when exposed to an appropriate stimulus [Fengkui Li et al. (1997)]. At

molecular level, SMP usually consist of two components: a soft switching phase and a hard

stationary phase [Lendlein et al. (2005), Xie (2010), You et al. (2012)]. The former is

responsible for the fixation of the materials’ temporary shape, while the latter determines the

original shape. The molecules in the switching phase are linked to each other by net-points,

which could be of either physical or chemical nature [You et al. (2012)]. When the

temperature surpasses the switching or transition temperature 𝑇𝑡𝑟𝑎𝑛𝑠, the polymer networks

exhibit “super-elasticity”, and the entropy is considered as the driving force for shape

recovery in SMP systems [Hu et al. (2012)].

2.5 Shape memory polymer 17

2.5.1 Classification of SMPs

The reported SMPs include electrically sensitive, light sensitive, pH sensitive, magnetic

sensitive, thermal or moisture induced materials, based on the external stimulus [Hu et al.

(2012)]. According to the nature of the net-points, SMPs can be derived into two main classes:

physical cross-links and chemical cross-links [Meng and Hu (2009), Chang (2012)]. For the

SMPs based on chemical cross-links, the rubbery elasticity derived from covalent cross-links

leads to a great shape memory property, which can be tuned by the degree of covalent

crosslinking [Jung et al. (2010)]. On the other hand, the crystalline or rigid amorphous phase

usually act as hard stationary phase for SMPs based on physical cross-links, and the transition

temperature 𝑇𝑡𝑟𝑎𝑛𝑠 is either a glass transition temperature 𝑇𝑔 or a melting temperature 𝑇𝑚 .

Numerous SMPs have been prepared by physical cross-linking, such as linear block

copolymers [Behl and Lendlein (2007)] or copolyesters [Booth et al. (2006)].

Extensive studies have been carried out to develop new materials with a shape memory

potential and to expand their application. Based on the structural principles of polymers,

SMPs with new macromolecular structures can be synthesized or designed [Behl et al. (2009),

Wu et al. (2013)]. In the work of Lendlein et al. [Lendlein et al. (2001)], an AB-polymer

network showing shapes memory property was first reported. Oligo(ɛ-caprolactone) were

incorporated covalently into the thermoset as a crystallizable triggering segments that could

fix the secondary shape by physical cross-links. This polymer system showed excellent shape-

memory properties with recovery rate above 99% after 3 cycles. Liu et al. [Liu et al. (2006)]

prepared SSPs based on poly(methyl methacrylate)-co-(N-vinyl-2-pyrrolidone) and linear

poly(ethyleneglycol) (PMMA-co-VP/PEG). The shape memory network was prepared by

radical copolymerization of MMA and VP in the presence of linear PEG based on hydrogen-

bonding. Thereafter, multiple types shape memory polymers containing AB-polymer

networks were introduced [Lendlein et al. (2005), Bellin et al. (2007), Li et al. (2014)].


However, the methods of synthesis and modification of the designed networks are proved to

be complicated and inconvenient. To some extent, ease the processing has been an issue for

large-scale utilization of SMPs. Hence, polymer blending offers a simply way to tune the

shape memory property of conventional SSP and fabricate new SMP system. Miscible SMP

blend systems have aroused considerable scientific and practical interest since it possess

favorable phase interaction and good physical properties.

2.5.2 Structure and mechanism of semi-crystalline SMPs

The shape memory mechanism of SMP is significantly influenced by the materials’ molecular

structure [Hu et al. (2012)]. It’s well known that cross-linked polyethylene (PE) is one of the

first SMPs based on the semi-crystalline phase [Ota (1981)]. The crystalline phase with a

crystal melting temperature (𝑇𝑚) serves as switching phase, while the chemically cross-linked

PE network is used to memorize the permanent shape after deformation upon heating. For this

type SMP, the switching temperature is 𝑇𝑚.

Another type of semi-crystalline SMP has a switching temperature related to 𝑇𝑔 of the

amorphous phase. Compounding miscible amorphous/crystalline polymers is proved to be an

attractive method to prepare shape memory polymers that have a single phase and 𝑇𝑔. Mather

et al. [Campo and Mather (2005)] reported two types of miscible amorphous/semi-crystalline

polymer blends: amorphous polyvinyl(acetate) (PVAc)/semi-crystalline PLA and amorphous

PMMA/semi-crystalline polyvinylidene fluoride (PVDF). In this shape memory polymer type,

the crystalline phase served as physical cross-links and the amorphous phase between the

crystals acted as the switching phase. Furthermore, 𝑇𝑡𝑟𝑎𝑛𝑠 of the blends which can be tailored

by the composition is chosen as transition temperature [Liu et al. (2007)]. Furthermore, You

and co-workers [You et al. (2012), You et al. (2012)] investigated the shape memory

mechanism of another miscible amorphous/crystalline polymer blend composed of PVDF and

acrylic copolymer (ACP). It was found that the PVDF crystals worked as fixed phase and the

2.5 Shape memory polymer 19

amorphous phase between the PVDF crystals worked as the switching phase. In addition, the

tie molecules among the fixed PVDF crystalline phase significantly influenced the shape

memory properties. It was found that, the blend with 50 wt% PVDF possessed the best shape

memory properties.

Accordingly, the shape-memory mechanism of semi-crystalline polymers related to 𝑇𝑚 or 𝑇𝑔

are proposed and depicted schematically in Figure 2.4.

Figure 2.4 Schematic diagrams for the shape memory properties of semi-crystalline polymers

related to (a) 𝑇𝑚 and (b) 𝑇𝑔.

In order to fulfill the increasing requirements of developing new SMP with good

processibility and functional features, a new miscible SMP blend system based on semi-

crystalline PLA and amorphous PMMA was prepared by melt mixing. PLA is one of the most

promising biopolymers for its excellent performances such as biocompatibility,

biodegradability and nontoxic to the human body and environment [John et al. (2000)].


Furthermore, PMMA is also a biocompatible polymer which has been used as bone cement

since about half a century [Goncalves et al. (2013)]. Nowadays it is widely applied as

ophthalmic implants [Lloyd et al. (2001), Panahi-Bazaz et al. (2009)]. Therefore, a binary

blend of these two polymers has a potential to be used in biomedical application. As reported

by Samuel et al. [Samuel et al. (2013), Samuel et al. (2014)], melt mixing of semi-crystalline

PLLA with amorphous PMMA results in a miscible blend which has excellent shape memory

property. The mechanism for PLA/PMMA blends is more complex because the crystallinity is

changed with composition. Except the PLA crystals, the molecular entanglements also play an

important role to influence the shape memory behavior. So, in this work we will analyze these

factors in detail.

The shape memory properties of the miscible amorphous/semi-crystalline polymer blends

have been extensively studied in the previous work [Behl and Lendlein (2007)]. To our

knowledge, the reported shape memory mechanisms for miscible semi-crystalline/amorphous

polymer blends are mostly related to the crystallite in the blends, and the crystallinity is

simply suggested to be the dominate factor that influence the shape memory performance

[Campo and Mather (2005), Liu et al. (2007), You et al. (2012)]. In general, the crystals are

considered to serve as the physical cross-links and 𝑇𝑔 of the amorphous phase works as the

critical temperature for triggering the shape recovery. However, a promising shape memory

performance still can be observed when the blends are amorphous, and the molecular

entanglements are believed to serve as physical cross-links [Samuel et al. (2014)]. The

researches have pointed out the switching phase and stationary phase of SMPs, but the

correlation between the shape memory performance and the degree of crystallinity or

molecular entanglement is still unclear. For the miscible amorphous/semi-crystalline polymer

blends, we believe the underlying shape memory mechanism needs further investigation.

2.6 Entanglements and the tube model 21

2.6 Entanglements and the tube model

As mentioned above, the molecular structure of miscible PLA/PMMA blend can significantly

influence the shape memory performance and the processing behavior the melts. Rheology

has been demonstrated to be a suitable tool to provide information about molecular structure

in the polymer melts [Dealy and Larson (2006)].

In concentrated solutions or melts with high molar mass, the flexible polymer chains are

invariably entangled with the neighbors and create topological entanglement junctions [De

Gennes (1979), Edwards (1986)]. That is, the motion of a chain is significantly impeded by

the topological constraints, and its ability to relax after deformation is imposed [Dealy and

Larson (2006)]. These constraints called entanglements are formed in molten state and can be

fixed when the temperature decreases so that the rubbery or glassy state is attained. The

entanglement junctions in the melt are randomly distributed and are constantly formed and

destroyed in the entanglement and disentanglement process [Wu (1989)]. As well known,

chain entanglements play an important role in controlling solid mechanical [Kausch (1987)],

melt rheological [Ferry (1980)], and adhesive properties of polymers [Wu (1982)].

The tube model has been considered as the most established framework to understanding

polymer dynamics in the melt state [De Gennes (1979), Doi and Edwards (1986)]. For the

monodisperse homopolymer melts with linear architecture, the dynamics of long chains are

governed by reptation behavior due to the presence of entanglements while that for short

chains follows Rouse behavior [Rouse Jr (1953), De Gennes (1979)]. For unentangled

polymer melts, the zero-shear viscosity 𝜂0 is found to be proportional to the molar mass 𝑀,

and this relationship is valid for linear polymers of low molar mass (Equation 2.11). When the

molar mass exceed a critical value 𝑀𝑐 , a new relationship is found between 𝑀 and 𝜂0

(Equation 2.2).


𝑓𝑜𝑟 𝑀 < 𝑀𝑐: 𝜂0 ∝ 𝑀 (2.11)

𝑓𝑜𝑟 𝑀 > 𝑀𝑐: 𝜂0 ∝ 𝑀3.4 (2.12)

The major breakthrough in the theory of entangled polymers is Edwards’ tube model of

entangled polymer networks [Doi and Edwards (1986)]. In tube model, the entanglements of a

test chain with the surrounding chains (matrix) are effectively confined to a tube-like region.

The surrounding chains restrict the transverse motion of the test chain, while forces will move

it for the most part along the axis of the tube. Figure 2.5a shows the tube model of the test

chain (red) entangled with surrounding chains.

Figure 2.5 (a) Schematic diagrams for tube model formed by molecular entanglements in

polymers, (b) Entanglements between similar and dissimilar molecular chains in miscible

binary blend.

Cooper-White and Mackay [Cooper‐White and Mackay (1999)] studied the dynamic

viscoelastic behavior of PLLA melts with molar masses ranging from 2,000 to 360,000 g/mol.

It was found that the critical molar mass 𝑀𝑐 for PLLA is approximately 16,000 g/mol. Dorgan

and his group [Dorgan et al. (1999), Dorgan et al. (2000), Dorgan et al. (2005)] investigated

the linear and branched PLAs in the molten state, the results show that for PLA with a 98:2

ratio of L and D enantiomeric monomers, the entanglement molar mass is ca. 9,000 g/mol.


Wu and Beckerbauer [Wu and Beckerbauer (1992)] found that the plateau modulus 𝐺𝑁0 and

entanglement molar mass 𝑀𝑒 of PMMA are strongly dependent on tacticity, while they are

independent of molar mass and its distribution. 𝐺𝑁0 and 𝑀𝑒 of PMMA vary from 2.410

5 Pa

and 16400 g/mol for pure isotactic chains to 5.3 105 Pa and 7800 g/mol for fully syndiotactic

chains. Moreover, log 𝐺𝑁0 and log 𝑀𝑒 vary linearly with diad fractions.

In a miscible binary blend formed by high molar mass polymers, there exist interactions

between similar and dissimilar molecular chains. Therefore, three kinds of entanglements are

formed in the blends. Figure 2.5b shows entanglements between similar and dissimilar

molecular chains in miscible binary blend. A double reputation model has been proposed [Des

Cloizeaux (1988)] and applied to miscible blends [Pathak et al. (2004)].

In the work of Wu [Wu (1987)], the effects of molecular structure and specific interchain

interactions on the entanglement network were investigated. The entanglement behavior

between dissimilar chains in a PVDF/PMMA blend is compared with that for similar chains.

The results reveal that, in these blends, the similar chains are more likely to entangle with

each other than dissimilar ones, resulting in a large reduction of zero shear viscosity in the

blends.

The molar mass where the zero shear viscosity changes from a linear dependence on 𝑀𝑤 to

𝑀𝑤3.4 is defined as the critical molar mass for entanglement, 𝑀𝑐 [Dealy and Larson (2006)].

The molar mass between entanglements 𝑀𝑒 , is the most fundamental material parameter to

study the molecular dynamics.

For an elastomer, the equilibrium shear modulus for infinitesimal deformation can be defined

based on the classical theory of rubber elasticity [Ferry (1980)],

𝐺𝑒 = 𝑣𝑅𝑇 (2.13)


where 𝑣 is the number of moles of network strand per unit volume, 𝑅 is the gas constant and

𝑇 is the absolute temperature. The entangled melts can be considered to be a rubber in which

the crosslink network is replaced by the entanglement network. Therefore, Ferry defined the

plateau modulus of entangled melts by

𝐺𝑁0 = 𝑣𝑒𝑅𝑇 =

𝑅𝑇

𝑀𝑒 (Ferry definition) (2.14)

where is the melt density. The entanglement molar mass is given by

𝑀𝑒 = 𝑎

/𝑒 (2.15)

It is worth noting that the definition of 𝑀𝑒 by Equation 2.14 reflects all the relaxation that

occurs in response to the initial stress, except for the extremely short-time glassy modes. One

fifth of the initial stress relaxes before the entanglement network interrupts the process due to

the relatively fast Rouse modes allow re-equilibration of tension along the chains. Thus, the

observed plateau modulus in experiments is expected to be about 4/5 of the definition in

Equation 2.14. Graessley and Fetters [Ferry (1980), Graessley (1980), Fetters et al. (1994)]

modified the definition and gave a new correlation between 𝑀𝑒 and 𝐺𝑁0 by the following

equation,

𝐺𝑁0 = 4𝜌𝑅𝑇/5 𝑀𝑒 (Graessley-Fetters definition) (2.16)

where 𝑅 is the gas constant, 𝜌 is the density.

In order to determine the value of plateau modulus 𝐺𝑁0 , some semi-empirical methods have

been developed to extract 𝐺𝑁0 from the linear viscoelastic experiments [Plazek and Echeverrıa

(2000), Dealy and Larson (2006), Liu et al. (2006)], and a cross-check of all available

methods is the best way to achieve maximum accuracy.


Generally, the most common method to calculate 𝐺𝑁0 is measuring the linear viscoelastic

properties by oscillatory shear experiments. Especially for monodisperse polymers with high

molar mass (𝑀𝑤) and narrow molar mass distribution (MWD), 𝐺𝑁0 can be determined by the

value of storage modulus 𝐺′ at the frequency 𝜔𝑚𝑖𝑛 where 𝐺′′ reaches a minimum [Ferry

(1980)]:

𝐺𝑁0 = 𝐺′(𝜔)𝐺′′→𝑚𝑖𝑛𝑖𝑚𝑢𝑚. (2.17)

We call this approach the ‘minimum’ (MIN). Another method named “integral method (INT)”

is derived from the Kronig-Kramers relation for 𝐺′and 𝐺′′ [Sanders and Ferry (1969), Ferry

(1980)], 𝐺𝑁0 can be calculated by numerical intergration over the terminal relaxation peak of

𝐺′′(𝜔):

𝐺𝑁0 =

2

∫ 𝐺′′(𝜔)𝑑𝑙𝑛𝜔

+

− (2.18)

Unfortunately, PLA/PMMA blend is a typical polydisperse system, and the molar mass

difference between the components makes it impossible to get 𝐺𝑁0 from above methods.

Therefore, these methods should be modified and extend to polydisperse polymers [Liu et al.

(2006)], and the modifications of the MIN method and INT method were developed as

follows [Wu (1985), Wu (1989), Wu and Beckerbauer (1992)]

𝐺𝑁0 = 𝐺′(𝜔)𝑡𝑎𝑛→𝑚𝑖𝑛𝑖𝑚𝑢𝑚. (2.19)

𝐺𝑁0 =

4

∫ 𝐺′′(𝜔)𝑑𝜔𝑙𝑛

𝜔𝑚𝑎𝑥

− (2.20)

A semi-quantitative method based on the terminal cross-point of 𝐺′and 𝐺′′ were developed by

Wu [Wu (1989)] and Nobile-Cocchini [Nobile and Cocchini (2001)]. When the value for

𝑀𝑤/𝑀𝑛 is less than 3, 𝐺𝑁0 can be calculated from the crossover modulus 𝐺𝑋 (𝐺𝑋 = 𝐺′ = 𝐺′′)

by the follow equation,


log (𝐺𝑁

0

𝐺𝑋) = 0.38 +

2.63 log (𝑀𝑤/𝑀𝑛)

1+2.45 log (𝑀𝑤/𝑀𝑛) (2.21)

It is worth noting that the method base on crossover modulus to extract the value of 𝐺𝑁0 is a

semi-quantitative method. The plateau modulus obtained from Equation (2.21) is tentative due

to the approximation embedded in the relationships.

2.7 Motivation

Although PLA has modulus and tensile strength comparable to petroleum-based polymers,

some shortcomings such as brittleness, poor melt strength, and low heat and impact resistance

limit its application. Therefore, adding fillers, or blending with other polymers to form

composites is considered as an effective and simple way to extend and improve the properties

of PLA. The main conversion methods for PLA are usually based on melt processing. The

polymers are heated above their melting point, and shaped to the desired form with a cool

process. Therefore, understanding the thermal, crystallization and melt rheological behavior

of the composites is critical to optimize the materials properties. In the first part of this work,

we will study how silica with different particles size influences the thermo-mechanical and

rheological properties of PLA. What kinds of interactions exist in PLA/silica composites?

What’s the relationship between the particles size and the rheological percolation threshold of

PLA/silica composites?

PLA/PMMA blends with various compositions and molar masses of the PMMA used were

prepared by melt mixing. In this section, we will study how PMMA influence the thermo-

mechanical and rheological properties of PLA? How PLA and PMMA molecules interact

with each other in the blends? What’s the shape memory mechanism of PLA/PMMA blends?

What factors could influence the shape memory behaviors of PLA/PMMA blends?

In the third part of this work, nanosilica particles are added into PLA/PMMA 50/50 blends.

We will study how nanosilica particles disperse in the miscible PLA/PMMA 50/50 blends.

2.7 Goals of this work 27

What kinds of interaction exist in PLA/PMMA/silica mixtures? How nanosilica influence the

dynamic heterogeneity and shape memory behaviors of PLA/PMMA blends?

At the last part of this work, biaxially oriented films based on neat PLA, PLA/PMMA blends

and PLA/PMMA/silica nanocomposites were produced through simultaneous stretching at

different temperatures, strain rates and ratios. The influences of stretching parameters on the

shape memory performances of biaxially stretched films are analyzed in this work.

3. Material and sample preparation

3.1 Matrix polymers

In this work, the main matrix polymers are PLA and PMMA. PLA (Ingeo 4032D), containing

2% D-lactic acid and 98% L-lactic acid, was purchased from NatureWorks (USA). It is a

commercial grade designed for biaxially stretched films, having a density of 1.24 g/cm3 at

room temperature and 1.12 g/cm3 at 200 °Ϲ (see the appendix for the determination of melt

density). The weight average molar mass and number average molar mass are 𝑀𝑤= 210.2

kg/mol and 𝑀𝑛=123.5 kg/mol, respectively. Table 3.1 shows some material parameters of the

polymers.

Three different PMMA from Evonik Röhm GmbH (Germany) were chosen as blend partners

for PLA: Plexiglas® 6N (PMMA 6N), Plexiglas® 7N (PMMA 7N) and Plexiglas® 8N

(PMMA 8N). The glass transition temperatures 𝑇𝑔 of three PMMA increase from 6N to 8N.

From the 1H-NMR analysis (500 MHz, CDCl3, 25 °С) [Samuel et al. (2013)], the syndiotactic

sequences rr (42%) and atactic sequences mr (45%) are predominant in PMMA 6N. A similar

tacticity is found for PMMA 7N with the syndiotactic sequences rr (46%) and atactic

sequences mr (43%). For PMMA 8N, the syndiotactic sequences rr (49%) and atactic

sequences mr (42%) are predominant.

Table 3.1 Properties of the polymers used in this work.

Material Product

Density (g/cm3)

𝑴𝒘

(kg/mol) 𝑴𝒘/𝑴𝒏 𝑻𝒈(°С) Room

temperature 200 °Ϲ

PLA

PMMA

Ingeo 4032D

Plexiglas 8N

1.24

1.19

1.12

1.13

210

116

1.75

1.99

60

117

PMMA Plexiglas 7N 1.19 1.13 92 1.93 110

PMMA Plexiglas 6N 1.19 1.13 65 2.07 96

3.3 Sample preparation 29

3.2 Filler materials

Three different types of spherical silica particles were used in this study. For convenience, we

record these three particles as silica 300, silica OX50 and silica 63, respectively. They have

different average primary particle size 𝑑 and specific surface area (SSA, measured by BET-

method). The characters of these silica particles are given in Table 3.2 and Figure 3.1. The

silica particles are all spherical, and all silica particles were used as received without any

further treatments.

Figure 3.1 SEM images of silica particles (a) silica 300, (b) silica OX50, (c) silica 63.

Table 3.2 The characterizations of three kinds of silica particles.

Silica Supplier 𝒅 (𝐧𝐦) SSA (m2/g) Density (g/cm

3)

AEROSIL® 300 Evonik

Industries AG

7 300±30 2.2

AEROSIL®

OX50

Evonik

Industries AG

40 50±15 2.2

TIXOSIL 63 Rhodia Group 9000 55±5 2.2

3.3 Sample preparation

All the composites and blends used in this work are listed in Table 3.3. Before the melt

mixing, the polymers were dried at 80 °С under vacuum for more than 6 h to remove moisture

to prevent hydrolytic degradation of the PLA and PMMA. In addition, the silica particles

were dried in a vacuum oven at 80 °С for more than 24 h to remove moisture.

30 3. Material and sample preparation

Table 3.3 The PLA/silica composites, PLA/PMMA blends and PLA/PMMA/silica

nanocompsoites used in this work.

polymer matrix filler/blend Filler/blend

content

Mixing

temperature (°C)

PLA

silica 300 0, 1.1, 2.8, 5.8,

9.0 vol. % 180 silica OX 50

silica 63

PLA PMMA 7N

100/0, 90/10,

70/30, 50/50,

30/70,10/90,

0/100 (wt. /wt.)

200

PLA

PMMA 6N

PMMA 7N

PMMA 8N

50/50 (wt. /wt.) 200

PLA/PMMA 50/50

silica 300 0, 2, 5, 10 wt. % 200

PLA/PMMA 80/20 silica 300 0, 2 wt. % 200

3.3.1 Preparation samples for rheological measurements

In order to compare the difference of rheological properties of PLA induced by silica particles

of various sizes, an internal mixer (Haake polyDrive, Thermo Scientific, Germany) was used

to prepare the PLA/silica composites with 1.1, 2.8, 5.8 and 9.0 vol. % of silica (silica 300,

silica OX50, silica 63). The melt mixing was carried out at 180°C for 10 min with a rotational

speed of 100 rpm. For comparison, the neat PLA was subjected to the same treatment as the

composite. For rheological measurement, the samples are compression molded after extrusion

to 2 mm thick disk-shape plates with a diameter of 25 mm at 180 °C and 200 bars. Prior to the

blending and the measurements, all the samples were dried in a vacuum oven at least 12h at

80 °C to remove moisture.

PLA and PMMA (PMMA 7N) with different compositions (100/0, 90/10, 70/30, 50/50, 30/70,

10/90, 0/100 by weight) were melt mixed by means of an internal mixer (Haake polyDrive,

Thermo Scientific, Germany) at 200 °C for 10 min with a rotational speed of 100 rpm. Then,

the materials were hot pressed (T= 200 °C) into: sheets and disk-shape plates. The sheets with

a dimension of 85 mm × 85 mm × 0.3 mm were compression molded. After that, rectangular

3.3 Sample preparation 31

films of 25 mm × 5 mm were cut from the central part of the sheets for shape memory and

DMTA tests. The disk-shape plates with a diameter of 25 mm and 2 mm thickness were

prepared for rheological measurements at the same conditions as the sheets.

In order to study the influence of nanosilica on the dynamic rheology and molecular

entanglement of PLA/PMMA blends, PLA/PMMA (PMMA 7N) (weight ratio: 50/50) with

nanosilica (silica 300) contents of 0, 2, 5 and 10 wt% were melt mixed at 200 °C and 100 rpm

for 10 min with an internal mixer (Haake polyDrive, Thermo Scientific, Germany). In order to

compare the interaction between nanosilica with the components, neat PLA, neat PMMA,

PLA/10 wt% nanosilica and PMMA/10 wt% nanosilica were prepared at the same conditions.

The samples were then compression molded to two shapes at 200 °C. Rectangular films with

a dimension of 25 mm × 5 mm × 0.3 mm were prepared for differential scanning calorimetry

(DSC) test and dynamic mechanical thermal analysis (DMTA). Disk-shape plates (25 mm

diameter, 2 mm thickness) were made for dynamic rheological measurements. For

convenience, the processed neat PLA/PMMA blend and PLA/PMMA/silica nanocomposites

are, respectively, designated as P/P/Si x in the following discussion, and x represents the

silica weight content (wt %) in the nanocomposite.

In order to investigate the effect of the molar mass of PMMA on the molecular entanglements

and viscoelastic properties of symmetric PLA/PMMA blends, PLA/PMMA 50/50 blends

(PMMA 6N, PMMA 7N, PMMA 8N) were prepared by melt-blending at 200 °C and 100 rpm

for 10 min by an internal mixer (Haake PolyDrive, Thermo Scientific, Germany), respectively.

Neat PLA and PMMA are also prepared by the same way as reference samples. The samples

were then compression molded to 2 mm thick disk-shape plates with a diameter of 25 mm at

200 °C. Disk-shape plates of neat PLA and PMMA with 25 mm diameter and 1 mm thickness

were also prepared to make symmetrical bilayers based on PLA and PMMA.

32 3. Material and sample preparation

3.3.2 Preparation of cast films for biaxial stretching

Neat PLA, PLA/PMMA 80/20 blend and nanosilica (silica 300, 2wt%) filled PLA/PMMA

80/20 blend were first extruded through a slit die by a twin screw extruder at 200 °C followed

by cooling in a water bath unit, whose temperature was set to 20 °C. The samples were

granulated and then extruded through a wide flat die into cast film with a thickness of 0.3 mm.

The cast films were cut into 85 mm 85 mm specimens to be used in a Brückner laboratory

biaxial stretcher. The nanosilcia used here is silica 300, which is untreated before blending.

3.3.2 Preparation of biaxially stretched films

These cast films were then stretched in the partly molten state at temperatures of 80 and 90 °C

on a Brückner biaxial stretching device. In this work, the simultaneous stretching mode is

used and the strain rate changes from 20%/s to 100%/s. Before the stretching process, the

samples were pre-heated for 40 s to reach the desired temperature in the hot-air oven. Samples

were then stretched and then finally quickly cooled to room temperature. For each test, the

load and time were recorded and converted into stress vs. biaxial draw ratio curves. The

samples were then used for shape memory testing.

4. Characterization methods

4.1 Analytical characterization

4.1.1 Size exclusion chromatography (SEC)

The information of the molar mass 𝑀𝑤 and molar mass distribution 𝑀𝑤/𝑀𝑛 of PLA and

PMMA were obtained by size exclusion chromatography (GPCmax, Malvern). For PMMA,

the measurements were carried out at 25 °C with tetrahydrofuran (THF) and a constant flow

rate of 1 ml/min. In our study, the GPC calibration standard is PS. The lowest value of

polymer nominal 𝑀𝑃 is 580 g/mol, the highest value of 𝑀𝑃 value is 6870000 g/mol, and

𝑀𝑊/𝑀𝑛 is ca. 1.0.

4.1.2 Thermogravimetric analysis (TGA)

In order to determine the thermal stability of samples, thermogravimetric analysis (TGA 2950,

TA Instruments) were carried out under a nitrogen atmosphere. A constant heating rate of

10 °C/min is applied and the weight loss is recorded with a thermo-scale. The samples with an

initial weight of 20 mg to 30 mg were heated up to 500 °C.

4.1.3 Differential scanning calorimetry (DSC)

The thermal behavior is characterized using differential scanning calorimetry (DSC, TA

Q2000, TA Instruments, USA) under nitrogen. All samples were heated from ambient

temperature to 200 °C at a heating rate of 10 °C /min, kept there for 3 min to eliminate the

thermal history, and then cooled down to 20 °C at a rate of 10 °C/min. A second heating run

at the same conditions as the first one was applied in order to determine the glass transition

temperature 𝑇𝑔, taken at the inflection point of heat flow change. The degree of crystallinity

𝑋𝑐 of PLA and its semi-crystalline blends can be calculated by subtracting the cold

34 4. Characterization methods

crystallization enthalpy from the melting enthalpy, taking the concentration of PLA in the

blend (𝑤 ) into account (as shown in Equation 4.1). The melting enthalpy 𝐻𝑓𝑜 of 100%

crystalline PLA is 93 J/g.

𝑋𝑐 = 𝐻𝑓/(𝐻𝑓𝑜𝑤) (4.1)

4.2 Morphological characterization

Field Emission Scanning Electron Microscope (FE-SEM) (LEO 435 VP, Carl Zeiss

Microscopy, Germany) was used to investigate the morphology of silica particles and the

distribution of silica in the polymer matrix, as well the morphology of the fracture surface of

blends and composites. Before SEM observation, the molded specimens were fractured in

liquid nitrogen to get undeformed fracture surfaces and then coated with gold using Sputter

Coater S150B from Edwards.

4.3 Rheological characterization

4.3.1 Dynamic mechanical thermal analysis (DMTA)

Dynamic mechanical thermal analysis (DMTA) was conducted by means of DMTA IV

(Rheometric Scientific, USA) in the tensile mode. The dynamic storage and loss moduli were

determined as a function of temperature from 15 to 150 °C at a frequency of 1 Hz and a

heating rate of 2 °C/min. Herein, the glass transition temperature of the amorphous phase is

determined from the peak in the curve of loss modulus 𝐸′′ (also named -relaxation

temperature).

4.3.2 Oscillatory shear rheology

The rheological measurements were performed under a nitrogen atmosphere using ARG2

rheometer (TA-ARG2, TA Instruments, USA) in plate-plate geometry (25mm diameter, 2mm

4.3 Rheological characterization 35

gap). A new sample was used for each run, and a waiting time of 5 min was applied for each

test. The reproducibility for all rheological experiments in shear was better than ± 5% (as

shown in Appendix).

4.3.2.1 Dynamic mechanical experiment

In order to determine the linear viscoelastic region, dynamic strain sweep was performed first.

Figure 4.1 schematically illustrates the strain sweep in the linear region and nonlinear region.

The viscoelastic response can be quantified by two parameters: elastic storage modulus 𝐺′(𝜔)

and the viscous loss modulus 𝐺′′(𝜔). In the linear regime, the strain amplitude is sufficiently

small and both viscoelastic moduli are independent of strain amplitude. A strain level γ = 1%

was chosen for the linear rheological measurements.

Figure 4.1 Schematic illustration of the strain sweep test at a fixed frequency.

The oscillatory time sweeps at low frequencies were performed to ensure the long time

rheological tests were carried out in linear range, angular frequency of 0.1 rad/s and strain of

1% were adopted. 𝐺′ in the terminal region is very sensitive to detect molecular changes,

corresponding to the thermal stability of the sample. A maximum change in the storage

modulus 𝐺′ of 5 % from the initial value was used to estimate the range of thermal stability.


Oscillatory frequency sweeps ranging from 0.1 (or 0.05) to 500 rad/s were performed at

different temperatures for neat PLA and PLA composites. The storage modulus 𝐺′, the loss

modulus 𝐺′′ and complex viscosity |𝜂∗| were recorded as functions of angular frequency.

4.3.2.2 Creep and creep recovery experiment

In order to ensure the rheological tests were performed in the linear regime, the stress

dependence of the creep compliance and recoverable compliance were performed on neat

PLA and its composites in a stress range from 20 to 500 Pa at a temperature of 180 °C or

200 °C.

The creep compliance 𝐽𝑐𝑟(𝑡𝑐𝑟) of PLA and the composites can reach the constant double

logarithmic slope of one in ca. 1000 s, which indicated that after this time the creep

compliance reached the terminal flow zone. In consideration of the thermal stability of PLA, a

creep time 𝑡0=2000 s was chosen. The duration of the recovery section did last twice the time

of the creep section, and the experiments also proved that the recovery time of 𝑡𝑟 = 4000 s

was sufficient to reach the steady state for all the samples.

4.4 Shape memory characterization

The shape memory characterization experiments were carried out by means of DMTA IV

(Rheometric Scientific, USA) in the film tension mode. Rectangular films with the same

dimensions as for dynamic mechanical measurements were used. The whole process of the

shape memory test is shown in Figure 4.2. The sample was first uniaxial stretched to an

extensional strain of = 100% with a strain rate of 0.02 s-1

at the sample’s 𝑇𝑔 . The

deformation was frozen in by quenching the sample to ambient temperature by liquid nitrogen.

The shape recovery potential was quantified by a thermal shrinkage test. The stretched films

were put into an oil bath at a temperature of the sample’s 𝑇𝑔 +10 °C for 120 s, and then

4.4 Shape memory characterization 37

rapidly cooled down to room temperature. The time of 120s is sufficient for complete

recovery.

Two quantities were determined from this test. The shape fixing ratio 𝑅𝑓

𝑅𝑓 =𝐿2−𝐿0

𝐿1−𝐿0 × 100% (4.2)

quantifies the amount of deformation that was lost during the cooling and is, therefore, not

available for the shape recovery process, while the shape recovery ratio 𝑅𝑟

𝑅𝑟 =𝐿2−𝐿3

𝐿2−𝐿0 × 100% (4.3)

is a measure of the effectiveness to recover the initial shape.

Figure 4.2 Schematic diagram for shape memory test of PLA/PMMA blend.

In this work, neat PLA, PLA/PMMA 80/20 blend and PLA/PMMA 80/20 blend filled with

2wt% nanosilica were chosen to produce biaxially stretched films. The cast films were first

cut into 85 mm 85 mm specimens. Same stretching temperature (80 °C/90 °C) were chosen

in this work to draw films at a strain rate of 20%/s up to different stretch ratios .


Figure 4.3 Schematic diagram for shape memory test of biaxially stretched films.

In order to measure the shape memory properties of biaxially stretched films, the cast films

were treated under a specific temperature-deformation program as shown in Figure 4.3. The

recovery temperature is 10 °C higher than the stretching temperature. The shape fixing ratio

𝑅𝑓 and shape recovery ratio 𝑅𝑟 can be determined according to Equations (4.2 and 4.3).

5. PLA/silica composites

As discussed in Chapter 2, adding particles into polymers is a commonly used way to improve

the polymers’ mechanical properties and processibility due to the interactions between

particles and polymer matrix. It is well established that the mechanical properties of polymers,

such as stiffness, strength and toughness, are significantly influenced by particles size,

particle/matrix interface adhesion and particle loading [Fu et al. (2008)]. Nofar et al. [Nofar et

al. (2013)] reported the effects of various additives with different sizes on the crystallization

kinetics of PLA, and Katsikis et al. [Katsikis et al. (2007)] studied the thermal stability of

PMMA/silica nano- and microcomposites by dynamic-mechanical experiments. However,

there is little publication focus on the correlation between particle size and rheological

behavior in PLA/silica system. In this work, three types of silica particles from micro- to

nano- were chosen to fill PLA, and the viscous and elastic properties of PLA with different

silica concentrations were fully studied by dynamic-mechanical experiments and creep-

recovery experiments. In addition, a model was proposed to describe the interactions between

polymer matrix and particles. The correlation between particles size and rheological behavior

of PLA/silica composites was fully analyzed.


The morphologies of silica particles and the fracture surfaces of PLA/silica composites with

silica loading of 2.8 vol. % are shown in Figure 5.1. It can be seen that the geometries of three

types of silica particles are similar to spherical shape, and the particle size increases from

silica 300 to silica 63. As for PLA/silica composites, silica particles were detected as white

dots. As shown in Figure 5.1a’and b’, some silica agglomerates with diameters of hundred

nanometers can be observed in the nanocomposites, but the overall dispersion of the

nanosilica is quite good in the matrix. The agglomerates of nanosilica possess a significant

40 5 PLA/silica composites

porous structure, which means the polymer melt can infiltrate the agglomerates and interact

with the surface of nanoparticles [Münstedt et al. (2010)]. Furthermore, note that the

microsilica particles also disperse well in the polymer matrix (as shown in Figure 5.1c).

However, the interaction between microsilica and matrix is relatively weak, and some

particles nearly split away from polymer matrix at the fracture surface.

Figure 5.1 SEM images of silica particles and the fracture surfaces of composites with silica

loading 2.8 vol. %. (a) silica 300 (a’) PLA/silica 300 (b) silica OX50 (a’) PLA/silica OX50

(b’) silica 63 (c’) PLA/silica 63.

5.2 Thermal behavior 41

5.2 Thermal behavior

The thermograms of PLA/silica composites with various silica concentrations obtained by the

second heating scan are shown in Figure 5.2. The neat PLA exhibits a glass transition

temperature 𝑇𝑔 around 60 °C, while the cold crystallization peak 𝑇𝑐 is centered at 112.3 °C.

With the addition of silica particles, there is no change of 𝑇𝑔 can be observed, while the cold

crystallization peak and the melting peak are significantly influenced.

Figure 5.2 DSC curves of neat PLA and PLA/silica composites at heating rate of 10 °C/min.

(a) PLA/silica 300 (b) PLA/silica OX50 (c) PLA/silica 63.


Two melting peaks corresponding to α and α’ crystals [Pan et al. (2007)] can be clearly

observed between 160 to 170 °C for neat PLA. For neat PLA, this bimodal melting peak is

due to the melting of the imperfect α crystals and the formation of more perfect α’ crystals at

high temperature [Zhang et al. (2014)]. The presence of silica particles reduced the melting

peak of the α crystal, which indicates the perfect degree of crystallization for PLA is

improved. For all the composites, the cold crystallization enthalpy 𝐻𝑐𝑐 is reduced with the

addition of silica, and 𝑇𝑐 shifts to lower temperatures, of the range of 106.0-112.3 °C,

depending on the silica concentration and the particle size. The crystallinity (𝑋𝑐) of PLA can

be calculated by subtracting the cold crystallization enthalpy from the melting enthalpy,

taking the content of PLA in the mixtures (𝑤) into account (as shown in Equation 4.1). The

melting enthalpy of 100% crystalline PLA is taken as 93 J/g [Zhang et al. (2003)]. The values

of 𝑇𝑔, 𝑇𝑐 and 𝑋𝑐 of PLA in PLA/silica composites obtained from the second heating scan are

listed in Table 5.1.

Table 5.1 The values of 𝑇𝑔, 𝑇𝑐, 𝐻𝑐𝑐 and 𝑋𝑐 of PLA in PLA/silica composites in the second

heating scan.

silica concentration

(vol. %) 𝑻𝒈 (°C) 𝑻𝒄 (°C) 𝑯𝒄𝒄 (J/g) 𝑿𝒄(%)

PLA 0 60.0 112.3 26.2 6.5

PLA/silica

300

1.1 60.0 106.0 23.4 10.4

2.8 60.0 106.0 22.9 11.1

5.8 60.0 106.0 19.5 13.9

PLA/silica

OX50

1.1 60.0 107.2 24.9 7.9

2.8 60.0 107.2 22.5 8.5

5.8 60.0 107.2 21.4 10.7

PLA/silica 63

1.1 60.0 111.5 26.2 6.6

2.8 60.0 107.8 21.8 8.7

5.8 60.0 107.2 20.8 10.1

Obviously, the crystallinity of PLA is improved by the addition of silica particles, and 𝑋𝑐

increases with silica loading. The impact of silica 300 on 𝑋𝑐 is more prominent compared to

silica OX50 and silica 63, which is due to the effect of particle size. Therefore, it can be

5.2 Thermal behavior 43

concluded that in PLA/silica composites, silica particles work as nucleating agents and

improve the crystallinity of PLA. At the same filler concentration, the nanosilica with smaller

particle size provides much more nucleating agents, and therefore shows a more remarkable

impact on the crystallization of PLA.

5.3 Rheological investigation

5.3.1. Linear viscoelastic region

The linear viscoelastic region of the PLA matrix and the PLA/silica composites with the

highest silica concentration is determined by a dynamic strain sweep at 180 °C with a

frequency of 1 Hz (ω=6.28 rad/s). Figure 5.3 shows the dependence of storage modulus 𝐺′ on

the strain amplitude γ from 0.01% to 100% for neat PLA and PLA/9 vol. % silica composites

(the maximum silica concentration in this work). Apparently, the linear viscoelastic region of

the composites was reduced by the addition of silica, and the reduction was more pronounced

for silica 300 which has the smallest particle size. Therefore, all following oscillatory shear

rheological measurements were conducted at γ = 1%.

Figure 5.3 Dynamic strain sweeps for neat PLA and PLA/9 vol.% silica composites at 180 °C

with a frequency of 1 Hz (ω=6.28 rad/s).


5.3.2. Thermal stability

When long measuring time and high temperatures are applied, a precondition for reliable

rheological measurement is the thermal stability of the material. Particularly, PLA is easier to

degrade in comparison with petroleum-derived polymers when exposed to elevated

temperatures for a long time.

A very common way to evaluate the thermal stability of samples in molten state is to measure

the storage modulus 𝐺′ as a function of time at a defined temperature in the terminal region

(𝜔=0.05 rad/s) [Katsikis et al. (2007), Münstedt et al. (2010)]. Figure 5.4 shows the thermal

stability tests of PLA without and with 2.8 vol. % silica at the processing temperature 180 °C.

Samples are regarded to be stable as long as the deviation of 𝐺′(𝑡)/𝐺0′ is smaller than 5% (𝐺0

′

is the storage modulus at 𝑡=0). In this experiment, a moderate silica concentration (2.8 vol. %)

was chosen to investigate the thermal stability of composites due to the increase of 𝐺′(𝑡)/𝐺0′

induced by the particle diffusion at higher silica concentration.

Figure 5.4 Relative change of storage modulus as a function of the residence time at 180 °C

for neat PLA and PLA mixed with 2.8 vol. % silica.

As can be seen from Figure 5.4, the stable time for neat PLA is about 5000 s at 180 °C and a

slight increase (approximately 1000 s) can be found after mixing with 2.8 vol. % microsilica.

5.3 Rheological investigation 45

At the same temperature, the stable time for PLA/nanosilica mixtures significantly increase to

ca. 8000 s. In addition, it is found that the thermal stability of PLA/silica 300 is better than

PLA/silica OX50 nanocomposite, which may arise from the smaller particles size and larger

SSA of silica 300. The results indicate that the addition of silica particles could improve the

thermal stability of PLA, and the particles with smaller size will lead to a greater

enhancement. The results of thermal stability measurements also provide a time limitations

for the long time rheological measurement.

5.3.3. Dynamic mechanical experiments

The presence of various silica particles has different influence on the linear viscoelasticity of

PLA matrix. Figure 5.5 shows the frequency dependence of storage modulus 𝐺′ (Figure 5.5a,

b and c) and complex viscosity |𝜂∗| (Figure 5.5a’, b’ and c’) with various silica types and

silica concentrations at 180 °C. At low frequencies, the neat PLA shows the typical terminal

behavior with the scaling of 𝐺′ ∝ 𝜔2, which is consistent with the linear viscoelastic theory.

For PLA/silica 300 nanocomposites (Figure 5.5a), 𝐺′ at the low-frequency region increases

with the addition of nanosilica prominently and reaches an approximately frequency-

independent plateau at the high concentration (above 2.8 vol. %). At the high concentration

level, PLA/silica 300 nanocomposites exhibit solid-like response in the low frequency region,

indicating the formation of a percolated silica network [Wu et al. (2006)]. It is noteworthy that

the terminal behavior of PLA disappears gradually with increased nanosilica loading, and no

zero shear viscosity could be detected after the formation of interparticle network (as shown

in Figure 5.5a’). In Figure 5.5b and b’, the moduli and viscosity of PLA/silica OX50

nanocomposites exhibit similar response to the increased silica concentration. However, the

impact induced by silica OX50 is less pronounced due to its relatively larger particle size (40

nm). The nanocomposites do not display solid-like response even at the maximal silica

concentration in this work.


Figure 5.5 Storage modulus (𝐺′) and complex viscosity |𝜂∗| as function of angular frequency

ω for PLA/silica composite with various silica concentrations. (a, a’) PLA/silica 300 (b, b’)

PLA/silica OX50 (c, c’) PLA/silica 63.

The effect of microsilica (silica 63) on the rheological properties is shown in Figure 5.5c and

c’. It is found that the influence induced by microsilica on 𝐺′ and |𝜂∗| is extremely weak in

comparison with nanosilica. With the increased microsilica loading, 𝐺′ varies negligibly in the


high frequency region, and just a slight increase is found at the low frequency range. The

terminal region also disappeared with the addition of high content of microsilica. Moreover,

the viscosity of the microcomposite shows slight dependence on the addition of silica due to

the weak interaction between microsilica and PLA matrix.

As discussed above, 𝐺′ in the low frequency region is more sensitive to silica loading. In

order to investigate the effects of different silica particles on linear rheological properties of

PLA, storage moduli of the composites at a fixed frequency of 0.1 rad/s as a function of silica

concentration are plotted in Figure 5.6. The results show that silica 300 lead to a dramatic

increase in the rheological properties at high silica concentrations, and the inflection point can

be considered as the rheological percolation threshold φ𝑐. No inflection point can be observed

for PLA/silica OX50 and PLA/silica 63 system in the whole concentration range.

According the results shown in Figure 5.5 and 5.6, φ𝑐 for PLA/silica 300 nanocomposites is

between 2.8 vol. % and 5.8 vol. %. While φ𝑐 for PLA/silica OX50 and PLA/silica 63 are both

above 9 vol. %. Moreover, the effect of silica OX50 is less effective in comparison with silica

300 due to its relatively larger particle size. The microsilica shows the least impact on the

rheological properties.

Figure 5.6 Storage modulus (𝐺′) of PLA reinforced with various silica particles at a fixed

frequency of 0.1 rad/s as a function of silica concentration: (a) PLA/silica composites below

the rheological percolation threshold φ𝑐, (b) PLA/silica 300 in the whole concentration range.


5.3.4. Creep-recovery experiments

In order to investigate the melt elasticity of composites and reliably get insight into the

interactions between particles and polymer matrix, creep-recovery experiment has been

proved to be a good choice [Lamnawar et al. (2011), Triebel and Münstedt (2011)].

5.3.4.1. Stress dependence of creep-recoverable compliance

It has been demonstrated that the interaction between polymer matrix and filler is responsible

for the increased retardation time that determines the recoverable compliance [Lamnawar et al.

(2011)]. The applied creep stress could significantly influence the number of adherent

molecules. In order to apply the creep-recovery experiment in the linear region, the following

recoverable compliance should be independent on the creep stress. Therefore, the dependence

of the recoverable compliance on creep stress was evaluated on neat PLA and PLA/silica

composites in a stress range from 20 to 500 Pa at 180 °C. As can be seen from Figure 5.7a, a

double logarithmic slope of 1 is reached in the terminal flow zone for all the creep curves, and

the creep curves and recoverable curves of neat PLA at different stresses overlap each other

perfectly, i.e., the experiments are all performed in the linear range of deformation. The

recoverable compliance of neat PLA is found to be a constant value of Je0 =1.7×10

-5 Pa

-1 at

180 °C, and PLA shows a linear behavior in the whole stress range applied.


Figure 5.7 Stress dependence of the creep compliance and recoverable compliance for (a)

neat PLA, (b) PLA/silica 300, (c) PLA/silica OX50 and (d) PLA/silica63 composites with a

filler fraction of 2.8 vol. % at 180 °C.

Similar measurements were performed on PLA/silica composites with a filler concentration of

2.8 vol. %. As shown in Figure 5.7b, c, and d, the creep compliances don’t show any

noticeable dependence on the creep stress, but the recoverable compliances exhibit

remarkable stress dependence. The recoverable compliance curves applied at 20 Pa and 50 Pa

are almost overlap, indicating the creep-recovery experiments are performed at linear region

of deformation. Starting at a stress of 200 Pa, the steady-state recoverable compliances

decrease with increased creep stress. Therefore, a pronounced nonlinearity occurs when the

creep stress is larger than 200 Pa for the filled samples. This result may be induced by the


disintegration of attached molecules from the particles surfaces [Münstedt et al. (2010)].

Based on these results, a stress of 50 Pa can be chosen for the creep experiments.

5.3.4.2. Creep time dependence of creep-recoverable compliance

Figure 5.8 Creep-recovery compliance as a function of recovery time of PLA/2.8 vol. %

silica 300 composite following various creep times 𝑡𝑐𝑟.

In order to ensure that a steady state of the preceding creep behavior was fully reached, the

recovery compliances of PLA/2.8 vol. % silica 300 composite following different preceding

creep time 𝑡𝑐𝑟 (2000 s, 3000 s, 4000 s) at 180 °C are displayed in Figure 5.8. For a creep time

of 2000 s, the plateau in the recoverable compliance is found to be 0.0073 Pa-1

. An increase of

the creep time (up to 3000 s) results in a plateau of 0.0074 Pa-1

at the same experimental

condition. When the creep time is 4000 s, the plateau is around 0.0078 Pa-1

. The difference

between these plateaus is quite small, indicating that an increase of the creep time doesn’t

change the recoverable compliance. Hence, the creep time 𝑡𝑐𝑟=2000 s is long enough to reach

the steady state.


5.3.4.3. Temperature dependence of creep-recoverable compliance

The temperature dependence of creep-recovery compliance for neat PLA and PLA/2.8 vol. %

silica 300 composite are shown in Figure 5.9. Both the creep curves of neat PLA and the

composite are increasing with the increased temperature due to the lower viscosity at higher

temperatures. It evident that the linear steady state recoverable compliance of the neat PLA is

independent of temperature and attains a value of Je0 =1.7×10

-5 Pa

-1. However, for PLA/silica

composites, the steady state recoverable compliance shows a weak temperature dependence.

As shown in Figure 5.9b, the steady state recoverable compliance obtained at lower

temperatures is smaller than that determined at higher temperatures.

Figure 5.9 Temperature dependence of the creep compliance and recoverable compliance for

neat PLA and PLA/silica composites with a filler fraction of 2.8 vol. % at the temperature

range of 180-210 °C.

5.3.4.4. Concentration dependence of creep-recoverable compliance

The creep and recoverable compliance in dependence on the silica concentration are shown in

Figure 5.10. For PLA/silica 300 and PLA/silica OX50 nanocomposites, the creep compliances

decrease observably with the addition of nanosilica when the filler concentration is above 1.1

vol. %, corresponding to the increase of viscosity of the composites. A double logarithmic


slope of 1, indicating the steady state of creep compliance, is reached in the terminal flow

zone for the creep curves when the filler’s concentration is below φ𝑐. On the other side, when

the nanosilica concentration is above φ𝑐, such as PLA/5.8 vol. % silica 300 (as shown in

Figure 5.10a), there is no steady state reached with the increase of creep time, while the creep

curve approaches closely to a plateau at very long creep time. According to Ferry [Ferry

(1980)], this effect can be explained due to the formation of network phase.

Figure 5.10 Creep-recovery experiments on PLA filled with various volume fractions of

silica (a) silica 63 (b) silica OX50 (c) silica 300.

As for the following recovery stage, when the filler’s concentration is below φ𝑐 , the

recoverable compliance shows a significant increase with the addition of silica and then a

decrease after a critical concentration value. Therefore, it can be concluded that the highest

value of 𝐽𝑒0 of polymer/nanosilica system occurs at the filler concentration around φ𝑐. When


the filler’s concentration is above φ𝑐, the difference between the curves of creep compliance

and recoverable compliance is extremely small, indicating the solid-like behavior of the

samples.

For polymer/microsilica system as shown in Figure 5.10c, the curves of creep compliance

display little change with the increase of silica fraction, but the recoverable compliance

significantly increases. The magnitude of the increment is amazing even at low filler

concentration.

5.3.4.5. A comparison between complex viscosity and creep compliance

Figure 5.11 Complex viscosity |𝜂∗| as a function of ω in comparison with 𝑡/𝐽(𝑡𝑐𝑟) in

dependence on creep time 𝑡 at 180 °C.

In Figure 5.11, the magnitude of the complex viscosity as a function of the angular frequency

is compared with 𝑡/𝐽(𝑡𝑐𝑟) as a function of creep time 𝑡 for PLA filled with silica particles.

The same filler fraction of 2.8 vol. %, which is below φ𝑐 for all PLA/silica systems was

chosen. According to Equation (2.7), the quantity of 𝑡/𝐽(𝑡𝑐𝑟) at long enough time is equal


to 𝜂0 , and this correlation is proved in Figure 5.11. These results also demonstrate the

accuracy and consistency of these two experimental methods [Münstedt et al. (2010)].

5.3.5. Zero shear viscosity and steady-state compliance

The zero shear viscosity is significantly influenced by the addition of fillers [Bhattacharya et

al. (2008)]. As shown in Figure 5.12, a linear relation between 𝑙𝑜𝑔𝜂0 and silica concentration

is found when the filler concentration is below φ𝑐,

𝑙𝑜𝑔𝜂0 = 𝑎 + 𝑏 (5.1)

The slopes 𝑎 for PLA/silica 300, PLA/silica OX50 and PLA/silica 63 composites are 10.6, 5.1

and 0.7, respectively. It can be concluded that the particles with larger size could induce a

slow growth rate of zero shear viscosity.

Figure 5.12 Zero shear viscosity 𝜂0 as a function of filler fraction for PLA/silica composites.

The linear steady state elastic compliance 𝐽𝑒0 is also presented as a function of filler

concentration in Figure 5.13. 𝐽𝑒0 for neat PLA is around 1.710

-5 Pa

-1. When the filler

concentration is below φ𝑐, the elastic properties of the composites increase with the addition

of silica more rapidly for the PLA/nanosilica system in comparison with the PLA/microsilica

system, and the growth rate is strongly depend on the particles size. At the same filler faction


of 2.8 vol. %, an increase by a factor of 10 was found for PLA/silica 63, while the increase

factor of PLA/silica 300 and PLA/silica OX50 is 200 and 60, respectively. Compared to the

results shown in Figure 5.12, it is found that 𝐽𝑒0 is distinctly stronger influenced by the

addition of particles than 𝜂0.

Figure 5.13 Steady-state compliance 𝐽𝑒0 as a function of filler fraction for PLA/silica

composites.

5.4 A model to describe the interactions in PLA/silica composites

Understanding the interactions in polymer/particle systems is a key element to reveal the

structure-property correlations for polymer composites. In particular, the flow characteristics

of the composites during processing at molten state are significantly influenced by the

interactions in the materials. In PLA/silica system, the main interactions included particle-

polymer interaction and particle-particle interaction [Asakura and Oosawa (1958), Fu et al.

(2008)]. A theoretical network model is verified in the following section.

5.4.1 Interaction between silica particles and PLA matrix

With the incorporation of silica into the PLA matrix, the interactions between particles and

polymer matrix can significantly influence the thermo-mechanical and rheological properties

of the composite [Sarvestani and Picu (2004), Bhattacharya et al. (2008)]. PLA molecules are


assumed to attach on the surface of silica particles by physical adhesion forces, which will

hinder the mobility of those PLA molecules and lead to longer retardation times. In

PLA/silica composites, the primary adhesion forces between silica particles and PLA matrix

are the Van-der-Waals forces, which can be enhanced by increasing the particle contact area

[Hays et al. (1996), Quesnel et al. (2002)]. The particle surface area for silica 300, silica

OX50 and silica 63 can be easily calculated as all these silica particles are spherical and

monodisperse. Based on the specific surface area of each particle listed in Table 3.2, the

particle surface areas in m2 per cm

3 of PLA/silica composites can be calculated as a function

of the volume fraction (as shown in Figure 5.14).

Figure 5.14 Specific particles surface area in m2 per cm

3 for PLA/silica composites as a

function of silica concentration.

It is evident that the increase of surface area as a function of concentration for silica 300 is

much stronger than that of silica OX50 and silica 63. Although silica OX50 is in nano-scale,

but its SSA is relatively small. The specific particles surface area for silica OX50 is similar

with that of silica 63, indicating the Van-der-Waals forces in both PLA/silica composites are

similar with each other. However, the viscosity and elasticity for PLA/silica OX50

nanocomposites are much larger than that of PLA/silica 63 microcomposites at the same filler

5.4 A model to describe the interactions 57

concentration (as shown in Figure 5.12 and 5.13). This result demonstrates that the particle

size play a crucial role in the polymer/filler composites.

The existence of hydrogen-bonding interactions between the Si-OH and the C=O of PLA

chains has been reported in the previous work [Wen et al. (2009), Li et al. (2012)] . As shown

in Figure 5.15, silica particles possess Si-OH groups on the surfaces, and PLA has C=O

groups in the molecular chains. Therefore, hydrogen bonding interactions between PLA and

silica may exist, and this assumption is proved by Fourier transform infrared (FTIR) analysis

[Wen et al. (2009)]. All silica particles have a similar chemical structure, but the surface area

per volume unit for microsilica is much lower compared to nanosilica. For the equal filler

fraction, the total specific surface area of nanosilica is relatively larger. Hence, nanosilica can

adsorb more polymer molecules and result in greater interactions in comparison with

microsilica. Although nanosilica will form some loose agglomerates in the polymer matrix,

these agglomerates possess a significant porous structure, which means the polymer melt can

infiltrate the agglomerates and still interact with the surface of nanoparticles [Münstedt et al.

(2010), Triebel (2011)].

Figure 5.15 Schematic illustrations of the hydrogen-bonding interactions between the PLA

and silica particles.


Therefore, it can be concluded that the interactions between particles and polymer molecules

are mainly determined by the particle size and specific surface area in PLA/silica composites,

and this interaction can significantly hinder the mobility of the attached PLA molecules. The

formation of hydrogen-bonding interactions between the PLA and silica particles increased

the thermal stability of PLA, which can be used to interpret the better stability of PLA/silica

composites in comparison with unfilled PLA.

5.4.2 Interaction between silica particles

Generally speaking, the interaction between small particles is mainly determined by the

attractive forces like Van-der-Waals forces and repulsing forces like electrostatic forces

[Hamaker (1937)]. However, the attractive forces between nanoparticles get very pronounced

due to the large specific surface area, which makes the repulsing forces can be ignored. In this

case, the attractive forces will lead to the formation of agglomerates [Rhodes (1981), Zhang et

al. (2004)]. Moreover, from the chemical point of view, reactions of hydroxyl groups on the

surface of silica particles under the elimination of a water molecule are possible when the

distance between particles is very small [Bakar et al. (2009), Kourki and Famili (2012)]. This

chemical reaction also contributes to the formation of nanosilica agglomerates.

In polymer/nanoparticles mixture, the interactions between particles can be ignored at low

filler contents, which are below the rheological percolation threshold φ𝑐. However, a particle

network will be formed when the filler content exceeds φ𝑐. A theoretical network model was

proposed by Sarvestani [Sarvestani and Picu (2004)], they suggested that the polymeric chains

would bridge neighboring fillers and form a nanoparticle network when the wall-to-wall

distance between fillers was small than the bridging segment. For the nanocomposites with

well dispersed non-agglomerated nanoparticles, the bridging segment is related to the radius

of gyration 𝑅𝑔 of polymer chains.


In order to study the formation of the silica network, a comparison between the mean particle

distance 𝐷 and the radius of gyration 𝑅𝑔 is carried out for PLA/silica composites with

different particle sizes and particle concentrations.

The inter-particle distance in case of an ideal distribution of spherical primary particles with

different diameters 𝑑 and filler concentrations can be calculated from the Equation (5.2),

according to Refs. [Münstedt et al. (2010), Xu et al. (2010)]. The results were showed in

Figure 5.16.

𝐷 = (√4π

3

3− 2) ∗ 𝑑 (5.2)

The radius of gyration 𝑅𝑔 of PLA molecules can be calculated by the method given by Flory

[Flory and Volkenstein (1969)]:

𝑅𝑔2 =< 𝑠2 >=

1

6< 𝑟2 > (5.3)

< 𝑟2 >= 𝑏02 × 𝑧 × 𝐶 × 𝑃 (5.4)

𝑟 is the chains’ end-to-end distance. Here z is the number of bonds of a monomer unit in the

main chain being 3 for PLA. 𝑏0 is the distance between neighboring atoms per repeat unit in

the main chain, which is made up by C-O and C-C bonds. So the average length of the

skeletal bond 𝑏0 = 2.9 Å. 𝑃 is the degree of polymerization of PLA, which can be calculated

from 𝑀𝑛/𝑀𝑔 . The characteristic ratio 𝐶 is ca. 6.7 for PLA. Consequently, for the PLA studied

𝑅𝑔 =< 𝑠2 >0.5≈ 21 𝑛 𝑚 (5.5)

As shown in Figure 5.16, the inter-particle distance D (ideal dispersion condition) is

calculated and plotted as function of particle fraction. In case of a volume concentration of 2.8

vol. %, particles of 7 nm in diameter would be 23 nm apart from each other, for 40 nm this


quantity is 132 nm, and for 9 m microsilica is ca. 29.7 m. A comparison between 2𝑅𝑔 and

the inter-particle distance is often used to determine the existence of particle-particle

interactions via attached polymer molecules [Sarvestani and Picu (2004), Münstedt et al.

(2010)]. However, for PLA/silica nanocomposites, the nanosilica agglomerates are hard to

break during melt compounding. Although there are some local particle-particle interactions

in the nanocomposites due to the formation of silica aggregates, a continuous silica network

structure has not formed even the inter-particle distance is smaller than 2𝑅𝑔. According to the

rheological experiments, this concentration (2.8 vol. %) is below the rheological percolation

threshold of these three PLA/silica composite systems, i.e., there is no continuous silica

network structure formed. In comparison with particle-PLA interactions, the particle-particle

interactions under this concentration can be neglected.

Figure 5.16 The modified relationship to determine the rheological percolation threshold φ𝑐.

When the volume concentration increases up to 5.8 vol. %, the ideal inter-particle distance for

silica 300 is ca. 14 nm, which is much less than 2𝑅𝑔 of PLA molecules. As discussed above,

PLA/5.8 vol. % silica 300 nanocomposite exhibits a solid-like behavior at low frequencies,

indicating the formation of a continuous silica network, and the rheological properties are

mainly determined by particle-particle interactions and particle-PLA molecule interactions.


For PLA/silica OX50 system, although the nanoscale particles dispersed well in the matrix,

the inter-particles distance is larger than 2𝑅𝑔 of PLA molecules even at the highest filler

concentration (9 vol.%) in this work. Therefore, it is unlikely to form a continuous silica

network in this composite. That is to say, the interactions between particles via attached

molecules are impossible, and the rheological properties are related to particles-polymer

molecule interactions, only. In addition, for PLA/microsilica system, the particle-particle

interaction is negligible because of the extremely large particle size. Therefore, just silica

particle-PLA molecules interactions are responsible for the rheological behavior of

PLA/microsilica composites.

Figure 5.17 Schematic representation of the interactions between nanoparticles under ideal

and real distribution.

As shown in Figure 5.17, the bridging segment is around 2𝑅𝑔 for the nanocomposites with

well dispersed non-agglomerated nanoparticles [Sarvestani and Picu (2004)]. However, for

PLA/silica nanocomposites, the nanosilica agglomerates are hard to break during

compounding. Considering the impact of nanosilica agglomerates on the real distribution of

silica nanoparticles, using the comparison between 2𝑅𝑔 and 𝐷 to determine the formation of

continuous silica network is inaccurate. According to the rheological percolation threshold of

PLA/silica300 nanocomposite system (between 2.8 vol. % and 5.8 vol. %.), a modified


relationship between 𝑅𝑔 and 𝐷 was concluded as shown in Figure 5.16. When inter-particle

distance is larger than 2𝑅𝑔, the interaction between the particles via attached molecules is

insignificant. Therefore, the rheological behavior is merely related to particle-polymer

interactions. In case of the inter-particle distance being smaller than 𝑅𝑔 of PLA molecules, a

continuous silica network will be formed. The interactions between particles are so strong that

the composites act as solid-like rheological behavior at low frequency. The particle-particle

interactions dominate the rheological properties.

A critical situation is that 𝐷 locating between 𝑅𝑔 and 2𝑅𝑔, the interactions between particles

and the rheological properties of nanocomposites are mainly determined by the dispersion of

fillers [Damm et al. (2008), Triebel et al. (2010)]. This model additionally confirms that the

particle size has a significant effect on the rheological properties of PLA/silica composites.

What calls for special attention is the limitation of this model for polymer filled by

microparticles. When the volume of microparticle is dominant in the composites, although

there is no silica network structure formed in this case, a solid-like flow behavior will occur

because of the replacement of flexible polymer chains by rigid particles.

5.5 Conclusions

The thermo-mechanical and rheological properties of PLA/silica composites with various

particle sizes and concentrations were investigated. It was found that silica particles worked

as nucleating agents in the composites and significantly improved the crystallinity of PLA.

The nanosilica shows stronger impact on crystallization compared with microsilica. In

addition, the influence of silica particle size and concentration on the rheological properties of

PLA/silica composites were investigated by dynamical mechanical and creep-recovery

experiments. The results demonstrate that the thermal stability of PLA is improved by the

addition of silica, especially for the silica particles with smaller size. In addition, the


rheological properties of PLA/silica composites show a strong dependence on the particle size

and concentration. The presence of nanosilica can significantly enhance the moduli and

viscosity of the composites, which is almost not influenced by the microsilica. When the filler

concentration is below the rheological percolation threshold φ𝑐, a linear relationship between

𝑙𝑜𝑔𝜂0 and filler concentration is found. Creep-recovery experiments reveal that the melt

elasticity of the composite is very sensitive to the addition of particles. Even for

PLA/microsilica system, the steady-state compliance 𝐽𝑒0 could be increased dramatically upon

the addition of silica. An enhancement of 𝐽𝑒0 by a factor 10 for PLA reinforced by microsilica

at a filler fraction of 2.8 vol. % is observed. Under the same silica concentration, the increase

factors for PLA/nanosilica OX50 (d=40 nm) and PLA/nanosilica 300 (d=7 nm)

nanocomposites are ca. 60 and 200, respectively. The particles with smaller size could induce

a greater enhancement on the melt elasticity. A model describing the interactions in

PLA/silica system was proposed on the basis of correlation between the radius of gyration of

polymer matrix 𝑅𝑔 and the mean distance between particles 𝐷. The model suggests that when

the mean distance between particles exceeds 2𝑅𝑔of polymer matrix, the rheological properties

are mainly determined by the particles-polymer interactions. Whereas the particle-particle and

particle-polymer interactions are responsible for the rheological properties as the mean inter-

particle distance is below the radius of gyration of polymer matrix.

6. PLA/PMMA blends

Blending polymers is a convenient way to develop polymeric materials with desirable

properties. Suitable blend partners could not only improve the physical properties, but also

create some novel features that are not available in the pure components. As is well known,

PMMA is one of the few polymers that are compatible with PLA. The blends show better

transparency, better mechanical behavior and processability in comparison with neat PLA.

Furthermore, PLA/PMMA blends have a potential to be used in biomedical application or

solar concentrators. Hence, it is of great significance to study the thermo-mechanical and

rheological properties of PLA/PMMA blends.

Accordingly, in this chapter, PLA/PMMA blends with various compositions and molar mass

of PMMA were prepared by melt mixing. The effects of the crystallites and chains

entanglement on the shape memory performances were investigated via thermo-mechanical

and rheological measurements. In addition, the influences of stretch parameters on the shape

properties of PLA/PMMA blends were fully studied.

6.1 PLA/PMMA 7N blends with different compositions

In this section, PMMA 7N is chosen to be blended with PLA with various compositions

(100/0, 90/10, 70/30, 50/50, 30/70, 10/90, 0/100 by weight) by melt mixing. The impact of

PMMA content on the thermo-mechanical and rheological properties of PLA/PMMA blends

will be investigated.

6.1 PLA/PMMA 7N blends with different compositions 65

6.1.1 Thermo-mechanical properties of PLA/PMMA blends

6.1.1.1 Differential scanning calorimetry (DSC)

The miscibility of PLA/PMMA blends in the solid state and the crystallization properties were

firstly investigated by DSC measurements. As shown in Figure 6.1, the neat PLA film

displays a glass transition temperature around 60 °C, followed by a cold crystallization peak

at ca. 112 °C. The neat PMMA film is completely amorphous and its glass transition

temperature is determined as 110 °C. The PLA/PMMA blends show a quite broad transition

characterized by only one single 𝑇𝑔 which locates between 𝑇𝑔 of the individual components

and increases with increased PMMA content (as shown in Table 6.1). It is worth noting that

the temperature span Δ𝑇𝑔 of the glass transition of the blends is much broader than that of the

neat components, which is generally acknowledged as a result of local heterogeneity and

concentration fluctuation in the segmental length scale [Wetton et al. (1978), Roland and Ngai

(1993), Shi et al. (2013)].

Figure 6.1 DSC thermograms in the second heating scans of PLA/PMMA blends.

66 6 PLA/PMMA blends

Comparison to the Predictions of the Lodge−McLeish Model

Figure 6.2 Variation of 𝑇𝑔 with blend composition for PLA/PMMA blends. The red and black

lines represent the fit to Equation (6.3) for PLA and PMMA, respectively. The pink line is 𝑇𝑔

calculated by the Fox’s equation. The solid dots (●) represent 𝑇𝑔 of PLA/PMMA blends

determined by DSC.

In a miscible polymer blend system, the glass transition temperatures of the blends can be

theoretically calculated by the Fox’s equation. As shown in Figure 6.2, 𝑇𝑔 determined by DSC

(blue dots) are different with that calculated by the Fox’s equation (pink dotted line). This

difference is attributed to the dynamic heterogeneity in the molecular length.

In PLA/PMMA blends, the local dynamics of the components’ chains may exhibit different

dependences on temperature and overall composition. In order to take into account the

dynamic heterogeneities in this miscible blend system, a concept of “self-concentration”

which is caused by the intermolecular connectivity is introduced by Lodge and McLeish

[Lodge and McLeish (2000)]. According to the Lodge-McLeish (LML) model, the effective

local concentration 𝑒𝑓𝑓

is given by


𝑒𝑓𝑓

= 𝑠

+ (1 − 𝑠) (6.1)

where 𝑠 is the “self-concentration” of monomers, and is the average bulk composition. The

determination of 𝑠 is based on the volume actually occupied by a Kuhn length’s worth of

monomers, divided by 𝑉 = 𝑙𝑘3

𝑠

=𝐶𝑀0

𝑛𝑏𝑁𝑎𝑉𝑉 (6.2)

where 𝐶 is a polymer’s specific constant the characteristic ratio, 𝑀0 is the repeating unit

molar mass, 𝑛𝑏 is the number of backbone bonds per repeat unit, is the density, 𝑁𝑎𝑉 is the

Avogadro constant, and volume 𝑉 is assumed to be the volume occupied by the Kuhn length

(𝑙𝑘)’s worth of monomers, expressed by 𝑉 = 𝑙𝑘3.

In a binary polymer blend, a consequence of “self-concentration” is that, A monomers

experience local environments that tend to a rich in A, and the same status for B monomers.

The self-concentrations of components A (PLA) and B (PMMA) are taken as 0.37 and 0.25,

according to the calculation based on Equation (6.2), respectively. In a miscible blend, the

component with higher 𝑇𝑔 exhibits a lower 𝑠 and vice versa. The dynamics of the average

blend composition can be better represented by the dynamics of component with high 𝑇𝑔, as

proposed in a previous study [Lodge and McLeish (2000)].

The effective glass transition temperature 𝑇𝑔,𝑒𝑓𝑓 for each component can be calculated by the

modified Fox’s equation,

1

𝑇𝑔,𝑒𝑓𝑓,𝐴=

𝑒𝑓𝑓,𝐴

𝑇𝑔,𝐴+

1−𝑒𝑓𝑓,𝐴

𝑇𝑔,𝐵 (6.3)

The effective glass transition temperature for the components can be calculated and compared

with the calorimetric 𝑇𝑔 of the blends in Figure 6.2. According the concept proposed by


Lodge and McLeish [Lodge and McLeish (2000)], the prediction of the LML model should

meet the physics that the lower 𝑇𝑔 component (PLA) tend to have segmental dynamic in the

blends closer to its own bulk, weakly dependent on concentration. On the other hand, the

dynamics of the higher 𝑇𝑔 component (PMMA) would be more representative of the average

blend composition [Lodge and McLeish (2000)]. This effect could be demonstrated at high

PMMA content region (>50%). However, when PMMA content is below 50%, the

calorimetric 𝑇𝑔 of the blends are more close to 𝑇𝑔,𝑒𝑓𝑓 of PLA. The plausible reason for this

phenomenon may be due to the restriction of chain mobility in the vicinity of the crystallites

[Ngai and Roland (1993)].

Crystallization of PLA/PMMA blends.

From the DSC results, the two melting peaks of the neat PLA corresponding to α crystal and α’

crystal could be clearly observed at 163 °C and 169 °C, respectively [Pan et al. (2007)].

However, the tendency of PLA to crystallize is obviously suppressed by the incorporation of

PMMA. The crystallinity 𝑋𝑐 of the blend is listed in Table 6.1. It is worth noting that, if the

PMMA content is below 50%, a weak melting peak can be found at 165 °C in the blends.

Consequently, the degree of crystallinity 𝑋𝑐 decreased with the increasing PMMA content.

For PMMA content above 50%, no melting peak was found. Hence, the PLA in these blends

is completely amorphous. As the blends have shown to be miscible, the various polymer

chains (PLA and PMMA) in the amorphous phase are randomly distributed and interact with

each other [Graessley (1965)]. The segmental mobility of PLA chains in the amorphous may

be significantly affected by the interactions between PMMA and vice versa. The interactions

between PMMA and PLA will be discussed in more detail later in this section.

A single 𝑇𝑔 is obtained for all the PLA/PMMA blends, indicating the intimate mixing between

PLA and PMMA chains. There are two elements can explain the suppression of PLA


crystallinity with the addition of PMMA: i) the incorporation of PMMA into PLA matrix

dilutes the PLA chains in the blends, ii) the molecular entanglements between PLA and

PMMA chains reduced the mobility of PLA chains in the matrix, which can prevent the

alignment of PLA chains. Moreover, the work of Samuel [Samuel et al. (2013)] demonstrated

the absence of any other reactions between PMMA and PLA phase. Therefore, the crystalline

phase of PLA was suppressed when PMMA was introduced.

Table 6.1 Glass transition temperature 𝑇𝑔 , associated broadness Δ 𝑇g and crystallinity 𝑋𝑐 of

PLA/PMMA cast films.

DSC DMTA

PLA/PMMA 𝑻𝒈a

(°C) Δ𝑻𝐠b

(°C) 𝑿𝒄c (%) 𝑻𝐠

d (°C) Δ𝑻𝐠

e (°C)

100/0 60 14 10.8 59 19

90/10 62 17 6.3 61 26

70/30 67 28 3.4 65 36

50/50 75 32 0.1 73 45

30/70 85 36 0 82 50

10/90 100 29 0 98 36

0/100 110 18 0 109 30 a

Evaluated by DSC at the inflection point (second heating scan). b

Evaluated by DSC as 𝑇𝑔−𝑒𝑛𝑑 – 𝑇𝑔−𝑜𝑛𝑠𝑒𝑡 . c

Evaluated by DSC (first heating scan). d

Evaluated by DMTA. e

Evaluated by DMTA as half bandwidth of the 𝑇g peak.

6.1.1.2 Dynamic mechanical analysis (DMTA)

Beside DSC, DMTA is another common method to characterize the glass transition. As

shown in Figure 6.3, a single -relaxation corresponding to the glass-rubber transition of

polymers was observed. It is evident that the -relaxations shifts to higher temperature with

increasing PMMA content, and the broadness of glass transition region of the blends is also

enhanced compared to the neat components. For neat PLA, the -relaxation temperature

determined by DMTA is about 2 °C smaller than its glass transition temperature evaluated by

DSC, but the broadness of -relaxation process is much larger than that measured by DSC.


As listed in Table 6.1, the broadness of glass transition determined by DSC and DMTA

methods exhibit similar tendencies with the variation of PMMA content. These differences

between the values of 𝑇g and Δ𝑇g are induced by the different measuring principles of DSC

and DMTA [Rahman et al. (2007)].

Figure 6.3 The dynamic loss moduli 𝐸′′ as a function of temperature determined at a

frequency of 1 Hz and a heating rate of 2 °C/min.

According to Jordan et al. [Jordan et al. (2014)], two transition regimes can be identified in

the loss modulus curves of neat PMMA. The low temperature process (only partially revealed

in the temperature regime measured) is associated with the β-relaxation, while the one at

higher temperature is associated with the glass transition (-relaxation). As illustrated in

Figure 6.3, the high temperature flank of the β-relaxation at low temperature increases

gradually with PMMA addition. Especially for the blends with PMMA contents above 50%,

the high temperature shoulder of the β-relaxation peak at low temperature range is quite

obvious.


6.1.2 Melt rheology of PLA/PMMA blends

6.1.2.1 Linear rheological region

In order to determine the linear viscoelastic limits of PLA/PMMA blends, the dynamic strain

sweep measurements were carried out at 200°C and an angular frequency of 6.28 rad/s. As

shown in Figure 6.4, the storage moduli 𝐺′ of various blends increase obviously with the

presence of PMMA due to the enhanced rheological behavior. The linear viscoelastic limits of

neat PLA is around the strain of 50%, and the incorporation of PMMA into PLA matrix

reduced the linear viscoelastic region. Interestingly, the linear regions of PLA/PMMA blends

are smaller than that of the neat components, and PLA/PMMA 50/50 blend shows the

smallest linear limit of 4%. This effect may be related to the self-concentration in miscible

PLA/PMMA blends.

Therefore, the linear viscoelastic properties of PLA/PMMA blends were determined at a

strain of 1% in this work.

Figure 6.4 The storage modulus 𝐺′ of various PLA/PMMA blends as a function of strain

amplitude at 200°C.


6.1.2.2 Thermal stability

Dynamic time sweeps were performed to measure the thermal stability of PLA/PMMA blends

in the linear range of deformation. The degradation of PLA and PMMA during the rheological

measurements should be considered because polymers are quite unstable in the molten state.

Dynamic time sweeps were performed to measure the thermal stability of PLA/PMMA blends

in the linear range of deformation. The thermal stability is evaluated using the storage

modulus 𝐺′ as a function of time in the terminal region (0.05 rad/s) at 200 °C. Samples are

regarded to be stable as long as 𝐺′ doesn’t diverge from the original 𝐺′ by more than 5%. As

shown in Figure 6.5, the time of thermal stability for neat PLA at 200 °C is around 1000 s. At

the same temperature, the addition of PMMA distinctly increases the stabling time of the

blends. For PLA/PMMA 50/50 blend sample, no change of 𝐺′within the stability limit even

after 8000 s is observed.

Figure 6.5 The storage modulus 𝐺′ of PLA/PMMA blends obtained in time sweep at 200 °C.

6.1.2.3 Dynamic mechanical experiments

As shown in Figure 6.6a, the complex viscosities |𝜂| at low frequencies increase with the

addition of PMMA, and a plateau of |𝜂| which is equal to zero shear viscosity 𝜂0 could be

reached in the low frequency range for all the blends. PMMA shows larger viscosity


compared with PLA at the same temperature, and the viscosities of PLA/PMMA blends are

located between the neat components.

A Cole-Cole curve is useful to obtain some viscoelastic properties of polymers, removing the

effect of frequency. Figure 6.6b presents the 𝜂′′ as a function of 𝜂′ for neat components and

the blends. The characteristic relaxation time 0 can be determined at angular frequency

corresponding to the maximum 𝜂′′ [Dealy and Larson (2006)]. The Cole-Cole plot of each

PLA/PMMA blend displays a smooth and single semicircle like the neat components,

indicating the excellent miscibility of the PLA/PMMA blend melts.

Figure 6.6 (a) The complex viscosity |𝜂| of PLA/PMMA blends as a function of angular

frequency and (b) Cole-Cole plots for PLA/PMMA blends obtained by oscillatory frequency

sweep at 200 °C.

It is worth mentioning the viscosities of the PLA/PMMA blends increase with the addition of

PMMA. According to Haley et al. [Haley and Lodge (2004)], if |𝜂| of the blend can be

described by,

𝜂𝑏𝑙𝑒𝑛𝑑 = 𝑤1|𝜂1

| + 𝑤2|𝜂2| (6.4)

where 𝑤 is the weight fraction of the component, the blend will be considered to be

unentangled (i.e. Rouse like). However, as shown in Figure 6.7, the correlation between the


complex viscosity and PMMA content is not well described by the linear model of Equation

6.4, but rather represented by the exponential form of the complex viscosity. This result

suggests the existence of an entanglement network in the PLA/PMMA blends [Liu et al.

(2002)]. Therefore, the additivity of 𝑙𝑜𝑔𝜂0 not only demonstrates the intimate mixing between

PLA and PMMA chains, but also indicates the existence of molecular entanglement in

PLA/PMMA blends.

Figure 6.7 (a) zero shear viscosity 𝜂0 at 200 °C versus blend composition (b) 𝑙𝑜𝑔𝜂0 at 200 °C

versus blend composition.

In Figure 6.8, the plot of the phase angle as a function of the absolute value of the complex

modulus |𝐺∗| (van Gurp-Palmen (vGP) plot [Van Gurp and Palmen (1998)], is used

additionally to evaluate the miscibility of PLA/PMMA blends. For neat PLA, the values

increased with the reduction of |𝐺∗| towards 90°. For PLA/PMMA blends, the curves of the

blends lay between the curves of the neat components, a slight deviation from the curves of

neat PLA was observed with the increased PMMA content.


Figure 6.8 (a) Van Gurp-Palmen plots of phase angle versus complex modulus |𝐺∗| of

various PLA/PMMA blends at 200 °C, and (b) Van Gurp-Palmen plots of the PLA/PMMA

50/50 blend at various temperatures between 180 °C and 210 °C.

The influence of temperature on the Van Gurp-Palmen plots of PLA/PMMA 50/50 blend as

an example is shown in Figure 6.8b. The curves of different temperatures perfectly

superimpose, indicating that the blend, as well as all other blends investigated, is thermo-

rheologically simple. This fact verifies the miscibility of two polymers in the molten state

[Ferry (1980)], which is based on the fact that the various relaxation times of

thermorheological simple polymers exhibit a similar temperature dependence [Van Gurp and

Palmen (1998)].

6.1.2.4 Time-temperature superposition (TTS)

Time-temperature superposition (TTS) principle is frequently used to determine the phase

separation temperature of polymer blends and estimate the miscibility of blend in molten state

[Jeon et al. (2000)]. Furthermore, the construction of master curves obtained by TTS principle

can extend the time or frequency range in rheological measurements. Figure 6.9 and Figure

6.10, respectively, show the master curves of the neat polymers and their blends at a reference


temperature 𝑇𝑟𝑒𝑓 =200 °C obtained by horizontal shifting along the angular frequency axis

using the shift factor 𝑎𝑇.

Figure 6.9 Master curves of 𝐺′ , 𝐺′′ , |𝜂∗| and 𝑡𝑎𝑛𝛿 for neat PLA and neat PMMA at a

reference temperature of 200 °C. The rheological data were measured at various temperatures

between 180 and 210°C (□■180 °C, △▲190 °C, ○●200 °C, ▽▼210 °C). 𝛼𝑇 is the shift

factor for constructing the master curves.

It is evident that all master curves follow the TTS principle well in the whole frequency range,

indicating the miscibility of PLA/PMMA blends at the experimental temperature range.


Figure 6.10 Master curves of 𝐺′, 𝐺′′, |𝜂∗| and 𝑡𝑎𝑛𝛿 for PLA/PMMA blends (70/30, 50/50,

30/70, 10/90) at a reference temperature of 200 °C. The rheological data were measured at

various temperatures between 180 and 210°C (□■180 °C, △▲190 °C, ○●200 °C, ▽

▼210 °C). 𝛼𝑇 is the shift factor for constructing the master curves.

To quantify the temperature dependence of the viscoelastic properties for all blends, the

values of 𝑎𝑇 are presented in an Arrhenius plot in Figure 6.11. All the curves can be

described by the Arrhenius equation as follows [Fesko and Tschoegl (1971)],

𝑙𝑜𝑔𝑎𝑇 (𝑇) =𝐸𝑎

2.303𝑅(

1

𝑇−

1

𝑇𝑟𝑒𝑓) (6.5)

where 𝑅 is the universal gas constant, and 𝐸𝑎 is the activation energy of flow. The 𝐸𝑎 values

for neat PLA is 80 kJ/mol and for neat PMMA is 182 kJ/mol, which are consistent with the

reported values in the literature [Agrawal et al. (1997), Holland and Hay (2002)]. Moreover,

the 𝐸𝑎 values of PLA/PMMA blends linearly depend on the composition as expected for a

miscible system.


Figure 6.11 (a) Arrhenius plot of time-temperature superposition shift factor 𝛼𝑇 for various

PLA/PMMA blends, and (b) Activation energy 𝐸𝛼 versus PMMA content.

6.1.2.6 Creep-recovery experiments

Figure 6.12 The creep compliance and recoverable compliance of various PLA/PMMA

blends at 200 °C.

The creep and recoverable compliance of PLA/PMMA blends with different compositions are

plotted in Figure 6.12. The creep compliance is decreasing with increased PMMA content,

corresponding to the increased viscosity of the blends. All the experiments were performed in

the linear range of deformation, and a linear steady-state recoverable compliance 𝐽𝑒𝑜 is reached

within the chosen recovery time 4000 s. 𝐽𝑒𝑜 for neat PLA is ca. 1.7×10

-5 Pa

-1, and 𝐽𝑒

𝑜 for neat


PMMA is around 2.9 ×10-5

Pa-1

. The 𝐽𝑒𝑜 values of the blends are located between the neat

components. The differences between these 𝐽𝑒𝑜 values are extremely small, indicating the

intimate mixing between PLA and PMMA chains. The melt elasticity of miscible blend is not

influenced by the composition.

Figure 6.13 Complex viscosity |𝜂∗| as a function of ω in comparison with 𝑡/𝐽(𝑡𝑐𝑟) in

dependence on creep time 𝑡 at 200 °C.

In Figure 6.13, the complex viscosity |𝜂∗| as a function of ω is compared with 𝑡/𝐽(𝑡𝑐𝑟) in

dependence on creep time 𝑡 for PLA/PMMA blends. The zero shear viscosity obtained by

oscillatory shear experiments is equal to that determined by creep compliance. A steady-state

is reached for all the blends, and the creep time 𝑡 to reach this steady state is increasing with

the addition of PMMA.

6.1.3 Interactions of PLA and PMMA via molecular entanglements.

Entanglements between polymer molecules are essential in understanding mechanical [Wu

(1982), Kausch (1987)] and rheological [Ferry (1980)] properties of polymers. The average

molar mass between adjacent temporary entanglement points, 𝑀𝑒 , is one of the most

fundamental material parameters to investigate the structure of molten polymers [Ferry


(1980)]. According to Graessley and Fetters [Graessley (1980), Fetters et al. (1994)], the

entanglement molar mass 𝑀𝑒 can be deduced from the plateau modulus 𝐺𝑁0 ,

𝑀𝑒 = 4𝜌𝑅𝑇/5𝐺𝑁0 (6.6)

where 𝜌 denotes the density, 𝑅 the gas constant and 𝑇 the absolute temperature.

For a miscible binary blend, the subscripts 1 and 2 are used to describe the components PLA

and PMMA, respectively. There are three types of possible entanglements: 1-1, 2-2 and 1-2

(assumed to be equal to 2-1). Herein, 𝑀𝑒1 and 𝑀𝑒2 are defined as the average entanglement

molar mass of the neat components (similar chains), 𝑀𝑒12 is the average entanglement molar

mass of a hypothetical pure component formed by PMMA chains entangled with PLA

molecules (dissimilar chains). Hence, we can deduce the entanglement state in similar and

dissimilar chain by comparing the value of 𝑀𝑒1, 𝑀𝑒2 and 𝑀𝑒12.

Wu [Wu (1987)] showed that the density of contacts between two similar chains is

proportional to the square of volume fraction 𝜙12 or 𝜙2

2 while that between two dissimilar

chains has shown to be proportional to 2𝜙1𝜙2.The total average entanglement density can be

defined as [Wu (1987)]

𝜌

𝑀𝑒=

𝜙12𝜌1

𝑀𝑒1+

𝜙22𝜌2

𝑀𝑒2+

2(𝜙1𝜙2)(𝜌1𝜌2)

𝑀𝑒12 (6.7)

By substituting Equation (6.6) into Equation (6.7), 𝑀𝑒12 is obtained by

𝑀𝑒12 = 2𝜙1𝜙2𝑅𝑇(𝜌1𝜌2)1

2/(𝐺𝑁0 − 𝜙1

2𝐺𝑁10 − 𝜙2

2𝐺𝑁20 ) (6.8)


Figure 6.14 Frequency sweep of PLA/PMMA 50/50 and PLA/70%PMMA blends at 140 °C.

As shown in Figure 6.9 and 6.10, 𝐺𝑁0 for neat PMMA and PLA/90%PMMA can be

determined as 𝐺′ at the frequency where 𝑡𝑎𝑛𝛿 reaches a minimum (MIN method) [Liu et al.

(2006)]. As shown in Figure 6.14, the minimum 𝑡𝑎𝑛𝛿 for PLA/PMMA 50/50 and

PLA/70%PMMA blends can be obtained at 140 °C, and the corresponding 𝐺𝑁0 is determined

on the basis of Equation (2.19). However, for neat PLA and PLA/PMMA blends (PMMA

content<50%), the MIN method is not viable to determine 𝐺𝑁0 as the low experimental

temperature will result in the crystallization of PLA. So this method cannot be used to

determine 𝐺𝑁0 for all the samples. As alternative, Wu [Wu (1989)] and Nobile-Cocchini

[Nobile and Cocchini (2001)] proposed a semi-quantitative method based on the crossover

modulus 𝐺𝑋 ( 𝐺𝑋 = 𝐺′ = 𝐺′′ ). Wu [Wu (1989)] found the relationship between 𝐺𝑁0 and

crossover modulus 𝐺𝑋 if 𝑀𝑤/𝑀𝑛 < 3 by the following equation,

log (𝐺𝑁

0

𝐺𝑋) = 0.38 +

2.63 log (𝑀𝑤/𝑀𝑛)

1+2.45 log (𝑀𝑤/𝑀𝑛) (6.9)

For miscible blends, 𝑀𝑤 and 𝑀𝑛 are averaged values and can be calculated by the following

expression [Struglinski and Graessley (1985)]

𝑀𝑤 = 𝑤1𝑀𝑤1 + 𝑤2𝑀𝑤2 (6.10)


1/𝑀𝑛 = 𝑤1/𝑀𝑛1 + 𝑤2/𝑀𝑛2 (6.11)

where 𝑤1 and 𝑤2 are the weight fractions of PLA and PMMA, respectively.

The entanglement molar mass 𝑀𝑒 and 𝑀𝑒12 of the various PLA/PMMA blends determined by

the “crossover modulus” and “MIN” methods are listed in Table 6.2.

Table 6.2 Average entanglement molar mass 𝑀𝑒, 𝑀𝑒12 and average entanglement density 𝑒

of PLA/PMMA blends.

PLA/PMMA

blend

𝑴𝒆 a (kg/mol)

𝑴𝒆 b

(kg/mol)

𝒆 a

(×10-4

mol/cm3)

𝑴𝒆𝟏𝟐 a (kg/mol)

100/0 3.8 ± 0.1 ---- 2.9 ± 0.1 ----

90/10 3.4 ± 0.1 ---- 3.3 ± 0.1 2.8± 0.1

70/30 3.1 ± 0.2 ---- 3.6 ± 0.2 2.9 ± 0.2

50/50 3.2 ± 0.1 3.5 ± 0.1 3.5 ± 0.1 3.0 ± 0.1

30/70 3.7 ± 0.2 4.7 ± 0.2 3.0 ± 0.2 3.1 ± 0.2

10/90 4.3 ± 0.1 6.2 ± 0.1 2.6 ± 0.1 2.1 ± 0.1

0/100 6.0 ± 0.1 7.1 ± 0.1 1.9 ± 0.1 ---- a

Estimated by using “crossover modulus-based method”. b

Estimated by using “MIN method”.

The 𝑀𝑒 value of pure PMMA obtained from “MIN method” agrees well with that reported in

literature [Wu (1987), Zhang et al. (2015)]. However, there is no available 𝑀𝑒 for pure PLA

that can be determined by “MIN method” even if the experimental temperature is decreased to

its crystallization temperature range. The 𝑀𝑒 values of neat PMMA and the PLA/PMMA

blends (PMMA content ≥50%) obtained from the “MIN method” is somewhat higher than

those determined by “crossover modulus-based method”, and this variation should be ascribed

to the semi-quantitative nature of the latter method. It is worth noting that the 𝑀𝑒 values

determined by both methods exhibit the same trend versus PMMA content.


Figure 6.15 Average entanglement molar mass 𝑀𝑒 , 𝑀𝑒12 and entanglement density 𝑒

PLA/PMMA blends as a function of blend composition.

As shown in Figure 6.15, it can be observed that the values of 𝑀𝑒12 are in general smaller

than 𝑀𝑒 of neat components and the blends, indicating that the dissimilar chains are more

likely to entangle with each other than similar ones in the PLA/PMMA blends [Wu (1987)].

This result can partially explain the larger entanglement density for the blends compared to

the neat components. When PMMA content is below 50%, the increase of 𝑀𝑒12 with the

addition PMMA demonstrates the strong tendency of PLA chains to self-association rather

than inter-association with PMMA chains [Es‐Haghi et al. (2007)], corresponding to the self-

concentration model in miscible blends. The 𝑒 values of the blends are increasing with

PMMA content up to 50% and then decreasing with PMMA content.

The results about the degree of entanglement can be used to explain why PLA/PMMA blends

have improved shape memory properties compared to the neat components. Whereafter, shape

memory measurements will be carried out to confirm the impact of molecular entanglement

on the shape memory performance in the section 6.3.

6.2 PLA/PMMA 50/50 blends with different molecular structures

In this section, PMMA (PMMA 6N, PMMA 7N, PMMA 8N) with different molar masses are

used to blend with PLA. The effect of PMMA’s molecular structure on the thermo-

mechanical and rheological properties of PLA/PMMA 50/50 blends will be investigated. This

study is relevant in understanding the effects of molecular structure and specific inter-chain

interaction on molecular entanglement.

6.2.1 Molecular Characterization of PMMA 6N, 7N and 8N

The molar mass distributions of the PMMA 6N, 7N and 8N samples are plotted in Figure 6.16.

Obviously, the average molar mass 𝑀𝑤 of PMMA is increasing from 6N to 8N, and these

PMMA samples have similar and broad molar mass distribution in terms of the degree of

dispersion, 𝑀𝑤/𝑀𝑛. The 𝑀𝑤 of these PMMA are all above the critical molar mass 𝑀𝑐 (ca.

3104 g/mol) for entanglement coupling [Tadano et al. (2014)]. Therefore, the zero-shear

viscosity 𝜂0 of PMMA should scale in the following manner with the molar mass 𝑀𝑤,

𝜂0 = 𝐾𝑀𝑤3.4 (6.12)

In general, this relationship holds for linear polymers except for extremely broad blends, and

it could be check by the oscillatory shear experiments.

In addition, the radius of gyration 𝑅𝑔 of the PLA and PMMA chains could be calculated based

on Equation (5.3 and 5.4). The characteristic ratio 𝐶 is ca. 8.2 for PMMA [Wool (1995)]. As

listed in Table 6.3, the radius of gyration of PLA is ca. 21.6 nm, which is much larger than

that of PMMA. The radii of PMMA are increasing from 6N to 8N.

6.2 PLA/PMMA 50/50 blends with different molecular structures 85

Figure 6.16 Molar mass distribution of the PMMA grades under investigation.

6.2.2 Thermal behavior of PMMA and PLA/PMMA 50/50 blends

The thermal behavior of PLA, PMMA and the various PLA/PMMA 50/50 blends were

measured by DSC, as shown in Figure 6.17. The glass transition temperature 𝑇𝑔 of neat PLA

is around 60 °C, and 𝑇𝑔 for neat PMMA 6N, 7N and 8N are ca. 96 °C, 110 °C and 117 °C,

respectively. The differences in PMMA’s 𝑇𝑔 are related to the tacticity and molar mass of

PMMA. This effect will be discussed later in detail.

Figure 6.17 DSC thermograms in the second heating scan for (a) neat PLA and PMMA, (b)

PLA/PMMA 50/50 blends.


A single broad 𝑇𝑔 for PLA/PMMA 50/50 blends were observed, confirming the miscibility of

the blends. 𝑇𝑔 for PLA/PMMA 50/50 blends are 72 °C, 75 °C and 77 °C, corresponding to

PMMA 6N, 7N, 8N, respectively. Furthermore, the broadness of 𝑇𝑔 of the PLA/PMMA 50/50

blends are increasing from PMMA 6N to 8N. According to the literature [Wetton et al. (1978),

Roland and Ngai (1993)], the broadening of 𝑇𝑔 is a result of concentration fluctuation and

local heterogeneity in the blend system.

In addition, it is worth mentioning that these three PLA/PMMA 50/50 blends are almost

amorphous, and no obvious melting peak could be observed in the DSC heating curves.

6.2.3 Rheological properties of neat PMMA

The zero shear viscosity 𝜂0 of PMMA could be determined by oscillatory shear experiments

and then plotted as a function of molar mass 𝑀𝑤, as shown in Figure 6.18a. A well-known

power law dependence with an exponent for the PMMA products of 3.62 is observed for the

correlation between 𝜂0 and 𝑀𝑤. Figure 6.18b presents 𝜂′′ as a function of 𝜂′ for neat PMMA.

The characteristic relaxation time 0 can be determined at angular frequency corresponding to

the maximum 𝜂′′ [Dealy and Larson (2006)], as listed in Table 6.3.

Figure 6.18 (a) Zero shear viscosity at 180 °C as a function of molar mass and (b) Cole-Cole

plots determined at 180 °C for PMMA 6N, PMMA 7N and PMMA 8N.


The master curves of neat PMMA obtained by time-temperature superposition (TTS)

principle at a temperature range of 170-210 °C are shown in Figure 6.19. The temperature

dependence of the shift factors followed the Arrhenius equation (Equation (6.5)) and the

corresponding values of the activation energy 𝐸𝑎 are given in Table 6.3. It is evident that 𝐸𝑎

for neat PMMA is increasing from 6N to 8N. Furthermore, a plateau zone of 𝐺′ curves of

PMMA can be perceivable at the high frequency range. The plateau modulus 𝐺𝑁0 can be

determined at the reference temperature 180 °C based on the “MIN” method, as listed in

Table 6.3.

Figure 6.19 Master curves of 𝐺′, 𝐺′′, 𝜂∗ and 𝑡𝑎𝑛𝛿 for PMMA at a reference temperature of

180 °C. The rheological data were measured at 180-210°C. (□■170°C, ○●180°C, △▲190°C,

▽▼200°C, ◇◆210°C). 𝛼𝑇 is the shift factor for constructing the master curves.


As shown in Table 6.3, the entanglement molar mass 𝑀𝑒 of PMMA are decreasing from 6N to

8N, and the average entanglement densities of PMMA are increasing from 6N to 8N.

According to previous studies [Wu and Beckerbauer (1992), Huang et al. (2011)], the

molecular entanglement behavior of PMMA is mainly influenced by chain tacticity, and the

pure syndiotactic PMMA shows the least 𝑀𝑒 in comparison with other PMMA. In this work,

the proportions of syndiotactic sequence increase from PMMA 6N to 8N (as shown in section

3.1), corresponding to the decreased 𝑀𝑒.

Table 6.3 Characterization of the neat components.

PLA PMMA

6N 7N 8N

Glass transition temperature 𝑇𝑔

(°C)

60 96 110 117

Radius of gyration 𝑅𝑔 (nm) 21.6 4.5 5.5 6.1

Zero shear-rate viscosity at

180 °C (×104 Pas)

0.5 8.6 28.3 56.1

Relaxation time 𝜏0 at 180 °C (s) 0.006 0.2 0.7 1.6

Plateau modulus 𝐺𝑁0 at 180 °C

(×105 Pa)

7.6 3.6 5.4 5.6

Activation energy 𝐸𝑎 (kJ/mol) 80.1 165.8 182.0 189.2

Entanglement molar mass 𝑀𝑒

(kg/mol)

4.2 7.2 6.1 5.8

Average entanglement density 𝑒

(×10-4

mol/cm3)

2.9 1.6 1.9 2.0

6.2.4 Interactions of PLA and PMMA via molecular entanglements in symmetrical

PLA/PMMA blends

The molecular entanglement in miscible blends is significantly influenced by the molecular

structure of the components. As discussed above, the dissimilar chains are more likely to

entangle with each other than the similar ones in PLA/PMMA blend.

As shown in Figure 6.20, TTS works well in the temperature range from 140-200 °C for all

PLA/PMMA 50/50 blends, indicating the miscibility of the blends in the experimental


temperature range. In addition, 𝑡𝑎𝑛𝑚𝑖𝑛 is reached in the high frequency range and the

plateau modulus 𝐺𝑁0 for the blends can be obtained by “MIN” method, as listed in Table 6.4.

Figure 6.20 Master curves of 𝐺′ , 𝐺′′ , |𝜂∗| and 𝑡𝑎𝑛𝛿 for PLA/PMMA 50/50 blends at a

reference temperature of 180 °C. The rheological data were measured at various temperatures

between 140 and 200 °C (□■140 °C, △▲160 °C, ○●180 °C, ▽▼200 °C).

Table 6.4 Plateau modulus 𝐺𝑁0 (180 °C), entanglement molar mass 𝑀𝑒 and entanglement

density 𝑒 of PLA/PMMA 50/50 blends.

PLA/PMMA

50/50

𝑮𝑵𝟎

(×105 Pa

)

𝑴𝒆 (kg/mol)

𝒆

(×10-4

mol/cm3)

6N 9.0±0.2 3.7±0.2 2.9±0.2

7N 9.6±0.1 3.5±0.1 3.2±0.1

8N 9.9±0.1 3.4±0.1 3.4±0.1


As can be seen from the Table 6.4, the average entanglement molar mass 𝑀𝑒 of PLA/PMMA

50/50 blends is decreasing slightly from 6N to 8N, while the entanglement densities 𝑒 is

increasing from 6N to 8N. In general, the entanglement molar mass of polymers is mainly

determined by the molecular structures, such as chain length, molar mass, nature of chain

substituents and spatial arrangement [Chalmers and Meier (2008)].

As discussed above, PMMA 8N has the largest molar mass and chain length, and the

conformational behavior of PMMA is studied in section 6.1. PLA/PMMA 8N 50/50 has the

largest entanglement density due to the larger chain length and higher proportion of

syndiotactic sequences of PMMA 8N.

Therefore, it can be concluded that the molecular structure of the component can significantly

influence the entanglement work in the miscible blends. The polymer with larger chain length,

molar mass and higher proportion of syndiotactic sequence is much easier to entangle with

other chains, leading to a higher entanglement density.

6.3 Shape memory property of PLA/PMMA blends and the underlying

mechanism

PLA/PMMA blends are typical SMP formed by a semi-crystalline polymer and an amorphous

polymer. The shape memory properties of PLA/PMMA blend films can be quantified by

Equations (4.2 and 4.3) based on Figure 4.2. In this section, the influence of stretching

temperature, strain rate, molar mass and blend composition on the shape fixing ratio 𝑅𝑓 and

shape recovery ratio 𝑅𝑟 were systematically studied. The maximum strain of DMTA, used a

deformation of 100%, is applied to all samples.

6.3 Shape memory property of PLA/PMMA blends 91

6.3.1 Influence of stretching parameters on the shape memory properties

6.3.1.1 Stretching temperature

The glass transition temperature 𝑇𝑔 is around 60 °C for neat PLA and 75 °C for PLA/PMMA

7N 50/50 blends. In order to study the influence of stretching temperature 𝑇𝑠 on the shape

memory performance, three stretching temperatures 𝑇𝑔, 𝑇𝑔+10 °C, and 𝑇𝑔+25 °C were chosen

to draw the films at a constant strain rate of 0.02/s for 50 s. The temperature for shape

recovery measurements (𝑇𝑟) is 10 °C above the stretching temperatures. For each sample, at

least three samples are measured.

Figure 6.21 Stress-strain curves of (a) neat PLA and (b) PLA/PMMA7N 50/50 blend films

stretched at various temperatures at a strain rate of 0.02 /s.

The stress-strain curves of films based on neat PLA and PLA/PMMA 7N 50/50 blend

determined at various temperatures are shown in Figure 6.21. When the PLA films were

stretched at 𝑇𝑔 (60 °C), a linear stress-strain relationship corresponding to elastic deformation

could be observed up to about 3% deformation, where an inconspicuous yield point was

obtained. After a slight decrease of the stretching stress at the yield point, a stable stress was

reached with the increase of deformation. The constant stress portion of the curve is the

elastic-plastic region, which is induced by the orientation of the free chains in the amorphous


phase around 𝑇𝑔. In addition, no strain hardening can be observed up to the maximum strain

of 100%. Similar stress-strain curve is obtained when the PLA films are stretched at 𝑇𝑔+10 °C

(70 °C). However, the modulus and the constant stretching stress were reduced with increased

stretching temperature.

When the stretching temperature of PLA film is much higher than its 𝑇𝑔 (85 °C), the samples

react like a rubber. A highly nonlinear stress-strain response followed by a constant flow

stress could be observed. During this nonlinear stress-strain region, crystalline grains induced

by chains orientation and cold crystallization could be formed for semi-crystalline polymers

(as shown in Table 6.5). Afterwards, typical equilibrium is reached between the

recrystallization and stress relaxation induced by high temperature.

The stress-strain curves of films made of PLA/PMMA 7N 50/50 blend show s similar

response to an increase in stretching temperature. As shown in Figure 6.21b, when the sample

is stretched at 𝑇𝑔 (75 °C), a stable flow stress is reached after the yield point at about 3%

deformation. With the increase of stretching temperature, the linear stress-strain relationship

transforms into a nonlinear stress-strain response before a constant tress is arrived. The value

of the flow stress is reduced, and an obvious stress relaxation behavior can be observed when

the stretching temperature is above 100 °C.

After stretching and quenching to the room temperature, the length the sample was recorded

and then a shape recovery process was carried out in the oil bath. The shape fixing ratio 𝑅𝑓

and shape recovery ratio 𝑅𝑟 tested at different temperatures are listed in Table 6.5.

As shown in table 6.5, the shape fixing ratios 𝑅𝑓 for all samples are above 95%, and 𝑅𝑓 is

increasing with increased stretching temperature 𝑇𝑠. When 𝑇𝑠 is much higher than 𝑇𝑔, 𝑅𝑓 is

close to 100%. On the other side, the shape recovery ratio 𝑅𝑟 shows a different dependence on

increased 𝑇𝑠 . A higher 𝑇𝑠 could result in a lower 𝑅𝑟 , and the maximum value of 𝑅𝑟 is


obtained at 𝑇𝑠 = 𝑇𝑔 . Therefore, it can be concluded that the shape memory properties of

PLA/PMMA blends show obvious “temperature memory effect”, i.e., the shape fixing ratios

could be improved by increased stretching temperature, while the shape recovery ratios are

reduced by increased stretching temperature.

Table 6.5 The shape fixing ratio 𝑅𝑓 and shape recovery ratio 𝑅𝑟 of PLA and PLA/PMMA 7N

50/50 blend films stretched at various temperatures, and the crystallinity 𝑋𝑐 of cast films after

stretching.

𝑻𝒔 (°C) 𝑹𝒇 (%) 𝑹𝒓 (%) 𝑿𝒄 (%) 𝑻𝒓 (°C)

PLA

60 95.1 0.8 88.6 0.9 15.5 70

70 98.5 1.5 86.3 0.8 16.2 80

85 99.2 1.0 73.9 1.3 20.3 95

PLA/PMMA7N

50/50

75 96.2 1.3 98.9 0.7 0.2 85

85 98.8 1.6 97.5 1.4 0.5 95

100 99.3 1.1 91.8 1.2 3.8 110

6.3.1.2 Strain rate

In this section, three strain rates 0.02/s, 0.005/s, 0.002/s were chosen to investigate their

influences on the shape memory performance of films made of PLA/PMMA 7N 50/50 blend

at various stretching temperatures. The stress-strain curves obtained at various strain rates are

shown in Figure 6.22.


Figure 6.22 Stress-strain curves of films made of PLA/PMMA7N 50/50 blend stretched at (a)

75 °C and (b) 100 °C at different strain rates.

As illustrated in Figure 6.22a, a stable stress level was reached after the yield point at ca. 3%

deformation when the films were stretched at 𝑇𝑔 (75°C). The stress-strain curves obtained at

different strain rates coincide. Thus, the flow stress is not influenced by the strain rate at 𝑇𝑔.

On the other side, when the samples are stretched at higher temperatures (100 °C), the stress-

strain curves are significantly influenced by the strain rate. After a nonlinear stress-strain

response, a dynamic equilibrium state is reached for all samples. It is found that lower strain

rates leads to a lower stretching stress due to stress relaxation processes.

The shape fixing ratio 𝑅𝑓 and shape recovery ratio 𝑅𝑟 tested at various temperatures and strain

rates are calculated and listed in Table 6.6. When the samples are stretched at 𝑇𝑔, lower strain

rates result in a slightly higher shape fixing ratio, while the strain rate shows no impact on the

shape recovery ratio. On the contrary, the strain rate shows little impact on the shape recovery

ratio when the samples are stretched at higher temperatures. Smaller strain rates leads to a

significantly reduced shape recovery ratio.

Table 6.6 The shape fixing ratio 𝑅𝑓 and shape recovery ratio 𝑅𝑟 of PLA/PMMA 7N 50/50

blend films stretched at various strain rates.

Strain rate 𝑻𝒔 (°C) 𝑹𝒇 (%) 𝑹𝒓 (%) 𝑿𝒄 (%) 𝑻𝒓 (°C)

0.02/s 75 96.2 1.3 98.9 0.7 0.2 85

0.005/s 75 96.6 0.9 98.5 1.1 0.4 85

0.002/s 75 97.1 1.8 98.3 0.6 0.9 85

0.2/s 100 98.3 1.1 91.8 2.2 0.8 110

0.005/s 100 98.8 0.9 90.4 1.4 1.9 110

0.002/s 100 99.6 0.8 82.9 1.7 2.6 110

When the sample is stretched at low strain rate, the relaxation of “soft domains” is enhanced,

which could increase the shape fixing ratio. Moreover, a slight increase of crystallinity can be


observed after long time of stretching. These two factors are responsible for the reduced shape

recovery ratio.

Therefore, it could be concluded that a lower strain rate could slightly increase the shape

fixing ratio of PLA/PMMA blends, while decrease the shape recover ratio. In order to reach a

higher shape recovery ratio in the shape memory test, the larger strain rate (0.02/s) was

chosen for further experiments.

6.3.1.3 Discussion

For neat PLA films, the PLA crystallites mainly serve as physical cross-links to keep the

permanent shape of the samples and the amorphous phase between the crystallites works as

switching phase. When PLA films are stretched at lower temperatures (around 𝑇𝑔), there are

two reasons would lead to the reduced recovery ratios: (1) a slight increase of the crystallinity

after stretching; (2) chain slippage at the interfacial regions between the crystalline and

amorphous phase. The chain slippage and crystallization could change the proportions of

switching phase and stationary phase. Accordingly, this effect would lead to a plastic

irreversible modification during the stretching process and significantly reduce the shape

recovery ratio.

As shown in Table 6.5, the neat PLA film exhibits a crystallinity of about 10.8% before

stretching and 15.5% after stretching. This increase of crystallinity may be induced by a strain

(or local orientation)-induced crystallization of PLA, which has been demonstrated by

previous studies [Huang et al. (2011), Saeidlou et al. (2012)]. When the films are stretched

above the glass transition temperature, the active chains in the amorphous phase rearrange

along the deformation direction. Therefore, the stretching process would result in an increase

in crystallinity, and a schematic is given in Figure 6.23.


Figure 6.23 Schematic illustration of microstructure changes of PLA/PMMA blend films

under strain deformation and crystallization.

The cold crystallization of PLA starts around 85 °C (as shown in Figure 6.1). Therefore, when

PLA films are stretched at higher temperature (≥ 85 °C), in addition to the strain-induced

crystallization, cold crystallization is also possible to increase the crystallinity of the samples.

As shown in Figure 6.21a, a stress relaxation behavior can be observed when PLA films are

stretched at 85 °C. This relaxation behavior is a partial relaxation of “soft domains”, which

may reduce the orientation of switching phase. Moreover, this relaxation behavior will lead to

a better shape fixing ratio but reduce the shape recovery ratio.

Therefore, the low recovery ratios of PLA films at high temperatures could be attributed to (1)

partial modification of “stationary phase” induced by strain-induced crystallization and cold

crystallization, (2) plastic irreversible deformation induced by chain slippage between the

crystalline and amorphous chains, (3) relaxation of “soft domains” [Ratna and Karger-Kocsis

(2008), Samuel et al. (2014)].

For semi-crystalline PLA/PMMA blends (PLA rich), a similar mechanism can be used to

explain the influence of temperature on the shape memory properties as for neat PLA.


Consequently, the stretching at higher temperatures shows a positive effect on the shape

fixing ratio, but exhibits a significantly and negative impact on the shape recovery ratio on

neat PLA films and semi-crystalline PLA/PMMA blend films.

For PLA/PMMA 50/50 blend films, the temperature shows similar impact on the shape

memory performances as for neat PLA, but with different mechanisms. The PLA/PMMA

50/50 blend is almost amorphous with an extremely low crystallinity (0.1%). The molecular

entanglements mainly serve as physical cross-links to keep the original shape. When the films

are stretched at low temperatures (around 𝑇𝑔 ), the stress-strain curves shows no stress

relaxation behavior during stretching process. In addition, there is little change of the

crystallinity of the films, indicating the good stability of “hard domains” during stretching.

Therefore, a good shape recovery ratio is obtained for PLA/PMMA 50/50 blend stretched at

𝑇𝑔.

With the increase of stretching temperature, stress-relaxation behavior could be observed

during stretching process. The stress-relaxation behavior will not only reduce the orientation

of switching phase, but also induce disentanglement during stretching [Ratna and Karger-

Kocsis (2008), Wang and Li (2015)]. Moreover, the DSC measurements proved the increase

of crystallinity which will induce a plastic irreversible deformation (as shown in Table 6.5).

Consequently, it can be concluded that the shape fixing ratio of PLA/PMMA 50/50 blend

films is improved with increased stretching temperature, while the shape recovery ratio is

reduced by the increased stretching temperature.


6.3.2 Influence of molecular structure of PMMA and blend composition on the shape

memory properties

6.3.2.1 PMMA’s molecular structure

The influences of PMMA’s molecular structure on the thermo-mechanical and rheological

properties of PLA/PMMA 50/50 blends have been discussed in section 6.2. In this section, its

effect on the shape memory performances of PLA/PMMA blends will be discussed based on

the 50/50 blend.

Figure 6.24 Stress-strain curves of films made of PMMA/50%PMMA6N, 7N and 8N blends

stretched at a strain rate of 0.02 /s at their respective 𝑇𝑔.

As shown in Figure 6.24, the stress-strain curves of symmetric PLA/PMMA blends with

PMMA of various molecular structures display little difference when they are stretched at

same condition at their respective 𝑇𝑔. The shape fixing ratio 𝑅𝑓 and shape recovery ratio 𝑅𝑟 of

three blends were calculated and listed in Table 6.7. It is evident that the blends show similar

𝑅𝑓 and 𝑅𝑟 when they are stretched at their respective 𝑇𝑔. According to the results listed in

Table 6.4, the entanglement density is increasing from 6N to 8N, but the increment is so small

that little difference could be observed in their shape memory performance. Consequently, it

can be concluded that the molar mass of PMMA shows a negligible influence on the shape


memory properties on PLA/PMMA blends due to the small difference between entanglement

densities. Therefore, PMMA 7N was chosen for further experiments.

Table 6.7 The shape fixing ratio 𝑅𝑓 and shape recovery ratio 𝑅𝑟 of films made of

PLA/PMMA 50/50 blends stretched at their respective 𝑇𝑔.

PLA/PMMA 50/50 𝑻𝒈 (°C) 𝑹𝒇 𝑹𝒓 𝑻𝒓 (°C)

6N 73 96.1 1.7 98.2 2.1 83

7N 75 96.2 1.3 98.9 0.7 85

8N 77 95.9 2.2 98.7 1.2 87

6.3.2.2 PMMA’s content

For miscible amorphous/crystalline polymer blends used as shape memory polymers, 𝑇𝑔 of

the amorphous phase is the critical temperature for triggering the shape recovery [Mather et al.

(2009)]. According to our study in the section 6.3.1 and the investigations of Samuel et. al

[Samuel et al. (2014)], the shape memory performance of PLA/PMMA blends presents a

significant “temperature memory effect”. Therefore, the sample’s 𝑇𝑔 is chosen as switching

temperature to compare the influence of blend composition on the shape memory properties.

Figure 6.25 Stress-strain curves of PLA/PMMA blend films stretched at their respective 𝑇𝑔

with a strain rate of 0.02/s.


As shown in Figure 6.25, for each PLA/PMMA blend film, a stable flow stress is reached

after the yield point at ca. 3% deformation when it is stretched at their respective 𝑇𝑔. The

stretching stresses of the blends are quite similar and range from 2.0106 to 3.010

6 Pa.

Furthermore, no stress relaxation or strain hardening behavior could be observed in the steady

state stress levels when the samples are stretched at their respective 𝑇𝑔.

The shape fixing ratios 𝑅𝑓, shape recovery ratios 𝑅𝑟 and crystallinity 𝑋𝑐 after stretching as a

function of PMMA content are listed in Table 6.8. It is evident that all the samples show

shape fixing ratios around 95%, independent of the blend composition. However, the shape

recovery ratios of PLA/PMMA blends exhibit strong composition dependence. The highest

shape recovery ratio was observed for blends containing 30-70% PMMA, and the

corresponding 𝑅𝑟 values for these samples are all above 95%.

Table 6.8 The shape fixing ratio 𝑅𝑓 , shape recovery ratios 𝑅𝑟 and crystallinity 𝑋𝑐 after

stretching of PLA/PMMA blend films stretched at their respective 𝑇𝑔.

PLA/PMMA 𝑇𝑔 (°C) 𝑅𝑓 (%) 𝑅𝑟 (%) 𝑋𝑐 (%) 𝑇𝑟 (°C)

100/0 60 95.1 0.8 88.6 1.1 15.5 70

90/10 62 95.8 1.2 95.1 0.8 8.2 72

70/30 67 95.9 1.5 98.2 1.2 4.9 77

50/50 75 96.2 1.3 98.9 0.7 0.2 85

30/70 85 96.1 1.0 96.9 0.8 0 95

10/90 100 96.6 1.4 86.9 0.5 0 110

0/100 110 96.2 1.3 81.1 1.0 0 120

6.3.3 The shape memory mechanism of PLA/PMMA blend system

As discussed above, the shape memory properties of PLA/PMMA blends show distinct

composition dependence. Therefore, the corresponding mechanism can be divided into two

categories according to the blend composition: semi-crystalline blends and amorphous blends.

For the semi-crystalline blends, the PLA crystallites and molecular entanglement play the role


of physical cross-links. On the other side, for amorphous PLA/PMMA blends, just molecular

entanglements serve as physical cross-links.

Figure 6.26 Shape fixing ratio 𝑅𝑓 and shape recovery ratio 𝑅𝑟 of PLA/PMMA blends as a

function of PMMA content, and the shape memory mechanism at different PMMA contents.

As shown in Figure 6.26, the neat PLA film shows a moderate shape recovery ratio. The PLA

crystallites are considered as the stationary phase for neat PLA, and the active chains between

crystallites play a role of the switching phase. During the stretching process, these disordered

active chains would rearrange along the deformation direction (as shown in Figure 6.23),

leading to an increase of crystallinity. Consequently, the strain-induced crystallization of neat

PLA results in an irreversible modification during the stretching process and significantly

reduces the shape recovery ratio. On the other hand, molecular slippage at the interfacial

regions between the crystalline and amorphous phase will occur upon long-term stress [You et

al. (2012)]. This factor could also reduce the shape recovery ratio of neat PLA.

For the blends with PMMA content less than 50% (PLA-rich), the crystallization of PLA is

strongly hindered by the presence of PMMA (as shown in Figure 6.27). This effect can be

explained by two factors: (1) the incorporation of PMMA into PLA matrix dilutes the PLA

chains in the blends which disrupt the ordered arrangement of PLA chains, (2) the molecular


entanglements between PLA and PMMA chains reduced the mobility of PLA chains in the

matrix, thus limiting the capability of PLA chains to adopt an optimal alignment. Moreover,

the work of Samuel [Samuel et al. (2013)] demonstrates the absence of any other reactions

between PMMA and PLA phase. Therefore, the crystalline phase of PLA was suppressed

when PMMA was introduced.

Figure 6.27 The crystallization 𝑋𝑐 of the films made of PLA/PMMA blends before and after

stretching at their respective 𝑇𝑔.

In addition, the introduction of PMMA into PLA creates new physical cross-links which are

formed by the interactions between PLA and PMMA chains. It could be noticed that the shape

recovery ratios seem to increase with the amount of PMMA up 50%. In this case, in addition

to the PLA crystallites acting as physical cross-links to keep the original shape, the role of

molecular entanglements in the amorphous phase become more important [Ratna and Karger-

Kocsis (2008)] and contribute to the good shape memory properties of the blends. In Figure

6.28a, the shape recovery ratio 𝑅𝑟 shows exponential dependence on both the crystallinity 𝑋𝑐

and the entanglement density 𝑒. However, 𝑅𝑟 decrease with 𝑋𝑐 but increase almost linearly

with 𝑒.


During the stretching process at 𝑇𝑔, it is evident that the crystallinity of the blends is increased

due to the strain-induced crystallization (as shown in Figure 6.27) [Huang et al. (2011),

Saeidlou et al. (2012), Yin et al. (2015)]. Moreover, the disentanglement of long linear

polymer chains during the crystallization process has also been demonstrated [Luo and

Sommer (2012)]. Although PLA/30%PMMA blend and PLA/PMMA 50/50 blend have a

similar entanglement density in the molten state (as shown in Figure 6.28b), the

disentanglement of polymer chains due to the crystallization process could lead to a lower

entanglement density in PLA/30%PMMA blend in comparison with PLA/PMMA 50/50 blend.

Consequently, PLA/PMMA 50/50 blend exhibits better shape recovery ratio than

PLA/30%PMMA blend.

Figure 6.28 The dependence of shape recovery ratio 𝑅𝑟 on (a) crystallinity 𝑋𝑐 (b)

entanglement density 𝑒 for the blends with PMMA contents above 50%.

Concerning the stability of the stationary phase, for semi-crystalline blends, the molecular

entanglements between PLA and PMMA chains seem to have a positive impact on the shape

recovery ratio, while the crystallinity shows a negative impact on it.


Figure 6.29 Shape recovery ratio 𝑅𝑟 as a function of entanglement density 𝑒 for the blends

with PMMA content above 50%.

When PMMA dominates in the blends (PMMA-rich), PLA crystallization is completely

suppressed by the presence of PMMA. The PLA/PMMA blends (PMMA content >50%) are

amorphous and only the entanglement network is responsible for maintaining the original

shape. As shown in Figure 6.29, for the amorphous PLA/PMMA blends in which PMMA

accounts for more than 50% of mass, the shape memory potential is arising from the

entanglement network and strongly dependent on the entanglement density.

According to the previous investigations, the shape memory mechanism of miscible semi-

crystalline/amorphous blends can be concluded from PLA/PMMA blend system. When the

blends are semi-crystalline, the crystallites and molecular entanglement act as physical cross-

links to keep the permanent shape and recovery to it. However, a negative influence will be

induced by crystallites due to a strain-induced or temperature-induced crystallization during

the deformation above the glass transition temperature. For the amorphous blends, the

entanglement network serves as physical cross-link and plays a crucial role to influence the

shape memory performances. In summary, we propose that the entanglement network in

miscible semi-crystalline/amorphous blend is the main factor to maintain the shape recovery

property, which could be compromised by the increased crystallinity. The results of our study


provide a novel understanding of the mechanisms underlying the shape memory properties for

miscible semi-crystalline/amorphous SMPs.

6.4 Conclusions

The thermo-mechanical and rheological properties of miscible PLA/PMMA blends with

different blend compositions and PMMA molar masses were investigated in this work. The

crystallinity of the blends was found to decrease upon mixing with PMMA up to 50% where a

transition from the semi-crystalline to amorphous phase occurs. A smaller entanglement

molar mass for 𝑀𝑒,𝑃𝐿𝐴−𝑃𝑀𝑀𝐴 compared to 𝑀𝑒 of neat components or blends was derived from

the oscillatory shear rheological measurements on the PLA/PMMA blends, suggesting that

the dissimilar chains are more likely to entangle with each other than the similar ones. For the

semi-crystalline blends with PMMA contents less than 50%, an increase in entanglement

density is induced by the addition of PMMA which leads to a decreased crystallinity and an

enhanced shape recovery ratio for the blends. This result demonstrates that the molecular

entanglement has a positive influence on the shape memory performance, whereas crystallites

exhibit an opposite impact which may arise from the strain-induced crystallization and the

molecular slippage between the crystalline and amorphous chains network occurs upon long-

term stress. In the case of an amorphous blends in which PMMA accounts for more than 50%,

an positive dependence was derived between the entanglement network and shape recovery

ratio, indicating that the entanglement network is solely contributing to the shape recovery

potential. In summary, for miscible amorphous/semi-crystalline SMPs, the entanglement

network serves as a critical element in determining the shape recovery capability, while the

effect of crystallites may be an impediment via strain-induced crystallization.

In addition, the influences of stretching temperature, strain rate and component molar mass on

the shape memory performances of PLA/PMMA blends were systematically studied. It was


found that the higher stretching temperature or lower strain rate would result in a larger shape

fixing ratio, but a lower shape recovery ratio. The molar mass of the component could

influence the critical temperature for triggering the shape recovery, but show little influence

on the shape memory properties when they the samples are stretched at their respective 𝑇𝑔.

7. PLA/PMMA/silica nanocomposites

In production processes, the commonly used polymeric materials are usually manufactured by

mixing different macromolecules or incorporating solid “filler” to improve the impact

strength, modulus, processability, conductively, flammability or appearance, etc. [Meijer et al.

(1988)] Polymer nanocomposites have gained extensive interests since the incorporation of

well dispersed nanoparticles can significantly improve the mechanical, optical or barrier

properties. In particular, for polymer blends, the addition of filler can result in either an

increase or a decrease of the temperature of phase separation, change of the interaction

parameter between two components, a modification of the shape of the phase diagram or a

change in the kinetics of phase separation [Lipatov (2002), Lipatov et al. (2002), Ginzburg

(2005), Huang et al. (2005), Lipatov and Alekseeva (2007)]. In recent years, it has been

recognized that small fractions of nanoscale fillers can significantly affect the rheological and

mechanical properties of polymers [Krishnamoorti et al. (1996), Krishnamoorti and Giannelis

(1997), Hoffmann et al. (2000), Lamnawar et al. (2011)]. Moreover, the presence of

nanoparticles can significantly affect the thermodynamic phase behavior of polymer blends [Ji

et al. (2000), Lee et al. (2006)].

In the present work, the intermolecular cooperativity and segmental dynamics in

PLA/PMMA/nanosilica mixtures were studied. The effect of nanosilica (silica 300, 𝑑=7 nm)

on the phase behavior, molecular entanglement, thermo-mechanical and rheological properties

PLA/PMMA 7N 50/50 blends was systematically investigated. For convenience, the unfilled

and filled PLA/PMMA 7N 50/50 blends are designed as P/P/Si x in the following discussion.

Here x represents the silica content (wt %) in the nanocomposite.

108 7 PLA/PMMA/silica nanocomposites


7.1.1 Dispersion of nanosilica in PLA and PMMA

It is well known that the dispersion of nanofillers in the polymer matrix plays an important

role in affecting the physical properties of polymer. A homogeneous dispersion of nanofillers,

together with an optimized interaction between nanofiller and polymer matrix, will effectively

improve the thermal mechanical and rheological properties of the polymer matrix [Li et al.

(2012)]. The dispersion of nanosilica (10 wt%) in PLA and PMMA matrix was firstly

investigated by FE-SEM. As shown in Figure 7.1, the nanoparticles dispersed evenly in both

the PLA and PMMA matrix and exhibited agglomerates with particle size less than 50 nm.

The dispersion level of nanosilica in PLA matrix is highly similar with that in PMMA matrix.

Figure 7.1 SEM micrographs of the fractured surfaces of PLA/10% silica and PLA/10%

silica nanocomposites.

7.1.2 Dispersion of nanosilica in PLA/PMMA blends

In order to elucidate the effect of nanosilica on the phase morphology, the PLA/PMMA 50/50

blend is chosen. The fracture surfaces of samples with and without nanosilica were observed

by FE-SEM. Clearly, as shown in Figure 7.2a, the binary PLA/PMMA blend shows typical

single phase morphology, indicating the good miscibility between PLA and PMMA. For the

7.1 Morphological characterization 109

nanocomposites (Figure 7.2b, c and d), nanosilica particles were detected as white dots. It is

evident that nanosilica particles can form aggregates that are uniformly dispersed in the blend

matrix with average size less than 100 nm, even at low silica contents (2 wt%, Figure 7.2b). A

specific “crater” structure is formed around the nanosilica aggregates which appears to serve

as the central core. With the increase of nanosilica loading, an increase in both the size and

number of the nanosilica aggregates are observed, whereas the dimension of the “crater”

structures is remarkably reduced (Figure 7.2c, d). At higher silica contents (> 5 wt%), the

size of the aggregates can even exceed 300 nm. These observations agree well with the notion

that the higher nanofiller contents, the larger the aggregate forms due to the strong

interactions among the nanoparticles [Li et al. (2012)].

Figure 7.2 SEM micrographs of the fractured surfaces of (a) P/P/Si 0, (b) P/P/Si 2, (c) P/P/Si

5, (d) P/P/Si 10.


An interesting comparison can be made as shown in Figure 7.3. Although the same silica

content of 10 wt% in all the nanocomposites, the dispersions of nanosilica in neat PLA or

PMMA matrix differs significantly from that in polymer blend matrix. In addition, the

nanosilica aggregates formed in the neat polymer matrix are much smaller than that formed in

blend matrix. Interestingly, the specific “crater” structure is solely observed in the fractured

surfaces of the nanocomposites based on PLA/PMMA blends.

Figure 7.3 The dispersion of nanosilica in PLA, PMMA and PLA/PMMA blends with the

same filler concentration of 10 wt%.

The influences of nanoparticles on the overall phase behavior of miscible blend have

extensively been studied [Lipatov (2002), Lipatov et al. (2002), Huang et al. (2005), Lipatov

(2006), Chung et al. (2007), Lipatov and Alekseeva (2007)]. One of the explanations is

7.1 Morphological characterization 111

related to the specific interactions and preferential adsorption on the fillers by one of the

components of the blend [Huang et al. (2005)]. This preferential adsorption will lead to the

unique morphological characterization in the nanocomposites based on miscible blend.

7.2 Preferential adsorption on nanosilica by one of the components of

PLA/PMMA blends

The interactions between nanosilica and the pure components were first investigated by

oscillatory shear rheology. In general, the enhancement of the complex viscosity |𝜂∗| of

nanocomposites mainly depends on the processing method, the dispersion of nanofillers and

the interactions between the nanofillers and the polymer matrix [Bar-Yam (1997)]. As

depicted in Figure 7.1, a similar dispersion of nanosilica (10 wt%) is observed in PLA matrix

and PMMA matrix which were prepared following the same manufacturing procedure.

Therefore, the different enhancements on the linear viscoelastic behaviors are mainly arisen

from the interactions between the nanosilica and the polymer matrix.

Figure 7.4 Normalized complex viscosity |𝜂∗| for the PLA and PMMA nanocomposite

samples containing 10 wt% of nanosilica at 200 °C.

Figure 7.4 illustrates the complex viscosity |𝜂∗| of PLA/10 wt% silica and PMMA/10 wt%

silica nanocomposites relative to |𝜂∗| of their corresponding neat polymer matrix at the


temperature equal to their compounding temperature (200 °C). Normalized complex viscosity

(|𝜂𝑁𝑎𝑛𝑜𝑐𝑜𝑚𝑝𝑜𝑠𝑖𝑡𝑒∗ |/|𝜂𝑀𝑎𝑡𝑟𝑖𝑥

∗ |) curves of different polymers with equal loadings of nanofillers

can provide insight about the affinity of the nanofiller towards each polymer [Abbasi Moud et

al. (2015), Rostami et al. (2015)]. From the results presented in Figure 7.4, it is found that the

normalized complex viscosity for PLA is clearly much higher than that of PMMA at the

whole frequency range, demonstrating a stronger affinity of nanosilica particles towards the

PLA molecular chains as compared to PMMA chains.

Form the molecular perspective, both PLA and PMMA have C = O groups that can interact

with the silanol groups on the surface of silica to form hydrogen bond [Wen et al. (2009)] (as

shown in Figure 7.5). Thus the weaker binding affinity of silica towards PMMA can be

ascribed to the steric hindrance introduced by the CH3 − C = O groups in PMMA.

Consequently, PLA molecules have stronger affinity with nanosilica in comparison with

PMMA molecules.

Figure 7.5 Schematic illustrations of the hydrogen-bonding interactions between (a) PLA and

silica particles, (b) PMMA and silica particles.

The SEM picture of P/P/Si 2 at high magnification (105) is presented in Figure 7.6. It’s

clearly to observe that the nanosilica particles form small agglomerates in the polymer matrix.

These agglomerates interact with nearby PLA or PMMA molecules to form the “crater”

7.2 Preferential adsorption on nanosilica 113

structure, as highlighted in Fig. 4 (left panel). A similar scenario is also observed in a

previous work in which the aggregates formed by nanoscale particles leads to the

redistribution of other components like poly(vinylidene fluoride) (PVDF)/PMMA blends

filled by modified multiwalled carbon nanotubes (MWNTs) [Sharma et al. (2014)]. Given the

fact the stronger binding affinity of nanosilica towards PLA, it can be expected that the PLA

molecules are more likely to adsorb on the surface of nanosilica in comparison with PMMA.

We propose a model describing the composition of the “crater” structure induced by the

addition of nanosilica particles, as seen in Figure 7.6 (right panel). A selective accumulation

of PLA molecules surround the surface of silica aggregates, while the PMMA molecules are

mainly distributed at the peripheric of the “crater” structure.

Figure 7.6 SEM micrographs of the fractured surfaces of P/P/Si 2 nanocomposites. The

specific “crater” structure is highlighted by the red circle (left panel). A schematic diagram

illustrating the composition of the “crater” structure in which a preferential adsorption of PLA

molecules on the surface of nanosilica aggregates is suggested.


7.3 Thermo-mechanical properties

7.3.1 DSC

The influence of nanosilica on the thermo-mechanical behavior of PLA/PMMA blends was

determined by DSC. As shown in Figure 7.7a, the DSC curves of the second heating scan

exhibit single broad glass transition temperature 𝑇𝑔, confirming the miscibility of

nanocomposites in the solid state. It is worth noting that 𝑇𝑔 is increasing with the addition of

nanosilica, which shows no effect on the 𝑇𝑔 of PLA/silica or PMMA/silica mixtures.

Lodge−McLeish Model: “self-concentration”

Figure 7.7 (a) DSC second heating scans of P/P/Si x, and (b) variation of 𝑇𝑔 with silica

concentration for PLA/PMMA blends.

According the previous studies [Wetton et al. (1978), Roland and Ngai (1993), Shi et al.

(2013)], the broadening of 𝑇𝑔 for PLA/PMMA/nanosilica attributes to the concentration

fluctuations and dynamic heterogeneity in the miscible blend. A concept of “self-

concentration” was proposed by Lodge and McLeish [Lodge and McLeish (2000)], and the

effective glass transition temperature 𝑇𝑔,𝑒𝑓𝑓 for each component could be calculated according

to Equations (6.1-6.3).

7.3 Thermo-mechanical properties 115

In a miscible blend, the dynamics of higher 𝑇𝑔 component in the mixture is more

representative of the average blend composition, while the dynamics of lower 𝑇𝑔 component

is similar to its pure component [Lodge and McLeish (2000)]. That is to say, the calorimetric

𝑇𝑔 of PLA/PMMA 50/50 blend should be in accordance with the 𝑇𝑔,𝑒𝑓𝑓 of PMMA at 50%

content. Surprisingly, a large discrepancy between the calorimetric 𝑇𝑔 of unfilled

PLA/PMMA blend and the effective glass transition temperature of PMMA is observed in

Figure 7.7b. With the increase of nanosilica concentration, this discrepancy between

calorimetric 𝑇𝑔 and 𝑇𝑔,𝑒𝑓𝑓,𝑃𝑀𝑀𝐴 is reduced, suggesting the presence of nanosilica increases the

concentration fluctuations and dynamic heterogeneity of PLA/PMMA blends.

Crystallization of PLA/PMMA/nanosilica mixtures

Interestingly, the presence of nanosilica slightly increases the crystallization tendency of PLA,

and a small but significant melting peak can be observed around 165 °C for P/P/Si 10

(crystallinity approach 0.4%, see Figure 7.7a). For P/P/Si 0, the crystallinity index of PLA is

extremely weak (approach zero) due to the intimate mixing of PLA and PMMA chains

[Samuel et al. (2014)]. A possible interpretation for the increase of the crystallinity of PLA is

the preferential interactions between nanosilica and PLA molecules, which would lead to the

local accumulation of PLA around the surface of nanosilica aggregates. These aggregates

seem to act as potential nucleation agent which is proposed to increase the crystallinity of

PLA [Nofar et al. (2013)].

7.3.2 Dynamic mechanical analysis (DMTA)

Figure 7.8 shows the storage modulus 𝐸′ and loss modulus 𝐸′′ as a function of temperature

for unfilled PLA/PMMA blend and nanocomposites containing 2, 5 and 10 wt% of nanosilica.

The moduli at temperatures below 𝑇𝑔 are increasing with the addition of nanosilica, indicating

the presence of nanosilica improves the stiffness of matrix. A well-defined relaxation peak


(i.e., transition) was displayed around 71 °C for unfilled PLA/PMMA blend. The peak of

loss modulus (𝑇) also moves to higher temperatures, corresponding to the result of DSC tests.

In addition, the broadness of transition is also increased with the addition of nanosilica.

Figure 7.8 The loss and storage modulus as function of temperature for PLA/PMMA 50/50

blends with different nanosilica contents.

7.4 Rheological properties of PLA/PMMA/silica nanocomposites

7.4.1 Oscillatory strain sweep

The linear viscoelastic region of the samples can be determined by the dynamic amplitude

measurements. Figure 7.9 exhibits the strain dependence of the dynamic storage modulus 𝐺′

of the pure PLA/PMMA blend and its nanocomposites at 200 °C at an angular frequency of

10 rad/s. Obviously, 𝐺′ at low strain range increases monotonously with increased silica

content, but the linear viscoelastic region of the nanocomposite was reduced by the presence

of nanosilica. The linear viscoelastic region for the unfilled PLA/PMMA blend is around 30%,

while that for P/P/Si 10 is just 1.5%. Therefore, the following dynamic rheological

measurements were performed at = 1%.

7.4 Rheological properties of PLA/PMMA/silica nanocomposites 117

Figure 7.9 The storage modulus 𝐺′ for pure PLA/PMMA blend and PLA/PMMA/silica

nanocomposites obtained in strain sweeps at 200 °C and 10 rad/s.

7.4.2 Oscillatory time sweep

Oscillatory time sweeps are very important for polymer/particle mixtures, which may undergo

macro- or microstructural rearrangements with time. These rearrangements may be induced

by the polymer degradation or particle diffusion in the composites.

For unfilled PLA/PMMA blends, thermal stability can be accessed via the change of storage

modulus 𝐺′ as a function of time. As shown in Figure 7.10, it is evident that the thermal stable

time for P/P/Si 0 is about 8000 s at 200 °C. With the incorporation of 2 wt% nanosilica, the

thermal stability exhibits a slight increase and stabling time shifts to 9000 s. This result

indicates the presence of nanosilica improved the thermal stability of PLA/PMMA blends.


Figure 7.10 Relative change of storage modulus as a function of the residence time at 200 °C

for P/P/Si x.

For PLA/PMMA blend containing high contents of nanosilica (>5 wt%), a distinct increase of

the normalized 𝐺′ can be observed in the short time range. This increase is induced by the

structure build-up in the nanocomposites at molten state [Eslami et al. (2009)]. 𝐺′ begins to

decrease when the experimental time exceed 10000 s, indicating that possibly the begin of

polymer degradation.

7.4.3 Oscillatory frequency sweep

Time-temperature superposition (TTS)

Time-temperature superposition (TTS) principle can be used to determine the phase

separation temperature of polymer blends [Jeon et al. (2000)], and can also extend the

frequency or time range [Van Gurp and Palmen (1998)]. It has been proved that for

temperatures in the homogeneous region, TTS principle worked well. While TTS principle

failed in the temperature range of phase separation [Nesarikar (1995), Kapnistos et al. (1996)].

Figure 7.11 shows the master curves of the P/P/Si x at the reference temperature of 200 °C

obtained by TTS.


Figure 7.11 Master curves of 𝐺′, 𝐺′′, |𝜂∗| and 𝑡𝑎𝑛𝛿 for (a) P/P/Si 0, (b) P/P/Si 2, (c) P/P/Si 5,

(d) P/P/Si 10, at a reference temperature of 200 °C. The rheological data were measured at

190-220 °C (□■190 °C, △▲200 °C, ○●210 °C, ▽▼220 °C).

As shown in Figure 7.11a, the unfilled PLA/PMMA blend follows the known rheological

relations G′~𝜔2 and G′′~𝜔1 in the terminal region. The TTS principle holds satisfactorily for

𝐺′ , 𝐺′′ , 𝜂∗ and 𝑡𝑎𝑛𝛿 when the temperature is not higher than 210 °C, while TTS breaks

drown for 𝐺′ and 𝑡𝑎𝑛𝛿 at 220 °C. An obvious plateau is present in the low frequency region.

This result indicates that unfilled PLA/PMMA blend is a homogeneous mixture when the

temperature is below 210 °C, and phase separated when the temperature is above 210 °C.

Therefore, the phase separation temperature for the unfilled PLA/PMMA blend is between

210 and 220 °C.


The incorporation of nanosilica changed the slope of 𝐺′ in the terminal region, and its value

decreases with increased silica content. For P/P/Si 2 nanocomposite, a slope equal to 2 can

still be observed in the terminal region (Figure 7.11b), and the TTS principle applied well for

the temperature below 220 °C. A weak plateau of 𝐺′ can be observed at 220 °C in the low

frequency region, and the deviation of 𝑡𝑎𝑛𝛿 at low frequency region is also obvious. It can be

deduced that the phase separation temperature for P/P/Si 2 nanocomposite is around 220 °C,

which is slightly higher than that of unfilled PLA/PMMA blend. The slope of 𝐺′ at the

terminal region for P/P/Si 5 and P/P/Si 10 are both less than 2 (Figure 7.11c, d), while the

TTS principle worked well for both nanocomposites in the temperature range of the

experiments, indicating both of their phase separation temperatures are above 220 °C.

Han plots

In order to investigate the phase separation rheologically, an alternative method proposed by

Han is adopted. The Han plot (log𝐺′ vs. log𝐺′′) eliminates the effects of frequency, and it is

proved to be more sensitive to the phase separation induced by temperature [Nesarikar (1995),

Kapnistos et al. (1996)]. As shown in Figure 7.12a and 7.12b, the log𝐺′-log𝐺′′ curves of

P/P/Si 0 and P/P/Si 2 could be superposed on the same master curve at the temperatures from

180 to 210 °C, respectively. But the heterogeneous phase curves at 220 °C clearly deviate

from their own master curve. This result demonstrates their phase separation temperatures are

both located between 210 and 220 °C, agreeing with the conclusions obtained by TTS

principle.


Figure 7.12 Master curves of Han plot (i.e. log𝐺′ vs. log𝐺′′), (a) P/P/Si 0, (b) P/P/Si 2, (c)

P/P/Si 5, (d) P/P/Si 10.

For P/P/Si 5 and P/P/Si 10 nanocomposite (Figure 7.12c, d), the homogeneous phase curves

coincide over the whole temperature range (180 to 220 °C) of the experiments, indicating that

their phase separation temperatures are above 220 °C. Consequently, the result from Han plot

is well consistent with that from TTS.

According to the analysis results from TTS and Han plot, it can be concluded that the

incorporation of nanosilica increases the phase separation temperature, suggesting that the

phase stability of PLA/PMMA blends is enhanced by the presence of nanosilica. Similar

effect induced by silica particles on the phase separation temperature was also observed by

other researchers [Lipatov et al. (2002), Huang et al. (2005)].


7.4.4 Molecular entanglement

As discussed above, the presence of nanosilica in PLA/PMMA blend can change its phase

behavior. It has been demonstrated that the preferential adsorption between nanosilica and one

of the components in PLA/PMMA blends will lead to the redistribution of the components in

the matrix bulk. According to previous work [Wu (1987), Zhang et al. (2015)] the molecular

entanglement in miscible blend is significantly impacted by the blend composition. Therefore,

the molecular entanglement in PLA/PMMA blend will be influenced by the incorporation of

nanosilica.

Figure 7.13 Storage modulus 𝐺′ and damping 𝑡𝑎𝑛 as a function of angular frequency 𝜔 for

P/P/Si x at 140 °C.

Figure 7.12 shows the master curves of PLA/PMMA/silica nanocomposites at a reference

temperature of 200 °C. The plateau modulus 𝐺𝑁0 can be determined by two methods: (I) 𝐺𝑁

0

equals to 𝐺′ where 𝑡𝑎𝑛 reaches a minimum using Equation (4.19); (II) 𝐺𝑁0 can be calculated

by the crossover modulus using Equation (4.21). As shown in Figure 7.13, 𝑡𝑎𝑛𝑚𝑖𝑛 of P/P/Si x

can be obtained at 140 °C. The entanglement molar mass and entanglement density of P/P/Si

x determined by both methods are listed in Table 7.1.


Table 7.1 Plateau modulus 𝐺𝑁0 , entanglement molar mass 𝑀𝑒 and entanglement density 𝑒

of

P/P/Si x.

𝑮𝑵𝟎 a

(×105 Pa

)

𝒆 a

(×10-4

mol/cm3)

𝑮𝑵𝟎 b

(×105 Pa

)

𝒆 b

(×10-4

mol/cm3)

P/P/Si 0 10.4 ± 0.2 3.3 ± 0.2 8.8 ± 0.1 3.2 ± 0.1

P/P/Si 2 11.3 ± 0.1 3.5 ± 0.1 9.4 ± 0.1 3.4 ± 0.1

P/P/Si 5 12.9 ± 0.1 4.1 ± 0.1 10.4 ± 0.1 3.8 ± 0.1

P/P/Si 10 16.7 ± 0.2 5.2 ± 0.2 14.2 ± 0.1 5.1 ± 0.1 a

Estimated by using “crossover modulus-based methods” of Equation (4.21) at 200°C. b

Estimated by using “MIN methods” of Equation (4.19) at 140°C.

The relationship between entanglement density 𝑒 and nanosilica content are plotted in Figure

7.14. The values of 𝑒 can be calculated via Equation (4.19) and Equation (4.21). It is found

that the 𝑒 values calculated by “crossover modulus method” are a little higher than that

obtained by “MIN method” due to the semi-quantitative nature of the former method.

However, the results show the same variation tendency with the addition of nanosilica. It is

evident that 𝑒 exhibits a linear increase with silica content.

Figure 7.14 Entanglement density 𝑒 versus weight fraction of nanosilica for P/P/Si x.

The increase of entanglement density in PLA/PMMA/nanosilica mixture could be attributed

to (i) the redistribution of components around the surface of silica and the bulk matrix, (ii)

nanosilica particles also work as entanglement netpoints in the nanocomposites.


According to the discussion in section 6.1 and 6.2, the entanglement network in miscible

blend is significantly influenced by the molecular structure of the components and blend

composition. As stated previously, the incorporation of nanosilica into PLA/PMMA blends

can change the composition around the surface of silica and in the blend matrix due to

selective interactions (or preferential adsorption) between the surface of nanosilica and PLA

molecules. The original composition in blend matrix is 50/50. However, in the nanosilica

filled PLA/PMMA blends, the “crater” structure around silica agglomerate is rich in PLA

molecules, while the bulk matrix among the “crater” structures is rich in PMMA molecules.

As shown in Figure 7.2, the increase of nanosilica content increased the amount of “crater”

structure, i.e., the redistribution of molecular chains is exacerbated due to the addition of

nanosilica. Our previous investigations also demonstrated the dependence of molecular

entanglement on the blend composition in PLA/PMMA blends (See section 6.1). Therefore,

the entanglement network in PLA/PMMA blends is significantly influenced by the addition of

nanosilica. In addition, nanosilica particles with large specific surface area could strongly

interact with polymer chains. These nanoscale rigid particles could also play the role of

netpoints similar to the molecular entanglements. Therefore, nanosilica increased apparently

the entanglement density in PLA/PMMA/nanosilica mixture.

7.4.5 Creep and recovery experiment

In order to investigate the influence of nanosilica on the melt elasticity of PLA/PMMA blends,

the creep and recovery experiments of P/P/Si x were carried out at 200 °C. As shown in

Figure 7.15a, the creep compliance is decreasing with the addition of nanosilica,

corresponding to the increase of viscosity. For P/P/Si 0, P/P/Si 2 and P/P/Si 5, a slope of 1 in

the double logarithmic plot is reached with the chosen creep time of 2000 s. However, the

creep compliance of P/P/Si 10 approaches to a constant value with the increase of creep time.

This constant is named as elastic equilibrium compliance 𝐽𝑒 , which is induced by the


formation of silica network in the matrix. The melt elasticity of PLA/PMMA/nanosilica

composites is increasing with silica concentration up to 10 wt%. As shown in Figure 7.15b,

the zero-shear viscosity of P/P/Si 10 is non-existent due to the formation of silica network.

Therefore, it can be deduced that the rheological percolation threshold φ𝑐 of

PLA/PMMA/nanosilica is around 10 wt% silica content.

Figure 7.15 (a) Creep and recovery curves of nanosilica for P/P/Si x performed at 200 °C,

and (b) complex viscosity |𝜂∗| as a function of ω in comparison with 𝑡/𝐽(𝑡𝑐𝑟) in dependence

on creep time 𝑡 at 200 °C.

7.5 The influence of nanosilica on the shape memory properties of

uniaxially stretched PLA/PMMA blends

The method described in section 6.3 is used to study the impact of nanosilica on the shape

memory performances of the symmetric PLA/PMMA blends modified by nanosilica. The

glass transition temperature of each sample is chosen as stretching temperature to avoid the

influence induced by temperature. The stress-strain curves of PLA/PMMA/nanosilica

composites determined at their respective 𝑇𝑔 are shown in Figure 7.16. For each sample, a

constant stress level was reached after the yield point at about 3% deformation, and no


relaxation could be observed during the stretching process. In addition, the stretching stress is

decreasing with the addition of nanosilica.

Figure 7.16 Stress-strain curves of PLA/PMMA/silica nanocomposites stretched at their

respective 𝑇𝑔 with a strain rate of 0.02/s.

The shape fixing ratio 𝑅𝑓 and shape recovery ratio 𝑅𝑟 are calculated and listed in Table 7.2. It

was found that the incorporation of nanosilica has no influence on the shape fixing ratio of the

composites. According to the investigations in section 6.3, the shape fixing ratio is mainly

determined by the stretching temperature and strain rate. Moreover, a decrease of shape

recovery ratio is observed with the incorporation of nanosilica. The PLA/PMMA/silica

nanocomposites with 10 wt% nanosilica exhibit the lowest shape recovery ratio. Although the

incorporation of nanosilica increased apparently the entanglement density of PLA/PMMA

blend, the crystallinity was also increased due to the selectively dispersion of PLA chains

around silica surface. The strain induced crystallinity and relatively high 𝑇𝑔 (close to the cold

crystallization temperature) will significantly increase the crystallinity after stretching.

Therefore, the incorporation of nanosilica would reduce the shape recovery ratio of

PLA/PMMA 50/50 blends due to the increased crystallinity.

7.5 Shape memory properties of PLA/PMMA/nanosilica mixtures 127

Table 7.2 The shape fixing ratio 𝑅𝑓 and shape recovery ratio 𝑅𝑟 of PLA/PMMA 50/506N, 7N,

8N blend films stretched at their respective 𝑇𝑔.

𝑻𝒔 (°C) 𝑿𝒄a(%) 𝑹𝒇 𝑹𝒓 𝑿𝒄

b (%) 𝑻𝒓 (°C)

P/P/Si 0 75 0.1 96.2 1.3 98.6 0.7 0.2 85

P/P/Si 2 77 0.1 96.7 2.5 98.1 1.2 0.5 87

P/P/Si 5 79 0.2 96.5 0.4 97.4 1.5 1.1 89

P/P/Si 10 80 0.5 96.9 1.6 95.7 2.5 1.8 90 a

Evaluated by DSC before stretching. b

Evaluated by DSC after stretching.

7.6 The shape memory of biaxially stretched films

In order to produce shape memory films for industrial application, a biaxial stretching

equipment is used to produce films. In general, biaxially stretched films based on PLA are

usually used for packaging application, and PLA4032D is a grade designed for realization of

films. As discussed above, the addition of PMMA into PLA could increase its shape memory

properties, but still reduce the film formation ability. Hence, a PLA/PMMA 7N 80/20 blend

with low PMMA content is chosen to produce biaxially stretched films. For convenience,

PLA/PMMA 7N 80/20 blends can be abbreviated to P/20P. In addition, PLA/PMMA 7N

80/20 blends filled by 2 wt% silica 300 is designed as P/20P/Si 2.

In this section, neat PLA, P/20P and P/20P/Si 2 were chosen to produce biaxially stretched

films. The glass transition temperatures of these three samples are 60, 63, 64 °C, respectively.

When the cast films are stretched around 𝑇𝑔, only small stretch ratio (≤ 22) could be reached

without film tearing. In consideration of the small difference between samples’ 𝑇𝑔 , same

stretching temperature (𝑇𝑠= 80/90 °C) was chosen in this work to draw films at a strain rate of

20%/s up to different stretch ratios .

In order to measure the shape memory properties of biaxially stretched films, the cast films

were treated under a specific temperature-deformation program shown in Figure 7.19. The


recovery temperature is 10 °C higher than the stretching temperature 𝑇𝑠. The shape fixing

ratio 𝑅𝑓 and shape recovery ratio 𝑅𝑟 can be determined based on Equations (4.11 and 4.12), as

shown in Table 7.3.

Figure 7.19 Schematic diagram for shape memory test of biaxially stretched films.

Figure 7.20 shows the nominal stress-strain curves of the cast films made of PLA, P/20P and

P/20P/Si 2 simultaneously stretched at 80 °C with a strain rate of 20%/s. The small deviation

between the curves of machine direction (MD) and transverse direction (TD) stresses is

induced by the mechanical artifact, and this deviation is not related to the pre-orientation of

cast films [Capt et al. (2001)]. As expected, a highly non-linear stress-strain response was

observed when the biaxially stretched films were in the rubbery state. It is evident that the

neat PLA has the lowest modulus, flow stress, yield stress and strain hardening stress. With

the incorporation of PMMA and nanosilica, the modulus and stresses increase, P/20P/Si 2

7.6 The shape memory of biaxially stretched films 129

nanocomposites exhibit the highest values. Moreover, pronounced stain hardening behavior

could be observed after 150% deformation (around stretch ratio 2.52.5) at 80 °C, and the

strain hardening modulus is enhanced by the addition of PMMA and nanosilica.

Figure 7.20 Stress-strain curves for the cast films made of PLA, P/20P and P/20P/Si 2

stretched up to different ratios at 80 °C with a strain rate of 20%/s.

When the samples are stretched at 80 °C, 3.53.5 is the maximum stretch ratio that could be

reached without the sample tearing. As the deformation temperature increase, the modulus

and stresses decreases, consistent with the previous reports [Menary et al. (2012)]. As shown

in Figure 7.21, the maximum stretch ratio for films stretched at 90 °C increased to 44, and

the strain hardening behavior occurred at higher strain (around stretch ratio 3.53.5),

indicating the relaxation behavior at higher temperature. Interestingly, PLA displayed the

largest strain hardening modulus while P/20P showed the smallest value, corresponding to the

crystallinity of the samples after stretching (as shown in Table 7.3). This result demonstrated

that the strain hardening behavior occurring at the high temperatures was related to the

recrystallization of the samples during stretching.


Figure 7.21 Stress-strain curves for the cast films stretched up to the maximum stretch ratio at

80 and 90 °C with a strain rate of 20%/s.

As discussed in section 6.31, a higher stretching temperature results in a better shape fixing

ratio. The stretching temperatures used in this work (80/90 °C) are much higher than 𝑇𝑔, and

the stretched films were cooling to room temperature under the fixation of stretcher’s clamps.

Therefore, a high shape fixing ratio around 99% is obtained for all samples.

As shown in Table 7.3, the shape recovery ratios of three films show different dependencies

on the stretching temperature and stretch ratio. When the cast films are stretched at 80 °C, the

stretch ratio exhibits more significant impact on the shape recovery ratio of neat PLA than for

P/20P and P/20P/Si 2 due to the higher crystallinity of neat PLA. For neat PLA films, the

increase of stretch ratio could dramatically reduce the shape recovery ratio. While for PLA,

P/20P and P/20P/Si 2, the impact of stretch ratio on the shape recovery ratio is relatively small

in comparison with neat PLA. Moreover, P/20P exhibits higher 𝑅𝑟 than P/20P/Si 2, implying

that the presence of nanosilica reduces the shape memory property of PLA/PMMA blends.

This result is in good agreement with the conclusions obtained at section 7.5.

7.6 The shape memory of biaxially stretched films 131

Table 7.3 The shape fixing ratio 𝑅𝑓 and shape recovery ratio 𝑅𝑟 of the cast films made of

PLA, P/20P and P/20P/Si 2 stretched at 80 or 90 °C with a strain rate of 20%/s up to different

ratios (), and the crystallinity 𝑋𝐶 of the cast films before and after stretching.

𝑿𝑪a 𝑻𝒔 (°C) 𝑹𝒇 (%) 𝑹𝒓 (%) 𝑿𝑪

b

PLA 10.8%

80

22 99 84.1 0.3 15.8%

33 99 52.5 0.1 24.5%

3.53.5 99 42.4 0.4 30.1%

90

22 99 78.7 0.3 17.4%

33 99 40.1 0.4 26.5%

3.53.5 99 36.6 0.2 33.3%

44 99 33.5 0.3 35.6%

P/20P

2.3%

80

22 99 98.1 0.1 3.4%

33 99 95.6 0.2 4.9%

3.53.5 99 94.4 0.2 6.8%

90

22 99 85.2 0.2 4.1%

33 99 46.2 0.3 6.2%

3.53.5 99 41.5 0.2 7.5%

44 99 38.8 0.4 8.2%

P/20P/Si

2

3.5%

80

22 99 97.0 0.1 4.5%

33 99 89.7 0.3 5.8%

3.53.5 99 80.3 0.1 7.9%

90

22 99 79.2 0.2 5.2%

33 99 43.3 0.3 8.1%

3.53.5 99 38.3 0.5 8.9%

44 99 36.6 0.2 9.3% a crystallinity of the cast films before stretching.

b crystallinity of the cast films after stretching.

When the films are stretched at 90 °C, the impact of stretch ratio on 𝑅𝑟 is more significant for

all the films compared with lower temperatures. A higher stretch ratio (>22) could reduce 𝑅𝑟

notably. This effect is attributed to the increased crystallinity (as shown in Table 7.3) and

longer time for stress relaxation (as shown in Figure 7.21) when films are stretched up to

higher ratios.

Therefore, in order to get films with good shape recovery, the stretching temperature should

be fixed around 𝑇𝑔, and the deformation should be lower than 100%. The higher temperatures

or larger stretch ratios will more significantly increase the crystallinity of the films and


improve their stress relaxation behavior during stretching process, but eventually reduce the

shape recovery ratio.

7.7 Conclusions

PLA/PMMA 50/50 blend filled by nanosilica in various concentrations were prepared via

melt blending. The results of the thermo-mechanical analysis demonstrated the miscibility of

the nanocomposites in the solid state, and the broadening of 𝑇𝑔 revealed that the incorporation

of nanosilica increased the concentration fluctuations and dynamic heterogeneity in

PLA/PMMA blends. A distinct “crater” structure at the cross section of

PLA/PMMA/nanosilica mixtures was observed by SEM, and the dimension of the “crater”

structure was reduced markedly with the increased nanosilica content. The preferential

interactions of nanosilica and the components of the blend were predicted by oscillatory shear

experiments. The results revealed that nanosilica has stronger interactions with PLA

molecules in comparison to PMMA molecules. Therefore, PLA molecules were selectively

adsorbed on the surface of nanosilica in the PLA/PMMA/nanosilica mixtures. According to

the analysis from TTS and Han plot, it could be concluded that the incorporation of nanosilica

increased the phase separation temperature in comparison with the unfilled PLA/PMMA

blend, and also enhanced its phase stability. The entanglement network formed in

PLA/PMMA blend was also influenced by the presence of nanosilica. The values of 𝐺𝑋 and

𝐺𝑁0 of the nanocomposites measured at 200 °C exhibited similar linear growth with the

addition of nanosilica. Moreover, the increase of silica content resulted in a linear decrease of

𝑀𝑒 and a linear increase of 𝑒. A possible mechanism for this result was proposed based on

the preferential adsorption of PLA molecules on the surface of nanosilica, and this

preferential adsorption resulted in the change of blend compositions in the “crater” structures

and the bulk matrix among the “crater” structures.

The influence of nanosilica on the shape memory property of symmetric PLA/PMMA blend

was also investigated. It was found that the addition of nanosilica reduced the shape recovery

ratio due to the increased crystallinity. Moreover, the shape memory performances of

134 8. Summary and Outlook

biaxially stretched films made of neat PLA, PLA, P/20P and P/20P/Si 2 were also

investigated. The larger stretch ratios could significantly reduce the shape recovery ratio,

especially at higher temperatures. The reduced shape recovery ratio is attributed to the longer

time to crystallization and stress relaxation when the films are stretched up higher ratios.

135

8. Summary and Outlook

Summary

Polylactide (PLA) is one of the most promising biopolymers that are made from renewable

sources. It is nontoxic to the human body and the environment and, therefore, highly

biocompatible. Although these properties make PLA to be widely used as food packaging or

biomedical materials, etc. some drawbacks, such as low heat resistance, poor thermal stability

and mechanical resistance hinder the application of PLA.

Mixing of inorganic particle into polymer material is widely used to tailor polymers physical

properties and processibility, in which the size and concentration of the former play a critical

role in polymer processing. In this study, rigid spherical silica particle with varying average

primary particle size (7 nm, 40 nm, and 9 μm) were used to reinforce polylactide (PLA) by

melt compounding.

The dependence of rheological properties of PLA/silica composites on the silica size and

concentration were examined by dynamical mechanical and creep-recovery experiments. Our

results demonstrate that mixing of silica particles into PLA matrix could increase the thermal

stability of PLA. Oscillatory shear tests in the linear viscoelastic regime revealed a strong

concentration-dependent behavior for the storage and loss moduli, and the complex viscosity

of the PLA/silica composites by the addition of nanosilica, while these properties were

slightly affected by the addition of microsilica at low frequencies. A linear relationship

between the silica concentration and the logarithm of zero shear viscosity (log0) of the

composites is found when the concentration is below the rheological percolation threshold,

whereas the growth rate is inversely influenced by the silica particle size. Creep-recovery

experiments indicated that the elastic properties of PLA were more sensitive to the addition of

silica than the viscous properties. Even for microsilica, a remarkable enhancement of the

elastic properties was found at low silica concentration. A model based on the radius of


gyration of polymer matrix 𝑅𝑔 and the mean distance between particles 𝐷 is proposed to

describe the interactions between polymer matrix and particles. When 𝐷 is larger than 2𝑅𝑔,

the particles-polymer interactions are suggested to be responsible for the rheological

properties. On the other side, when 𝐷 is smaller than 𝑅𝑔, a silica network will be formed and

the rheological properties of the composites are dominated by the interactions of particle-

particle and particle-polymer.

The second object of this work is about the thermo-mechanical and rheological properties of

PLA/PMMA blends. The PLA/PMMA blend system is a typical miscible semi-crystalline/

amorphous polymer blend with shape memory potential and has received increasing interest

in recent years. With the incorporation of PMMA into PLA, a broad glass transition and

increased glass transition temperature 𝑇𝑔 fitting partially with the Lodge-McLeish model were

observed by differential scanning calorimetry (DSC) measurements. The broadening of glass

transition is attributed to the local nanoscale heterogeneities in the miscible blend system

which is related to the “self-concentration” of the components. The degree of molecular

entanglement of the blends was derived based on the oscillatory rheological measurements,

showing that the dissimilar chains are more likely to entangle with each other than the similar

ones, and the entanglement density 𝑒 is enhanced with increased PMMA content up to 50%

where a 100% recovery of the initial shape is yielded. The influences of stretching

temperature, strain rate, blend composition and molar mass on the shape memory

performance of PLA/PMMA blends were also investigated. It was found that the shape

memory properties of PLA/PMMA blends present a significant “temperature memory effect”.

The mechanism underlying the shape memory property is further validated by performing the

shape memory test on the PLA/PMMA blend films at their respective 𝑇𝑔. It is evident that for

the semi-crystalline blends (PLA rich), PLA crystallites and molecular entanglement provide

physical cross-links for shape recording, while a negative effect of crystallinity on the shape

137

recovery ratio is obtained due to the strain-induced crystallization and chain slippage between

the crystalline and amorphous chains. On the other hand, for the amorphous blends (PMMA

rich), the shape recovery ratio shows a strong exponential dependence on 𝑒 , and the

entanglement network is regarded as the most important factor in the shape memory

performance.

Nanosilica filled PLA/PMMA 50/50 blends with various silica concentrations (2, 5, 10 wt%)

were prepared by melt mixing. In this section, the effects of silica concentration and the

preferential adsorption between silica and the components on the thermo-mechanical and

rheological properties of PLA/PMMA blends were systematically investigated. The results of

DSC indicate the miscibility of PLA/PMMA/silica nanocomposites in the solid state, and the

incorporation of nanosilica does not only increase the glass transition temperature but also

extend the broadness of glass transition. Local nanoscale heterogeneities in the miscible

blends are proposed due to the self-concentration of the components, and the presence of

nanosilica increased the concentration fluctuation and dynamic heterogeneity of the

PLA/PMMA blends. A distinct “crater” structure can be observed in the fractured surfaces of

the blend nanocomposites. According to the results of SEM and rheological measurements, it

was proposed that PLA molecules were selectively adsorbed on the surface of nanosilica, and

the preferential adsorption of PLA changed the blend composition in the “crater” structure

and the bulk matrix. The phase separation temperature of the filled PLA/PMMA blends was

also increased by the incorporation of nanosilica, implying a potential role of nanosilica in

improving the phase stability of PLA/PMMA blends. In addition, nanosilica could apparently

increase the entanglement density and decrease the entanglement molecular weight of the

blends in a concentration-dependent manner. Finally, the influence of silica nanoparticles on

the shape memory performances of PLA/PMMA blends was investigated. Biaxailly stretched


films were also produced to investigate the influences of stretch ratio and temperature on the

shape memory properties.

Outlook

For the purpose of application of shape memory films, it would be interesting to study the

influences of stretching mode, temperature, speed, ratio and blend composition on the shape

memory properties of PLA/PMMA films.

The diffusion process at the polymer/polymer interface of bilayer system based on PLA and

PMMA with varying molar masses will be investigated by small-amplitude oscillatory shear

measurements. We will study the inter-diffusion kinetics as well as the development of

interphase for symmetrical and asymmetrical bilayers based on PLA and PMMA in the

further work.

9. Summary (in German)

Polylactid (PLA) ist eines der vielversprechendsten Biopolymere, welche aus erneuerbaren

Quellen hergestellt werden. Es ist nicht toxisch für den menschlichen Körper und die Umwelt

und daher in hohem Maße biokompatibel. Obwohl PLA aufgrund dieser Vorteile weithin für

Lebensmittelverpackungen oder biomedizinische Materialien usw. verwendet werden könnte,

behindern einige Nachteile wie geringe Wärmebeständigkeit, geringe thermische Stabilität

und mechanische Festigkeit die Anwendung von PLA.

Mischungen von anorganischen Partikeln mit Polymermaterialien werden am häufigsten

verwendet, um ein prozessierbares Polymer mit den gewünschten physikalischen

Eigenschaften maßzuschneidern, wobei die Größe und die Konzentration der Partikel eine

kritische Rolle bei der Polymerverarbeitung spielen. In dieser Arbeit wurden starre,

sphärische Silicapartikel mit unterschiedlicher Größe (durchschnittliche Durchmesser von 7

nm, 40 nm, und 9 μm) verwendet, um PLA durch Schmelzmischen zu verstärken. Die

Abhängigkeit der rheologischen Eigenschaften der PLA/Silica- Komposite von Größe und

Konzentration der Silica ist durch dynamisch-mechanische Experimente und Kriech-Erhol-

Versuche ermittelt worden. Es wurde festgestellt, dass die Zugabe von Silica-Partikeln zur

PLA-Matrix die thermische Stabilität des PLA verbessert und dass kleinere Silikapartikel zu

höherer Stabilität führen. Oszillatorische Scherversuche im linear-viskoelastischen Bereich

zeigten eine deutliche Konzentrationsabhängigkeit des Speichermoduls, des Verlustmoduls

und der komplexen Viskosität der PLA/Nanosilica-Komposite im Vergleich zu

PLA/Mikrosilica Komposite.

Der logarithmisch des Nullscherviskosität aller Verbundstoffe stieg linear mit der Zugabe von

Silica an, solange wenn die Konzentration unterhalb der rheologischen Perkolationsschwelle

lag und die Wachstumsrate war umgekehrt proportional zur Partikelgröße. Kriech-Erhol-

Versuche zeigten, dass hinsichtlich der Zugabe von Silica die elastischen Eigenschaften des

140 9. Summary (in German)

PLA empfindlicher sind als die viskosen Eigenschaften. Sogar für Mikrosilica wurde eine

bemerkenswerter Verbesserung der elastischen Eigenschaften bei niedrigen Silica-

Konzentration gefunden. Es wurde ein Modell entwickelt, um die Interaktion zwischen

Polymermatrix und Teilchen zu beschreiben. Wenn der durchschnittliche Abstand zwischen

den Teilchen weit oberhalb des GyrationsdurchmesserS der Polymermatrix liegt, werden die

rheologischen Eigenschaften nur von Teilchen-Polymer-Wechselwirkungen beeinflusst.

Wenn der durchschnittlichen Abstand zwischen den Teilchen hingegen unterhalb des

Gyrationsradius der Polymermatrix liegt, wird eine Siliciumdioxid-Netzwerkstruktur gebildet

und die Teilchen-Teilchen- und Teilchen-Polymer-Wechselwirkungen scheinen die

rheologischen Eigenschaften zu bestimmen.

Das zweite Thema dieser Arbeit le handelt die thermo-mechanischen und rheologischen

Eigenschaften der PLA/PMMA-Mischung. Das PLA/PMMA-Blendsystem ist eine typische

mischbare teilbkristalline/amorph Polymermischung mit Formgedächtnispotenzial und hat in

den letzten Jahren zunehmendes Interesse erlangt. Bei der Verwendung von PMMA in PLA

wurden ein breiter Glasübergang und eine erhöhte Glasübergangstemperatur 𝑇𝑔 mit Hilfe des

Lodge-McLeish Modells und DSC Messungen beobachtet. Die Verbreiterung des

Glasübergangs wird durch lokale, nanoskalige Heterogenitäten in der Mischung verursacht,

die mit der Selbst-Konzentration der Komponenten zusammenhängen. Der Grad der

molekularen Verschlaufung der Mischungen wurde auf Basis der oszillatorischen

rheologischen Messungen bestimmt und zeigte, dass ungleiche Ketten einfacher als gleiche

Ketten miteinander verschlingen und dass die Verschlaufungsdichte 𝑒 mit erhöhter PMMA-

Konzentration (bis zu 50%) zunahm, wobei eine 99% Rückstellung auf die ursprüngliche

Form erhalten wurde. Die Einflüsse der Recktemperatur, Reckgeschwindigkeit,

Gblendzusammensetzung und des Molekulargewichts auf die Form-Gedächtnisleistung von

PLA/PMMA-Blends wurden ebenfalls untersucht. Es wurde festgestellt, dass die

141

Formgedächtniseigenschaften von PLA/PMMA Blends einen erheblichen "Temperatur-

Gedächtnis-Effekt" aufweisen.

Der Formgedächtnismechanismus wird weiterhin durch die Durchführung von

Formgedächtnistests an PLA/PMMA-Blend-Folien bei den jeweiligen 𝑇𝑔 validiert. Es ist

offensichtlich, dass für die teilkristallinen Mischungen (PLA-reich) PLA-Kristallite und

molekulare Verschlaufungen physikalische Vernetzungen für das Formgedächtnis bieten,

während eine negative Wirkung auf das Formgedächtnis auf Grund der Kristallinität durch die

dehnungsinduzierte Kristallisation und das Abgleiten von Keffen zwischen kristallinen und

amorphen Bereichen zu Stande kommt. Im Gegensatz dazu zeigt das

Formrückgewinnungsverhältnis für die amorphen Blends (PMMA-reich) eine stark positiv

lineare Anslieg mit 𝑒 und die Verschlaufung des Netzwerks wird als einer der wichtigsten

Faktoren im Bezug auf die Formgedächtnisleistung angesehen.

Nanosilica-gefülltes PLA/PMMA (50/50) mit verschiedenen Silica-konzentrationen (2, 5, 10

wt%) wurden durch Schmelzmischen hergestellt. In diesem Abschnitt wurden die

Einflussfaktoren, wie beispielsweise Silica-Konzentration, die Verteilung der Nanosilica, die

spezifischen Wechselwirkungen und bevorzugte Adsorption zwischen Nano-Siliciumdioxid

und der Komponente, auf die thermo-mechanischen und rheologischen Eigenschaften von

PLA/PMMA-Blends systematisch untersucht. DSC-Versuche zeigen die Mischbarkeit von

PLA/PMMA/Silica-Nanokompositen im festen Zustand, und die Verwendung von Nanosilica

erhöht nicht nur die Glasübergangstemperatur, sondern erweitert auch die Breite des

Glasübergangs. Aufgrund der Selbst-Konzentration der Komponenten können lokale

nanoskalige Heterogenitäten in den mischbaren Blends vermutet werden, und die

Anwesenheit von Nanosilica erhöht die Konzentrationsschwankungen und die dynamische

Heterogenität in den PLA/PMMA-Blends. Eine deutliche "Krater"-Struktur ist in den

Bruchflächen der Blend-Nanokomposite zu beobachten. Im Zusammenhang mit den

142 9. Summary (in German)

Ergebnissen der SEM und rheologischen Messungen wurde vorhergesagt, dass PLA Moleküle

selektiv auf der Oberfläche von Nano Silica adsorbiert werden, und die bevorzugte

Adsorption von PLA veränderte die Mischungszusammensetzung in der "Krater"-Struktur

und der reinen Matrix. Darüber hinaus wurde die Phasentrennungstemperatur der gefüllten

PLA/PMMA-Blends im Vergleich zu den ungefüllten Mischungen verbessert , und es zeigte

sich, dass die Zugabe von Nanosilica die Phasenstabilität der PLA/PMMA-Blends verbessert.

Entsprechend der auf rheologischen Messungen basierenden Berechnungen wurde aufgrund

der Umverteilung von PLA und PMMA-Molekülen in der Masse und rund um die Silica-

Oberfläche ein linearer Anstieg der Verschlaufungsdichte mit steigendem Silica-Gehalt

erreicht. Schließlich ist der Einfluß der Silica-Nanopartikel auf die Formgedächtnisleistung

von PLA/PMMA-Blends untersucht worden. Biaxial gestreckte Folien wurden ebenfalls

hergestellt, um die Einflüsse des Streckungsverhältnisses auf die

Formgedächtniseigenschaften zu untersuchen.

10. Appendix

10.1 Reproducibility of rheological measurements

For rheological measurement, it is important to check the reproducibility of rheological

measurements for neat and filled polymers. Frequency sweeps and creep-recovery

experiments for neat PLA and PLA with 2.8 vol. % nanosilica are used to check the

reproducibility of the rheological measurement in the linear region deformation.

Figure 10.1 The oscillatory frequency sweep curves of neat PLA and PLA/2.8 vol. % silica

OX50 nanocomposites measured at 180 °C.

For the rheological measurements in this work, at least three samples are used for each test.

As shown in Figure 10.1, the data of the storage modulus, loss modulus and complex

viscosity exhibit excellent reproducibility of neat PLA and PLA/silica nanocomposites. The

deviations between the results of two individual samples are less than 10%, indicating the

high reproducibility of oscillatory frequency sweeps. In addition, the creep-recovery

experiments also show excellent reproducibility, as shown in Figure 10.2.

144 10 Appendix

Figure 10.2 The creep-recovery curves of neat PLA and PLA/2.8 vol. % silica OX50

nanocomposites measured at 180 °C.

10.2 The melt density of PLA and PMMA at 200 °C

In order to calculate the molecular entanglement of PLA/PMMA blends in the molten state,

the melt density of PLA and PMMA should be measured. In this work, the melt flow rate

(MVR) at per10 min was measured by melt flow indexer (MI-4, Göttfert, Germany), and then

the samples were weighted. The melt density can be calculated by the ratio of MVR and the

mean weight per 10 min.

Table 10.1 The melt flow index of PLA and PMMA measured at 200 °C.

Waiting

time

(min)

MVR

(cm3/10min)

Mean

weight

(g/10min)

Density

(g/cm3)

PLA

200 °C, 2.16 Kg 5 4.06 4.54 1.12

200 °C, 2.16 Kg 10 4.83 5.46 1.13

200 °C, 2.16 Kg 20 4.64 5.20 1.12

PMMA

200 °C, 3.8 Kg 5 2.17 2.45 1.13

200 °C, 3.8 Kg 10 1.99 2.25 1.13

200 °C, 3.8 Kg 20 2.05 2.32 1.13

145

10.3 Thermogravimetric analysis (TGA) of nanocomposites

The thermal decomposition of neat PLA and silica particles was investigated as a function of

temperature under N2 atmosphere. As shown in Figure 10.3a, the onset degradation

temperature for neat PLA is around 300 °C, and that for silica particles are far above 400 °C.

Therefore, the chosen processing temperature (180 °C) for is below the thermal degradation

temperature of all the compositions. On the other hand, there is no change of weight can be

observed below 100 °C, suggesting that the drying process has removed the moisture of the

samples.

Figure 10.3 TGA scans of dried PLA and silica particles. The samples were heated at

5 °C/min from 20 °C to 500 °C under N2 atmosphere.

A comparative TGA of neat PLA and its composites with 2.8 vol. % silica is shown in Figure

10.3b. It is evident that the onset degradation temperature of the composites is larger than that

of neat PLA, indicating the PLA/silica composites have better thermal stability in comparison

with neat PLA. This enhancement may result from the interactions between organic and

inorganic phases [Fu and Qutubuddin (2001)]. The size of silica particle also exhibits impact

on the thermal stability, and silica with smaller particle size results in a larger enhancement of

the onset degradation temperature.

146 10 Appendix

In addition, the real silica concentration after sample preparation was also investigated by

TGA. As shown in Figure 10.3b, the real concentrations of the composites are close to the

desired silica contents. As the deviations between the real and the desired silica concentration

are very small, the values of the desired concentrations are used in this thesis.

Figure 10.4 TGA curves of PLA/PMMA 50/50 blends with different nanosilica contents at

the heating rate of 10 °C/min, recorded under nitrogen atmosphere.

The thermal stability properties of P/P/Si x nanocomposites was investigated as a function of

temperature, as shown in Figure 10.4. The unfilled PLA/PMMA blend shows the initial

degradation at ca. 290 °C, and this blend almost fully decomposed at 500 °C. In contrast to

unfilled PLA/PMMA blend, the initial degradation temperature of P/P/Si 2 is around 298 °C,

while that for P/P/Si 10 is at ca. 304 °C. All the mixtures displayed the residue of degradation

at 500 °C, and difference of residue is attributed to the different silica contents. Therefore, it

can be concluded that the presence of nanosilica improve the thermal stability of PLA/PMMA

blends.

147

10.4 The stress-strain curves of semi-crystalline polymers during cold or hot-

deformation

According to our previous study, the typical stress-strain curves of semi-crystalline polymers

during cold or hot-deformation can be conclude as shown in Figure 10.5. When the samples

are stretched below 𝑇𝑔, a very linear stress-strain relationship up to a well-defined yield point

can be observed. This linear portion of the curve corresponds to the elastic region and its

slope is the elasticity modulus [Besson et al. (2009)]. After the yield point, the stress

decreases slightly and then a strain hardening behavior occurs as deformation continues.

However, different stress-strain curves can be obtained with the increase of deformation

temperature [Guo-Zheng (2013)].

Figure 10.5 Stress-strain curves of semi-crystalline polymers during cold or hot-deformation

within relatively small strain.

When the films are stretched around 𝑇𝑔, a constant flow stress could be reached after the

elastic region deformation. In this case, the free chains in the amorphous phase work as

switching phase. For semi-crystalline polymer, strain-induced crystallization will result in a

plastic deformation in this region. Therefore, the strain in this region is a combination of

elastic and plastic deformation. There is no strain-hardening occurred due to the relatively

small deformation.

148 10 Appendix

The third type is when the samples are stretched at temperatures far above 𝑇𝑔. A constant flow

stress could be observed after a nonlinear stress-strain region. Crystalline grains are formed in

the nonlinear region, and the following constant stress is a dynamic equilibrium between the

recrystallization and stress relaxation induced by high temperature.

The stress-strain curves of the stretched films could be used to predict the following shape

memory performances. The stress relaxation behavior during the stretching can improve the

shape fixing ratio but reduce the shape recovery ratio. Moreover, the recrystallization and

disentanglement behavior during the stretching process would induce an irreversible plastic

deformation, which could significantly reduce the shape recovery ratio.

Abbreviations and symbols

PLA

PMMA

SiO2

Silica 300

Silica OX50

Silica 63

P/P/Si

P/20P

PP

PE

PVDF

POM

SEM

DSC

TGA

FTIR

SEC

DMTA

BET

THF

wt%

vol. %

TTS

Polylactide

Poly(methyl methacrylate)

Silica

AEROSIL® 300

AEROSIL® OX50

TIXOSIL 63

PLA50%/PMMA50%/silica 300

PLA80%/PMMA20%

Polypropylene

Polyethylene

Polyvinylidenfluorid

Polyoxymethylene

Scanning Electron Microscopy

Differential scanning calorimetry

Thermogravimetric analysis

Fourier transform infrared spectroscopy

Size exclusion chromatography

Dynamic mechanical thermal analysis

Brunauer–Emmett–Teller

Tetrahydrofurane

Weight fraction in %

Volume fraction in %

Time-temperature superposition

150 Abbreviations and symbols

Molar mass

Weight average molar mass

Number average molar mass

Entanglement average molar mass

Critical molar mass

Polydispersity

Activation energy

Glass transition temperature

Cold crystallization peak

Melting temperature

-transition temperature

Density

Density of amorphous phase

Radius of gyration

Average primary particle size

Inter-particle distance

Specific surface area

Crystallinity

Melting enthalpy

Content in the blend

Storage modulus

Loss modulus

Complex modulus

Phase angle

Tangent of the phase angle

Complex viscosity

Zero shear viscosity

Angular frequency

𝑀

𝑀𝑤

𝑀𝑛

𝑀𝑒

𝑀𝑐

𝑀𝑤/𝑀𝑛

𝐸𝑎

𝑇𝑔

𝑇𝑐

𝑇𝑚

𝑇

𝑎

𝑅𝑔

𝑑

𝑋𝑐

𝐻𝑓

𝑤

𝐺′

𝐺′′

𝐺∗(𝜔)

𝑡𝑎𝑛

𝜂∗(𝜔)

𝜂0

𝜔

D

SSA

151

𝑡𝑐𝑟

𝛾(𝑡𝑐𝑟)

𝐽𝑐𝑟(𝑡𝑐𝑟)

𝜓(𝑡𝑐𝑟)

𝐽0

𝜏0

𝐽𝑟(𝑡𝑟)

𝐽𝑒0

𝑅𝑓

𝑅𝑟

𝐺𝑁0

𝑅

𝑇

𝑒

𝑀𝑒

𝐺𝑋

𝐽𝑁0

γ

φ𝑐

Creep time

Time-dependent deformation

Creep compliance

Creep function

Instantaneous elastic compliance

Creep stress

Recoverable compliance

Steady-state recoverable compliance

Shape fixing ratio

Shape recovery ratio

Plateau modulus

Gas constant

Absolute temperature

Entanglement density

Entanglement molar mass

Crossover modulus

Plateau compliance

Strain

Rheological percolation threshold

References

Abbasi Moud, A., A. Javadi, H. Nazockdast, A. Fathi and V. Altstaedt (2015). "Effect of dispersion

and selective localization of carbon nanotubes on rheology and electrical conductivity of polyamide 6

(PA6), Polypropylene (PP), and PA6/PP nanocomposites." Journal of Polymer Science Part B:

Polymer Physics 53(5): 368-378.

Agrawal, C., D. Huang, J. Schmitz and K. Athanasiou (1997). "Elevated temperature degradation of a

50: 50 copolymer of PLA-PGA." Tissue engineering 3(4): 345-352.

Asakura, S. and F. Oosawa (1958). "Interaction between particles suspended in solutions of

macromolecules." Journal of Polymer Science 33(126): 183-192.

Atalla, R. (1999). The individual structures of native celluloses. Proceedings of the 10th International

Symposium on Wood and Pulping Chemistry, Main Symposium.

Auras, R., B. Harte and S. Selke (2004). "An overview of polylactides as packaging materials."

Macromol Biosci 4: 835-864.

Auras, R., B. Harte and S. Selke (2004). "An overview of polylactides as packaging materials."

Macromolecular bioscience 4(9): 835-864.

Auras, R. A., B. Harte, S. Selke and R. Hernandez (2003). "Mechanical, physical, and barrier

properties of poly (lactide) films." Journal of Plastic Film and Sheeting 19(2): 123-135.

Auras, R. A., S. P. Singh and J. J. Singh (2005). "Evaluation of oriented poly (lactide) polymers vs.

existing PET and oriented PS for fresh food service containers." Packaging technology and science

18(4): 207-216.

Bakar, N. F. A., R. Anzai and M. Horio (2009). "Direct measurement of particle–particle interaction

using micro particle interaction analyzer (MPIA)." Advanced Powder Technology 20(5): 455-463.

Bar-Yam, Y. (1997). Dynamics of complex systems, Addison-Wesley Reading, MA.

Behl, M. and A. Lendlein (2007). "Shape-memory polymers." Materials today 10(4): 20-28.

Behl, M., U. Ridder, Y. Feng, S. Kelch and A. Lendlein (2009). "Shape-memory capability of binary

multiblock copolymer blends with hard and switching domains provided by different components."

Soft Matter 5(3): 676–684.

Bellin, I., S. Kelch and A. Lendlein (2007). "Dual-shape properties of triple-shape polymer networks

with crystallizable network segments and grafted side chains." Journal of Materials Chemistry 17(28):

2885–2891.

153

Besson, J., G. Cailletaud, J.-L. Chaboche and S. Forest (2009). Non-linear mechanics of materials,

Springer Science & Business Media.

Bhattacharya, S., R. Gupta and M. Kamal (2008). Polymeric nanocomposites theory and practice, Carl

Hanser Publishers.

Booth, C. J., M. Kindinger, H. R. McKenzie, J. Handcock, A. V. Bray and G. W. Beall (2006).

"Copolyterephthalates containing tetramethylcyclobutane with impact and ballistic properties greater

than bisphenol A polycarbonate." Polymer 47(18): 6398-6405.

Callan, J., W. Hess and C. Scott (1971). "Elastomer blends. Compatibility and relative response to

fillers." Rubber Chemistry and Technology 44(3): 814-837.

Campo, C. J. and P. T. Mather (2005). "PVDF: PMMA shape memory blends: effect of short carbon

fiber addition." Polymeric Materials Science and Engineering 93: 933-934.

Capt, L., M. Kamal, H. Münstedt, K. Stopperka and J. Sänze (2001). "Morphology Development

during Biaxial Stretching of Polypropylene Films." Tc (C) 117: 112.111.

Carlson, D., L. Nie, R. Narayan and P. Dubois (1999). "Maleation of polylactide (PLA) by reactive

extrusion." Journal of applied polymer science 72(4): 477-485.

Carreau, P. J., D. De Kee and R. P. Chhabra (1997). Rheology of polymeric systems: principles and

applications, Hanser Publishers Munich.

Cassagnau, P. (2008). "Melt rheology of organoclay and fumed silica nanocomposites." Polymer 49:

2183-2196.

Chalmers, J. M. and R. J. Meier (2008). Molecular characterization and analysis of polymers, Elsevier.

Chang, Y.-W. (2012). "Shape Memory Polymer Blends." Functional Polymer Blends: Synthesis,

Properties, and Performance: 127.

Chung, H.-j., K. Ohno, T. Fukuda and R. J. Composto (2007). "Internal phase separation drives

dewetting in polymer blend and nanocomposite films." Macromolecules 40(2): 384-388.

Chung, H.-J., A. Taubert, R. Deshmukh and R. J. Composto (2004). "Mobile nanoparticles and their

effect on phase separation dynamics in thin-film polymer blends." EPL (Europhysics Letters) 68(2):

219.

Cooper‐White, J. J. and M. E. Mackay (1999). "Rheological properties of poly (lactides). Effect of

molecular weight and temperature on the viscoelasticity of poly (l‐lactic acid)." Journal of Polymer

Science Part B: Polymer Physics 37(15): 1803-1814.

154 Acknowledgements

Damm, C., H. Münstedt and A. Rösch (2008). "The antimicrobial efficacy of polyamide 6/silver-nano-

and microcomposites." Materials Chemistry and Physics 108(1): 61-66.

De Gennes, P.-G. (1979). Scaling concepts in polymer physics, Cornell university press.

Dealy, J. M. and R. G. Larson (2006). "Structure and rheology of molten polymers." Hanser, Munich.

Des Cloizeaux, J. (1988). "Double reptation vs. simple reptation in polymer melts." EPL (Europhysics

Letters) 5(5): 437.

Doi, M. and S. F. Edwards (1986). The theory of polymer dynamics, Clarendon Press Oxford.

Dorgan, J. R., J. Janzen, M. P. Clayton, S. B. Hait and D. M. Knauss (2005). "Melt rheology of

variable L-content poly (lactic acid)." Journal of Rheology (1978-present) 49(3): 607-619.

Dorgan, J. R., H. Lehermeier and M. Mang (2000). "Thermal and rheological properties of

commercial-grade poly (lactic acid) s." Journal of Polymers and the Environment 8(1): 1-9.

Dorgan, J. R., J. S. Williams and D. N. Lewis (1999). "Melt rheology of poly (lactic acid):

Entanglement and chain architecture effects." Journal of Rheology (1978-present) 43(5): 1141-1155.

Edwards, S. F. (1986). "The theory of polymer dynamics."

Eguiburu, J., J. Iruin, M. Fernandez-Berridi and J. San Roman (1998). "Blends of amorphous and

crystalline polylactides with poly (methyl methacrylate) and poly (methyl acrylate): a miscibility

study." Polymer 39(26): 6891-6897.

Elias, L., F. Fenouillot, J.-C. Majesté and P. Cassagnau (2007). "Morphology and rheology of

immiscible polymer blends filled with silica nanoparticles." Polymer 48(20): 6029-6040.

Es‐Haghi, S. S., A. Yousefi and A. Oromiehie (2007). "Thermorheological complexity of poly (methyl

methacrylate)/poly (vinylidene fluoride) miscible polymer blend: Terminal and segmental levels."

Journal of Polymer Science Part B: Polymer Physics 45(20): 2860-2870.

Eslami, H., M. Grmela and M. Bousmina (2009). "Structure build‐up at rest in polymer

nanocomposites: Flow reversal experiments." Journal of Polymer Science Part B: Polymer Physics

47(17): 1728-1741.

Fengkui Li, Xian Zhang, Jianan Hou, Mao Xu, Xiaolie Luo, Dezhu Ma and B. K. Kim. (1997).

"Studies on thermally stimulated shape memory effect of segmented polyurethanes." Journal of

Applied Polymer Science 64(8): 1511-1516.

155

Fenouillot, F., P. Cassagnau and J.-C. Majesté (2009). "Uneven distribution of nanoparticles in

immiscible fluids: morphology development in polymer blends." Polymer 50(6): 1333-1350.

Ferry, J. D. (1980). Viscoelastic properties of polymers, John Wiley & Sons.

Fesko, D. and N. Tschoegl (1971). Time‐temperature superposition in thermorheologically complex

materials. Journal of Polymer Science Part C: Polymer Symposia, Wiley Online Library.

Fetters, L., D. Lohse, D. Richter, T. Witten and A. Zirkel (1994). "Connection between polymer

molecular weight, density, chain dimensions, and melt viscoelastic properties." Macromolecules

27(17): 4639-4647.

Flory, P. and M. Volkenstein (1969). Statistical mechanics of chain molecules, Wiley Online Library.

Fu, S.-Y., X.-Q. Feng, B. Lauke and Y.-W. Mai (2008). "Effects of particle size, particle/matrix

interface adhesion and particle loading on mechanical properties of particulate–polymer composites."

Composites Part B: Engineering 39(6): 933-961.

Fu, X. and S. Qutubuddin (2001). "Polymer–clay nanocomposites: exfoliation of organophilic

montmorillonite nanolayers in polystyrene." Polymer 42(2): 807-813.

Gajria, A. M., V. Dave, R. A. Gross and S. P. McCarthy (1996). "Miscibility and biodegradability of

blends of poly (lactic acid) and poly (vinyl acetate)." Polymer 37(3): 437-444.

Garlotta, D. (2001). "A literature review of poly (lactic acid)." Journal of Polymers and the

Environment 9(2): 63-84.

Garlotta, D. (2001). "A Literature Review of Poly(Lactic Acid)." Journal of Polymers and the

Environment 9: 63-84.

Gharachorlou, A. and F. Goharpey (2008). "Rheologically determined phase behavior of LCST blends

in the presence of spherical nanoparticles." Macromolecules 41(9): 3276-3283.

Ginzburg, V. V. (2005). "Influence of nanoparticles on miscibility of polymer blends. A simple

theory." Macromolecules 38(6): 2362-2367.

Goncalves, G., M. T. Portoles, C. Ramirez-Santillan, M. Vallet-Regi, A. P. Serro, J. Gracio and P. A.

Marques (2013). "Evaluation of the in vitro biocompatibility of PMMA/high-load HA/carbon

nanostructures bone cement formulations." J Mater Sci Mater Med 24(12): 2787-2796.

Graessley, W. W. (1965). "Molecular entanglement theory of flow behavior in amorphous polymers."

The Journal of Chemical Physics 43(8): 2696-2703.


Graessley, W. W. (1980). "Some phenomenological consequences of the Doi–Edwards theory of

viscoelasticity." Journal of Polymer Science: Polymer Physics Edition 18(1): 27-34.

Guo-Zheng, Q. (2013). Characterization for Dynamic Recrystallization Kinetics Based on Stress-

Strain Curves, INTECH Open Access Publisher.

Haley, J. C. and T. P. Lodge (2004). "Failure of time-temperature superposition in dilute miscible

polymer blends." Colloid and Polymer Science 282(8): 793-801.

Hamaker, H. (1937). "The London—van der Waals attraction between spherical particles." physica

4(10): 1058-1072.

Hamielec, A. E. and H. Tobita (1992). "Polymerization processes." Ullmann's Encyclopedia of

Industrial Chemistry.

Han, C. D. (2007). Rheology and Processing of Polymeric Materials: Polymer Processing, Oxford

University Press, USA.

Hays, D., D. Rimai and L. Sharpe (1996). "Advances in Particle Adhesion." Gordon and Breach

Publishers, Amsterdam.

He, C., X. Zhuang, Z. Tang, H. Tian and X. Chen (2012). "Stimuli‐Sensitive Synthetic Polypeptide‐Based Materials for Drug and Gene Delivery." Advanced healthcare materials 1(1): 48-78.

Hoffmann, B., C. Dietrich, R. Thomann, C. Friedrich and R. Mülhaupt (2000). "Morphology and

rheology of polystyrene nanocomposites based upon organoclay." Macromolecular Rapid

Communications 21(1): 57-61.

Holland, B. and J. Hay (2002). "The effect of polymerisation conditions on the kinetics and

mechanisms of thermal degradation of PMMA." Polymer degradation and stability 77(3): 435-439.

Hollander, A. P. and P. V. Hatton (2004). Biopolymer methods in tissue engineering, Springer.

Hu, J., Y. Zhu, H. Huang and J. Lu (2012). "Recent advances in shape–memory polymers: Structure,

mechanism, functionality, modeling and applications." Progress in Polymer Science 37(12): 1720-

1763.

Huang, C.-L., Y.-C. Chen, T.-J. Hsiao, J.-C. Tsai and C. Wang (2011). "Effect of tacticity on

viscoelastic properties of polystyrene." Macromolecules 44(15): 6155-6161.

Huang, S., H. Li, S. Jiang, X. Chen and L. An (2011). "Crystal structure and morphology influenced

by shear effect of poly (L-lactide) and its melting behavior revealed by WAXD, DSC and in-situ

POM." Polymer 52(15): 3478-3487.

157

Huang, Y., S. Jiang, G. Li and D. Chen (2005). "Effect of fillers on the phase stability of binary

polymer blends: A dynamic shear rheology study." Acta materialia 53(19): 5117-5124.

Hussain, F., M. Hojjati, M. Okamoto and R. E. Gorga (2006). "Review article: polymer-matrix

nanocomposites, processing, manufacturing, and application: an overview." Journal of composite

materials 40(17): 1511-1575.

Jamshidi, K., S.-H. Hyon and Y. Ikada (1988). "Thermal characterization of polylactides." Polymer

29(12): 2229-2234.

Jeon, H., A. Nakatani, C. Han and R. Colby (2000). "Melt rheology of lower critical solution

temperature polybutadiene/polyisoprene blends." Macromolecules 33(26): 9732-9739.

Ji, G., F. Clement and E. Giannelis (2000). Nanofiller Modification of Phase Stability in PS/PMMA

Blends. MRS Proceedings, Cambridge Univ Press.

John, R. D., L. Hans and M. Michael (2000). "Thermal and rheological properties of commercial-

grade poly(lactic acid)s." Journal of Polymers and the Environment 8(1): 1-9.

Jordan, J., J. Spowart, M. Kendall, B. Woodworth and C. Siviour (2014). "Mechanics of particulate

composites with glassy polymer binders in compression." Philosophical Transactions of the Royal

Society A: Mathematical, Physical and Engineering Sciences 372(2015): 20130215.

Jung, Y. C., H. J. Yoo, Y. A. Kim, J. W. Cho and M. Endo (2010). "Electroactive shape memory

performance of polyurethane composite having homogeneously dispersed and covalently crosslinked

carbon nanotubes." Carbon 48(5): 1598-1603.

Kapnistos, M., A. Hinrichs, D. Vlassopoulos, S. Anastasiadis, A. Stammer and B. Wolf (1996).

"Rheology of a lower critical solution temperature binary polymer blend in the homogeneous, phase-

separated, and transitional regimes." Macromolecules 29(22): 7155-7163.

Katsikis, N., F. Zahradnik, A. Helmschrott, H. Münstedt and A. Vital (2007). "Thermal stability of

poly (methyl methacrylate)/silica nano-and microcomposites as investigated by dynamic-mechanical

experiments." Polymer Degradation and Stability 92(11): 1966-1976.

Kausch, H.-H. (1987). Polymer fracture, Springer Verlag.

Kourki, H. and M. H. N. Famili (2012). "Particle sedimentation: effect of polymer concentration on

particle–particle interaction." Powder Technology 221: 137-143.

Krishnamoorti, R. and E. P. Giannelis (1997). "Rheology of end-tethered polymer layered silicate

nanocomposites." Macromolecules 30(14): 4097-4102.


Krishnamoorti, R., R. A. Vaia and E. P. Giannelis (1996). "Structure and dynamics of polymer-layered

silicate nanocomposites." Chemistry of Materials 8(8): 1728-1734.

Lamnawar, K., M. Bousmina and A. Maazouz (2011). "2D Encapsulation in multiphase polymers:

Role of viscoelastic, geometrical and interfacial properties." Macromolecules 45(1): 441-454.

Lee, M. H., C. H. Dan, J. H. Kim, J. Cha, S. Kim, Y. Hwang and C. H. Lee (2006). "Effect of clay on

the morphology and properties of PMMA/poly (styrene-co-acrylonitrile)/clay nanocomposites

prepared by melt mixing." Polymer 47(12): 4359-4369.

Lendlein, A., A. M. Schmidt and R. Langer (2001). "AB-polymer networks based on oligo(epsilon-

caprolactone) segments showing shape-memory properties." Proc Natl Acad Sci U S A 98(3): 842-847.

Lendlein, A., A. M. Schmidt, M. Schroeter and R. Langer (2005). "Shape-memory polymer networks

from oligo(?-caprolactone)dimethacrylates." Journal of Polymer Science Part A: Polymer Chemistry

43(7): 1369-1381.

Lendlein, A., A. M. Schmidt, M. Schroeter and R. Langer (2005). "Shape-memory polymer networks

from oligo(ϵ-caprolactone)dimethacrylates." Journal of Polymer Science Part A: Polymer Chemistry

43(7): 1369-1381.

Li, X., T. Liu, Y. Wang, Y. Pan, Z. Zheng, X. Ding and Y. Peng (2014). "Shape memory behavior and

mechanism of poly(methyl methacrylate) polymer networks in the presence of star poly(ethylene

glycol)." RSC Advances 4(37): 19273.

Li, Y., C. Han, J. Bian, L. Han, L. Dong and G. Gao (2012). "Rheology and biodegradation of

polylactide/silica nanocomposites." Polymer Composites 33(10): 1719-1727.

Lim, L.-T., R. Auras and M. Rubino (2008). "Processing technologies for poly (lactic acid)." Progress

in polymer science 33(8): 820-852.

Lipatov, Y. S. (2002). "Polymer blends and interpenetrating polymer networks at the interface with

solids." Progress in Polymer Science 27(9): 1721-1801.

Lipatov, Y. S. (2006). "Phase separation in filled polymer blends." Journal of Macromolecular Science,

Part B 45(5): 871-888.

Lipatov, Y. S. and T. T. Alekseeva (2007). Phase-separated interpenetrating polymer networks,

Springer.

Lipatov, Y. S., A. Nesterov, T. Ignatova and D. Nesterov (2002). "Effect of polymer–filler surface

interactions on the phase separation in polymer blends." Polymer 43(3): 875-880.

159

Liu, C., J. He, E. Van Ruymbeke, R. Keunings and C. Bailly (2006). "Evaluation of different methods

for the determination of the plateau modulus and the entanglement molecular weight." Polymer 47(13):

4461-4479.

Liu, C., H. Qin and P. Mather (2007). "Review of progress in shape-memory polymers." Journal of

Materials Chemistry 17(16): 1543-1558.

Liu, C., H. Qin and P. T. Mather (2007). "Review of progress in shape-memory polymers." Journal of

Materials Chemistry 17(16): 1543.

Liu, C., J. Wang and J. He (2002). "Rheological and thermal properties of m-LLDPE blends with m-

HDPE and LDPE." Polymer 43(13): 3811-3818.

Liu, G., C. Guan, H. Xia, F. Guo, X. Ding and Y. Peng (2006). "Novel Shape-Memory Polymer Based

on Hydrogen Bonding." Macromolecular Rapid Communications 27(14): 1100-1104.

Lloyd, A. W., R. G. Faragher and S. P. Denyer (2001). "Ocular biomaterials and implants."

Biomaterials 22(8): 769-785.

Lodge, T. P. and T. C. McLeish (2000). "Self-concentrations and effective glass transition

temperatures in polymer blends." Macromolecules 33(14): 5278-5284.

Luo, C. and J.-U. Sommer (2012). "Disentanglement of linear polymer chains toward unentangled

crystals." ACS Macro Letters 2(1): 31-34.

Luo, X. and P. T. Mather (2013). "Shape Memory Assisted Self-Healing Coating." ACS Macro Letters

2(2): 152-156.

Macosko, C. W. and R. G. Larson (1994). "Rheology: principles, measurements, and applications."

Mather, P. T., X. Luo and I. A. Rousseau (2009). "Shape memory polymer research." Annual Review

of Materials Research 39: 445-471.

Meijer, H., P. Lemstra and P. Elemans (1988). fL STRUCTURED POLYMER BLENDS. Macromol.

Symp.

Meister, J. (2000). Polymer modification: principles, techniques, and applications, CRC Press.

Menary, G., C. Tan, E. Harkin‐Jones, C. Armstrong and P. Martin (2012). "Biaxial deformation and

experimental study of PET at conditions applicable to stretch blow molding." Polymer Engineering &

Science 52(3): 671-688.


Meng, Q. and J. Hu (2009). "A review of shape memory polymer composites and blends." Composites

Part A: Applied Science and Manufacturing 40(11): 1661-1672.

Millich, F. and C. E. Carraher (1977). Interfacial Synthesis: Polymer applications and technology, M.

Dekker.

Münstedt, H., T. Köppl and C. Triebel (2010). "Viscous and elastic properties of poly (methyl

methacrylate) melts filled with silica nanoparticles." Polymer 51(1): 185-191.

Münstedt, H., T. Köppl and C. Triebel (2010). "Viscous and elastic properties of poly(methyl

methacrylate) melts filled with silica nanoparticles." Polymer 51: 185-191.

Murariu, M., A. Da Silva Ferreira, M. Alexandre and P. Dubois (2008). "Polylactide (PLA) designed

with desired end‐use properties: 1. PLA compositions with low molecular weight ester‐like

plasticizers and related performances." Polymers for Advanced Technologies 19(6): 636-646.

Nair, L. S. and C. T. Laurencin (2007). "Biodegradable polymers as biomaterials." Progress in

polymer science 32(8): 762-798.

Nampoothiri, K. M., N. R. Nair and R. P. John (2010). "An overview of the recent developments in

polylactide (PLA) research." Bioresource technology 101(22): 8493-8501.

Nesarikar, A. R. (1995). "Rheology of polymer blend liquid-liquid phase separation." Macromolecules

28(21): 7202-7207.

Ngai, K. and C. Roland (1993). "Chemical structure and intermolecular cooperativity: dielectric

relaxation results." Macromolecules 26(25): 6824-6830.

Nobile, M. R. and F. Cocchini (2001). "Evaluation of molecular weight distribution from dynamic

moduli." Rheologica acta 40(2): 111-119.

Nofar, M., A. Tabatabaei and C. B. Park (2013). "Effects of nano-/micro-sized additives on the

crystallization behaviors of PLA and PLA/CO< sub> 2</sub> mixtures." Polymer 54(9): 2382-2391.

Osman, M. A., A. Atallah, T. Schweizer and H. C. Ottinger (2004). "Particle–particle and particle-

matrix interactions in calcite filled high-density polyethylene—steady shear." Journal of Rheology 48:

1167-1184.

Ota, S. (1981). "Current status of irradiated heat-shrinkable tubing in Japan." Radiation Physics and

Chemistry (1977) 18(1): 81-87.

Pan, P., W. Kai, B. Zhu, T. Dong and Y. Inoue (2007). "Polymorphous crystallization and multiple

melting behavior of poly (L-lactide): molecular weight dependence." Macromolecules 40(19): 6898-

6905.

161

Panahi-Bazaz, M.-R., M. Zamani and B. Abazar (2009). "Hydrophilic acrylic versus PMMA

intraocular lens implantation in pediatric cataract surgery." Journal of ophthalmic & vision research

4(4): 201.

Pathak, J. A., S. K. Kumar and R. H. Colby (2004). "Miscible polymer blend dynamics: Double

reptation predictions of linear viscoelasticity in model blends of polyisoprene and poly (vinyl

ethylene)." Macromolecules 37(18): 6994-7000.

Paul, D. and J. Barlow (1979). "A brief review of polymer blend technology." Multiphase Polymers

176: 315-335.

Plazek, D. J. and I. Echeverrıa (2000). "Don’t cry for me Charlie Brown, or with compliance comes

comprehension." Journal of Rheology (1978-present) 44(4): 831-841.

Quesnel, D. J., R. S. Rimai and L. H. Sharpe (2002). Particle adhesion: applications and advances,

CRC Press.

Rahman, M. S., I. M. Al-Marhubi and A. Al-Mahrouqi (2007). "Measurement of glass transition

temperature by mechanical (DMTA), thermal (DSC and MDSC), water diffusion and density methods:

a comparison study." Chemical Physics Letters 440(4): 372-377.

Raquez, J.-M., Y. Habibi, M. Murariu and P. Dubois (2013). "Polylactide (PLA)-based

nanocomposites." Progress in Polymer Science 38(10): 1504-1542.

Ratna, D. and J. Karger-Kocsis (2008). "Recent advances in shape memory polymers and composites:

a review." Journal of Materials Science 43(1): 254-269.

Ray, S. S. and M. Okamoto (2003). "Polymer/layered silicate nanocomposites: a review from

preparation to processing." Progress in polymer science 28(11): 1539-1641.

Rhodes, W. (1981). "Agglomerate and Particle Size Effects on Sintering Yttria‐Stabilized Zirconia."

Journal of the American Ceramic Society 64(1): 19-22.

Robeson, L. M. (2007). "Polymer blends." Hanser, Munich: 109-210.

Roland, C. and K. Ngai (1991). "Dynamical heterogeneity in a miscible polymer blend."

Macromolecules 24(9): 2261-2265.

Roland, C. and K. Ngai (1993). Concentration fluctuations and segmental relaxation in miscible

polymer blends. Application of Scattering Methods to the Dynamics of Polymer Systems, Springer:

75-79.


Rostami, A., M. Masoomi, M. J. Fayazi and M. Vahdati (2015). "Role of multiwalled carbon

nanotubes (MWCNTs) on rheological, thermal and electrical properties of PC/ABS blend." RSC

Advances 5(41): 32880-32890.

Rouse Jr, P. E. (1953). "A theory of the linear viscoelastic properties of dilute solutions of coiling

polymers." The Journal of Chemical Physics 21(7): 1272-1280.

Saeidlou, S., M. A. Huneault, H. Li and C. B. Park (2012). "Poly (lactic acid) crystallization." Progress

in Polymer Science 37(12): 1657-1677.

Samuel, C., J. Cayuela, I. Barakat, A. J. Muller, J.-M. Raquez and P. Dubois (2013).

"Stereocomplexation of polylactide enhanced by poly (methyl methacrylate): improved processability

and thermomechanical properties of stereocomplexable polylactide-based materials." ACS applied

materials & interfaces 5(22): 11797-11807.

Samuel, C., J.-M. Raquez and P. Dubois (2013). "PLLA/PMMA blends: A shear-induced miscibility

with tunable morphologies and properties?" Polymer 54(15): 3931-3939.

Samuel, C. d., S. Barrau, J.-M. Lefebvre, J.-M. Raquez and P. Dubois (2014). "Designing Multiple-

Shape Memory Polymers with Miscible Polymer Blends: Evidence and Origins of a Triple-Shape

Memory Effect for Miscible PLLA/PMMA Blends." Macromolecules 47(19): 6791-6803.

Sanders, J. F. and J. D. Ferry (1969). "Polymer Entanglement Spacings Estimated from Integration of

the Loss Compliance." Macromolecules 2(4): 440-442.

Sarvestani, A. S. and C. R. Picu (2004). "Network model for the viscoelastic behavior of polymer

nanocomposites." Polymer 45(22): 7779-7790.

Sawyer, D. J. (2003). "Bioprocessing– no longer a field of dreams." Macromolecular Symposia 201:

271-282.

Shao, J., J. Sun, X. Bian, Y. Cui, Y. Zhou, G. Li and X. Chen (2013). "Modified PLA Homochiral

Crystallites Facilitated by the Confinement of PLA Stereocomplexes." Macromolecules 46(17): 6963-

6971.

Sharma, M., G. Madras and S. Bose (2014). "Cooperativity and structural relaxations in

PVDF/PMMA blends in the presence of MWNTs: an assessment through SAXS and dielectric

spectroscopy." Macromolecules 47(4): 1392-1402.

Sheth, M., R. A. Kumar, V. Davé, R. A. Gross and S. P. McCarthy (1997). "Biodegradable polymer

blends of poly (lactic acid) and poly (ethylene glycol)." Journal of Applied Polymer Science 66(8):

1495-1505.

163

Shi, P., R. g. Schach, E. Munch, H. l. n. Montes and F. o. Lequeux (2013). "Glass transition

distribution in miscible polymer blends: from calorimetry to rheology." Macromolecules 46(9): 3611-

3620.

Singh, S. and S. S. Ray (2007). "Polylactide based nanostructured biomaterials and their applications."

journal of Nanoscience and Nanotechnology 7(8): 2596-2615.

Spitalsky, Z., D. Tasis, K. Papagelis and C. Galiotis (2010). "Carbon nanotube–polymer composites:

chemistry, processing, mechanical and electrical properties." Progress in polymer science 35(3): 357-

401.

Struglinski, M. J. and W. W. Graessley (1985). "Effects of polydispersity on the linear viscoelastic

properties of entangled polymers. 1. Experimental observations for binary mixtures of linear

polybutadiene." Macromolecules 18(12): 2630-2643.

Sudesh, K. and T. Iwata (2008). "Sustainability of biobased and biodegradable plastics." CLEAN–Soil,

Air, Water 36(5‐6): 433-442.

Tadano, T., R. Zhu, Y. Muroga, T. Hoshi, D. Sasaki, S. Yano and T. Sawaguchi (2014). "A new

mechanism for the silica nanoparticle dispersion–agglomeration transition in a poly (methyl

methacrylate)/silica hybrid suspension." Polymer Journal 46(6): 342-348.

Tolaymat, T. M., A. M. El Badawy, A. Genaidy, K. G. Scheckel, T. P. Luxton and M. Suidan (2010).

"An evidence-based environmental perspective of manufactured silver nanoparticle in syntheses and

applications: a systematic review and critical appraisal of peer-reviewed scientific papers." Science of

the Total Environment 408(5): 999-1006.

Triebel, C., N. Katsikis, H. Stará and H. Münstedt (2010). "Investigations on the quality of dispersion

of nanofillers in poly (methyl methacrylate) composites by creep-recovery experiments." Journal of

Rheology (1978-present) 54(2): 407-420.

Triebel, C., P. Kunzelmann, M. Blankenburg and H. Münstedt (2011). "Elasticity of polystyrene melts

filled with silica nanoparticles: Influence of matrix polydispersity." Polymer 52(16): 3621-3626.

Triebel, C. and H. Münstedt (2011). "Temperature dependence of rheological properties of poly

(methyl methacrylate) filled with silica nanoparticles." Polymer 52(7): 1596-1602.

Triebel, C. and H. Münstedt (2011). "Temperature dependence of rheological properties of

poly(methyl methacrylate) filled with silica nanoparticles." Polymer 52(7): 1596-1602.

Triebel, C. K., P.; Blankenburg, M.; Münstedt, H. (2011). "Elasticity of polystyrene melts filled with

silica nanoparticles: Influence of matrix polydispersity." Polymer 52: 3621-3626.

Van Gurp, M. and J. Palmen (1998). "Time-temperature superposition for polymeric blends." Rheol.

Bull 67(1): 5-8.


Wang, A. and G. Li (2015). "Stress memory of a thermoset shape memory polymer." Journal of

Applied Polymer Science 132(24).

Wen, X., Y. Lin, C. Han, K. Zhang, X. Ran, Y. Li and L. Dong (2009). "Thermomechanical and

optical properties of biodegradable poly (L‐lactide)/silica nanocomposites by melt compounding."

Journal of applied polymer science 114(6): 3379-3388.

Wetton, R., W. MacKnight, J. Fried and F. Karasz (1978). "Compatibility of Poly (2, 6-dimethyl-1, 4-

phenylene oxide)(PPO)/Poly (styrene-co-4-chlorostyrene) Blends. 2. Dielectric Study of the Critical

Composition Region." Macromolecules 11(1): 158-165.

Wool, R. P. (1995). Polymer interfaces: structure and strength, Hanser.

Wu, D., L. Wu, Y. Sun and M. Zhang (2007). "Rheological properties and crystallization behavior of

multi-walled carbon nanotube/poly(ɛ-caprolactone) composites." Journal of Polymer Science Part B:

Polymer Physics 45: 3137-3147.

Wu, D., L. Wu, L. Wu and M. Zhang (2006). "Rheology and thermal stability of polylactide/clay

nanocomposites." Polymer Degradation and Stability 91: 3149-3155.

Wu, D., L. Wu, W. Zhou, Y. Sun and M. Zhang (2010). "Relations between the aspect ratio of carbon

nanotubes and the formation of percolation networks in biodegradable polylactide/carbon nanotube

composites." Journal of Polymer Science Part B: Polymer Physics 48(4): 479-489.

Wu, S. (1982). Polymer interface and adhesion, M. Dekker.

Wu, S. (1985). "Dynamic rheology and molecular weight distribution of insoluble polymers:

tetrafluoroethylene-hexafluoropropylene copolymers." Macromolecules 18(10): 2023-2030.

Wu, S. (1987). "Chain entanglement and melt viscosity of compatible polymer blends: poly (methyl

methacrylate) and poly (styrene-acrylonitrile)." Polymer 28(7): 1144-1148.

Wu, S. (1987). "Entanglement between dissimilar chains in compatible polymer blends: poly (methyl

methacrylate) and poly (vinylidene fluoride)." Journal of Polymer Science Part B: Polymer Physics

25(3): 557-566.

Wu, S. (1989). "Chain structure and entanglement." Journal of Polymer Science Part B: Polymer

Physics 27(4): 723-741.

Wu, S. and R. Beckerbauer (1992). "Effect of tacticity on chain entanglement in poly (methyl

methacrylate)." Polymer journal 24(12): 1437-1442.

Wu, X., W. Huang, Y. Zhao, Z. Ding, C. Tang and J. Zhang (2013). "Mechanisms of the Shape

Memory Effect in Polymeric Materials." Polymers 5(4): 1169-1202.

165

Xie, T. (2010). "Tunable polymer multi-shape memory effect." Nature 464(7286): 267-270.

Xie, T. (2011). "Recent advances in polymer shape memory." Polymer 52(22): 4985-5000.

Xu, H., S. Tang, L. Yang and W. Hou (2010). "Toughening of polycarbonate by core-shell latex

particles: Influence of particle size and spatial distribution on brittle-ductile transition." Journal of

Polymer Science Part B: Polymer Physics 48: 1970-1977.

Yan, S., J. Yin, J. Yang and X. Chen (2007). "Structural characteristics and thermal properties of

plasticized poly (L-lactide)-silica nanocomposites synthesized by sol–gel method." Materials Letters

61(13): 2683-2686.

Yin, Y., X. Zhang, Y. Song, S. de Vos, R. Wang, C. A. Joziasse, G. Liu and D. Wang (2015). "Effect

of nucleating agents on the strain-induced crystallization of poly (l-lactide)." Polymer 65: 223-232.

You, J., W. Dong, L. Zhao, X. Cao, J. Qiu, W. Sheng and Y. Li (2012). "Crystal orientation behavior

and shape-memory performance of poly(vinylidene fluoride)/acrylic copolymer blends." J Phys Chem

B 116(4): 1256-1264.

You, J., H. Fu, W. Dong, L. Zhao, X. Cao and Y. Li (2012). "Shape memory performance of

thermoplastic polyvinylidene fluoride/acrylic copolymer blends physically cross-linked by tiny

crystals." ACS applied materials & interfaces 4(9): 4825-4831.

You, J., H. Fu, W. Dong, L. Zhao, X. Cao and Y. Li (2012). "Shape memory performance of

thermoplastic polyvinylidene fluoride/acrylic copolymer blends physically cross-linked by tiny

crystals." ACS Appl Mater Interfaces 4(9): 4825-4831.

Zhang, G., J. Zhang, S. Wang and D. Shen (2003). "Miscibility and phase structure of binary blends of

polylactide and poly (methyl methacrylate)." Journal of Polymer Science Part B: Polymer Physics

41(1): 23-30.

Zhang, M. Q., M. Z. Rong and K. Friedrich (2004). Nanoparticle reinforced thermoplastic composites.

Encyclopedia of nanoscience and Nanotechnology, American Scientific Publishers. 7: 125-160.

Zhang, Y., B. Deng and Q. Liu (2014). "Viscoelastic behavior and crystallization property of poly

(lactic acid)/silica nanocomposite." Journal of Reinforced Plastics and Composites 33(9): 875-882.

Zhang, Y., M. Zuo, Y. Song, X. Yan and Q. Zheng (2015). "Dynamic rheology and dielectric

relaxation of poly (vinylidene fluoride)/poly (methyl methacrylate) blends." Composites Science and

Technology 106: 39-46.

Zou, H., S. Wu and J. Shen (2008). "Polymer/silica nanocomposites: preparation, characterization,

properties, and applications." Chem. Rev 108(9): 3893-3957.

Acknowledgements

This thesis resulted from my work as a PhD student at the Institute for Polymer Materials of

the Material Science department at the Friedrich-Alexander-University Erlangen-Nuremberg.

During my study in Erlangen, I have had wonderful time with my colleagues and friends.

Here I would like to thank everybody who has supported my work in the past four years.

First and foremost, I want to thank China Scholarship Council (CSC) for financial support of

my PhD study.

I would like express my sincere appreciation to my supervisors Prof. Schubert for giving me

this opportunity to pursue my PhD in LSP group. He always supported me very well in my

research with patience and encouragement. In the last few months of my PhD study, he also

provided financial support for my work.

I gratefully acknowledge my teacher Dr. Joachim Kaschta for his help and support. He is my

second supervisor of my PhD study. He provided me extensive advice and time for discussion

throughout the whole time working on this thesis. The every step of my work has gotten his

valuable support. I also learned a lot of fundamental knowledge from this project under the

guidance of Dr. Kaschta. Without his help I would not able to finish this project. I also want

to acknowledge Prof. Helmut Münstedt. His work about rheological experiments gives me a

lot of inspiration.

My further gratitude goes to my colleagues Xianhu Liu, Yamin Pan and Hao Wang. We

studied at the same college (Zhengzhou University) before we came to Germany. When I

have problems in my work, they always discuss with me and help me out. Moreover, Xianhu

and Yamin also revised this thesis.

167

Mathias Bechert and Peter Kunzelmann are very nice to me and give me lots of help. I

appreciate Mathias Bechert and Jie Xu for revising my summary in German.

I would like to thank my office colleagues Yaping Ding, Atheer Alaa Abdulhussein, Jie Xu

and Volker Achenbach for our good collaboration in a nice and friendly atmosphere.

I am grateful to Dr. Zdeněk Starý for teaching me to do the heat shrinkage test. Magdalena

Papp is very kind to me and she is thanked for teaching me to use SEM. Inge Herzer is

thanked for DSC and GPC test. Jennifer Reiser taught me to use FTIR and also helped to do

TGA test. Susanne Michler is thanked for ordering the materials for this project and helping

me for rheological and DMTA measurements. Karl and Marko Heyder are thanked for

teaching me to use the extruder and biaxial stretching machines.

I also want to thank my colleagues Michael Härth, Bastian Walter, Franz Lanyi, Florian Küng,

Andreas Ziegmann and Jonas Daenicke. It is great honor to work with them.

Finally, I want to express my deepest gratitude to my family. My parents, my younger sister

and brother give me constant encouragement and support for my study. My husband Jing Han

always accompany with me at my hard time. His love, patience, encouragement and

companionship helped me to complete this thesis successfully.

I love you, LSP. I love you, Germany. It is a very precious experience for me to study in this

great country. I will miss the life and people here forever.


List of Publication

1. Xiaoqiong Hao, Joachim Kaschta, Xianhu Liu, Dirk W. Schubert. Entanglement network

formed in miscible PLA/PMMA blends and its role in rheological and thermo-mechanical

properties of the blends. Polymer, Volume 80, 2 December 2015, Pages 38-45

2. Xiaoqiong Hao, Joachim Kaschta, Xianhu Liu, Yamin Pan, Dirk W. Schubert,

Intermolecular cooperativity and entanglement network in a miscible PLA/PMMA blend in

the presence of nano-silica. Polymer, Volume 82, 15 January 2016, Pages 57-65

3. Xiaoqiong Hao, Joachim Kaschta, Dirk W. Schubert. Viscous and elastic properties of

polylactide melts filled with silica particles: effect of particle size and concentration.

Composites Part B Engineering, Volume 89, 15 March 2016, Pages 44–53

4. Xianhu Liu, Kun Dai, Xiaoqiong Hao, Guoqiang Zheng, Chuntai Liu. Crystalline structure

of injection molded β-isotactic Polypropylene: analysis of the oriented shear zone, ACS

Applied Materials & Interfaces, 2013, 52 (34), 11996–12002.

rheological and thermo-mechanical properties of pla-based miscible blends … · 2016. 3. 29. ·...

Documents