design strategies for shape memory polymers · shape memory is an intrinsic property to all...

Available online at www.sciencedirect.com

Design strategies for shape memory polymersXiaofan Luo* and Patrick T Mather

Shape memory polymers (SMPs) are polymeric materials

capable of recovering from a ‘fixed’ temporary shape to a

‘memorized’ permanent shape upon exposure to an external

stimulus. Two structural elements are required for a polymer to

exhibit useful shape memory: a network structure that defines

the permanent shape (the ‘memory’), and a switching segment

that induces a significant change in the mobility of the network

chains. Four common strategies based on various chemical/

physical principles and with different advantages/

disadvantages have been established for the design and

preparation of SMPs. A new design strategy, based on the

concept of functional composite materials, allows for a greater

control over material properties and functions and has shown

great promise in designing SMPs for a wide variety of

applications.

Address

Department of Biomedical and Chemical Engineering, Syracuse

Biomaterials Institute, Syracuse University, Syracuse, NY 13244, USA

Corresponding author: Mather, Patrick T ([email protected])* Current address: Flow Polymers, LLC, 12819 Coit Rd, Cleveland, OH

44108, USA.

Current Opinion in Chemical Engineering 2013, 2:103–111

This review comes from a themed issue on Materials engineering

Edited by Thein Kyu

For a complete overview see the Issue and the Editorial

Available online 24th November 2012

2211-3398/$ – see front matter, # 2012 Elsevier Ltd. All rights

reserved.

http://dx.doi.org/10.1016/j.coche.2012.10.006

IntroductionShape memory polymers, or SMPs, are polymeric materials

that are capable of recovering from a ‘fixed’ temporary

shape to a ‘memorized’ permanent shape in a controlled

manner upon exposure to an external stimulus. Although

heat remains the ‘intrinsic’ stimulus, triggering shape

memory using other stimuli such as light, electric current,

magnetic field, and moisture, has also become possible.

The field of SMPs has been the subject of significant

research efforts in the past several years owing to increasing

amount of technological interests in this important class of

functional polymers. Many applications, ranging from

smart textiles, actuators, to medical devices have been

developed and new shape memory phenomena discovered

that have greatly extended both the fundamental under-

standing as well as the overall scope of SMPs. A number of

articles [1��,2,3��,4–7,8�,9–11,12�,13–17,18�,19,20] have

www.sciencedirect.com

appeared that provide excellent reviews of the progress

in SMPs spanning a range of emphases including

material compositions [1��,3��,7,9,11,12�], applications

[2,4,8�,10,13,14,16,17,19,20], new shape memory effects

[8�,18�], stimulus methods [5,9,17], and future challenges

[6].

The behavior of most SMPs can be described using the so

called ‘one-way shape memory cycle (1W-SMC)’.

Although some variations exist, a 1W-SMC consists

essentially of 4 steps (Figure 1). First (step 1), the

SMP is deformed at a temperature higher than its charac-

teristic transition temperature, Ttrans. The deformation is

elastic in nature and mainly leads to a reduction in

conformational entropy of the constituent network

chains. After cooling to a low temperature (step 2, below

Ttrans) while holding the deformation stress, the material

enters a more rigid state via either vitrification (rubber–glass transition) or crystallization, which leads to a sig-

nificantly reduced chain mobility that ‘freezes’ the

material in this entropically unfavored state. At the

macroscopic level the material ‘fixes’ the deformed,

temporary shape even after (step 3) the release of external

stress. Heating is finally applied (step 4) to the material

under a stress-free condition. By allowing the network

chains (with regained mobility) to return to their entro-

pically favored state, the material recovers from the

temporary to its permanent shape. It is noted here that,

although the result in Figure 1 was obtained from macro-

scopic (tensile) deformations, the same shape memory

phenomenon has also been demonstrated and increas-

ingly applied in microscopic, even nanometer-scale sys-

tems [21–26].

Structurally, two elements are required for a polymer to

exhibit shape memory:(a) a transition that induces a

significant change in the mobility of polymer chains

(usually manifested as a change in modulus), and (b)

an entropic ‘memory’ of its permanent shape, usually

through a permanent or semi-permanent network struc-

ture. As mentioned earlier, the most commonly used

transitions for SMPs are the glass–rubber transition and

the crystallization-melting transition. On the other hand,

the requisite network structure can be realized by either

covalent or non-covalent/physical crosslinks. Therefore

depending on the combination of transition type and

nature of the network, SMPs can be divided into four

main classes: (I) covalently crosslinked glassy thermosets,

(II) covalently crosslinked semi-crystalline networks,

(III) physically crosslinked glassy copolymers and blends,

and (IV) physically crosslinked semi-crystalline block

copolymers and blends [3��].


http://www.sciencedirect.com/science/journal/22113398/2/1




104 Materials engineering

Figure 1

0

20

40

60

80

100

0.00

0.05

0.10

0.15

0.200.25

10 20 30 40 50 60 70 80 90

Stre

ss (M

Pa)

Temperature (°C)

Cycle 1Cycle 2Cycle 3

*

(1)

(2)(3)

(4)

Str

ain

(%

)

Current Opinion in Chemical Engineering

Shape memory cycles (SMCs) for a Sylgard/PCL shape memory

elastomeric composite (SMEC, see text for more details of this material).

The material was thermally conditioned [72�,85] before testing. Three

consecutive cycles were performed and shown. The asterisk indicates

experimental start of a cycle.

One may realize from the discussion that these two

required structural elements exist widely in almost all

polymers. For example, all polymers possess at least one

thermal transition, the glass–rubber transition (semi-crys-

talline polymers have the additional melting transition).

Many polymers (e.g. thermosets) contain crosslinks; even

polymer chain entanglements can function as crosslinks at

some time scale depending on polymer’s molecular

weight. Indeed, some researchers may hold the opinion

that shape memory is an intrinsic property to all polymers.

While such an opinion is more semantic than anything

else, it is worth pointing out that the current research in

SMPs is less about passively discovering shape memory

effects in existing polymers, and more focused on actively

designing new materials with precisely controlled shape

memory properties.

Design strategies for shape memory polymersChemical crosslinking of a high Mw thermoplastic

polymer

The most straightforward strategy to prepare a SMP, at

least conceptually, is to take an existing high Mw thermo-

plastic polymer and chemically crosslink it. As mentioned

before, all polymers have at least one thermal transition

that can be used as the ‘switching mechanism’ for shape

memory. Chemical crosslinking introduces a network

structure that defines the permanent shape, or ‘memory’.

Two common crosslinking methods used to prepare


SMPs are (1) organic peroxides [27–29,30�,31–33] and

(2) high energy radiation [34–38]. In fact one of the

earliest SMPs was prepared this way (radiation cross-

linked polyethylene) and led to the invention of ‘heat-

shrinkable’ materials.

This method can be applied to both amorphous and semi-

crystalline polymers, leading to Class I and Class II SMPs,

respectively. However the crosslinking efficiency can

vary significantly among different polymers. Typically,

saturated polymers are less susceptible to free radical

crosslinking compared to unsaturated polymers, resulting

in incomplete crosslinking and low gel fractions

[27,31,32,37]. This can hurt the shape memory perform-

ance, leading to both low recovery and permanent defor-

mation. One possible solution is to physically blend the

polymer with an unsaturated species that functions as a

‘sensitizer’, before crosslinking. For example, Zhu et al.[36] blended poly(e-caprolactone) (PCL, a saturated poly-

mer) with small fractions of polymethylvinylsiloxane

(PMVS) before subjecting the system to gamma-ray

irradiation. The resulting materials showed a monotonic

increase in gel fraction with increasing amounts of PMVS

at identical radiation dosages. Voit et al. conducted quite

extensive studies on the impact of different types of

sensitizers [34,35] as well as different sensitizer lengths

[35] on the electron-beam crosslinking of poly(methyl

acrylate) (PMA). In general, the use of a sensitizer was

found to significantly lower the gelation dose and lead to

good shape memory properties.

One practical advantage of this approach is that it allows

the base polymer to be shaped by conventional thermo-

plastic processing methods such as extrusion and injec-

tion molding, followed by thermal (peroxide) or radiation

crosslinking. The main disadvantage of this approach is

its rather limited control over shape memory properties.

For a given SMP prepared under this approach, the

transition temperature (either Tm or Tg) is largely inher-

ited from the starting polymer and can only be adjusted in

a small range. Moreover, such adjustment would inevi-

tably change other properties. Possible side reactions (e.g.

main chain degradation) during the crosslinking process

must also be considered.

One-step polymerization of monomers/pre-polymers

and crosslinking agents

It is possible to prepare an SMP from the ‘bottom-up’ by

reacting properly selected monomers, reactive pre-polymers

and crosslinking agents, in which polymerization and

chemical crosslinking occur in a single step. The system

usually undergoes a sol–gel transition similar to many ther-

mosetting resins. This strategy can lead to much greater

control over shape memory and other material properties.

One of the most studied systems under this general

approach is the family of copolymer networks prepared


Design strategies for shape memory polymers Luo and Mather 105

from the free radical polymerization of acrylate/metha-

crylate monomers. Our group [39] first reported a series of

Tg-based (Class I) SMPs prepared from methyl

methacrylate (MMA), butyl methacrylate (BMA) and a

bi-functional crosslinking agent tetraethylene glycol

dimethacrylate (TEGDMA). The transition temperature

(Tg in this case) and rubbery modulus can be precisely

controlled by the MMA/BMA ratio and the amount of

TEGDMA, respectively. More extensive studies were

conducted by Ken Gall’s group, who investigated a

variety of acrylate/methacrylate monomers and crosslin-

kers and published a large body of data [40,41�,42–48]

useful for designing SMPs using these materials. Other

examples of Class I SMPs prepared by this approach

include epoxy-based SMPs [49–53], thiol-enephotopoly-

merized networks [54], thermosetting polyurethanes

[55,56], among others.

This approach can also be applied to Tm-based, Class II

SMPs. The main difference is that oftentimes a reactive

pre-polymer (typical Mw � several thousand g/mol) cor-

responding to the crystallizable switching segment is used

in addition to other monomers and/or crosslinking agents.

One of the early examples of SMPs prepared under this

approach was the free-radical polymerized co-network

based on PCL dimethacrylate and n-butyl acrylate

[57]. Again, SMPs following the same strategy but based

on a variety of other polymerization/crosslinking chem-

istries and crystallizable segments (including liquid crys-

talline segments [25,58�,59]) have been developed since

then.

Generally speaking, SMPs prepared under this approach

exhibit excellent shape memory properties (e.g. high

fixing and recovery ratios, good cycle life-time/stability)

owing to both the thermoset (permanent network) nature

of such SMPs and their well-defined structures down to

the molecular level. Control of shape memory properties

is reasonably easy, usually involving adjusting variables

such as monomer composition, pre-polymer Mw, and

crosslinker concentration and functionality. The biggest

disadvantage of this strategy may be constraints for pro-

cessing. Because of the thermosetting nature, many SMPs

exhibit relatively narrow processing windows (before the

gel time), and require processing techniques usually

relegated to those of coatings and adhesives.

One-step synthesis of phase-segregated block

copolymers

This strategy is similar to the previous one in that the

SMP is fundamentally designed at the molecular scale.

However the goal here is to yield a thermoplastic polymer

(rather than a thermoset) that can be processed using

more conventional plastics processing techniques. In

order to obtain shape memory, SMPs by this strategy

are usually phase-segregated block copolymers, with two

blocks exhibiting different transition temperatures. The


blocks with higher and lower transition temperatures are

sometimes referred to as the ‘hard’ and ‘soft’ segments,

respectively.

The most extensively studied SMPs prepared by this

strategy are shape memory polyurethanes (SMPUs)

[60�,61�,62,63], owing to the simplicity and versatility

of urethane chemistry compared to other polymerization

techniques, as well as the good availability of raw

materials (polyols and isocyanates). In SMPUs, soft and

hard segments form a multi-block structure. The hard

segment functions as physical crosslinks and defines the

permanent shape (‘memory’) whereas the soft segment

provides the switching mechanism for shape memory.

Depending on the selection of soft segment (glassy or

semi-crystalline), both Class III and Class IV SMPs can be

prepared. The hard segment can be glassy or semi-crystal-

line polymer segments with high Tg or Tm. A novel hard

segment explored in our group is Polyhedral Oligosilses-

quioxane (POSS), a nanostructured hybrid material with

an inorganic silica-oxygen cage functionalized with up to

8 pendent organic groups [64,65]. POSS can form crystal-

line nanodomains (with relatively high Tm’s) that when

used as the hard segment for SMPUs, gives excellent

rubbery elasticity and shape memory properties.

In general, SMPs by this strategy afford good control over

shape memory as well as other material properties. For a

given combination of soft/hard segments, the key vari-

ables are the ratio between the two blocks and their

molecular weights. However, owing to the thermoplastic

and physically crosslinked nature of these SMPs, the

shape memory performance (particularly recovery) is

often inferior to that of thermoset SMPs (Classes I and

II). Deviation from ideal entropic rubber and time-de-

pendent viscoelastic behavior can occur in the physically

crosslinked state, compromising both shape recovery and

cycle stability. Reasonable shape memory is achieved in

relatively narrow compositional windows [7]. The most

significant advantage, however, lies also in being thermo-

plastic, which allows for easy processing into different

permanent shapes and functional forms.

Direct blending of different polymers

Physically blending different thermoplastic polymers

(each with no or limited shape memory) to prepare blends

with shape memory properties represents another major

design strategy. The fundamental concept is to obtain

‘memory’ from one polymer and a switching mechanism

from the other. Following this concept, two different

approaches have been demonstrated.

As mentioned earlier, all polymers contain at least one

thermal transition. What many conventional thermoplas-

tics lack is an effective network structure when the

transition temperature is exceeded. Therefore, the first

approach is to blend in a second thermoplastic polymer



with a higher transition temperature (than the host/matrix

polymer) that functions as physical crosslinks for tem-

peratures between the two transitions. Based on this

concept, Liu and Mather [66] reported a Class III SMP

blend consisting of poly(vinyl acetate) (PVAc) and poly(-

lactic acid) (PLA). PVAc is an amorphous polymer with a

Tg of ca. 40 8C whereas PLA is a semi-crystalline polymer

with a high melting temperature of ca. 165 8C. PLA

crystals physically crosslink the PVAc and a well-defined

rubbery plateau is obtained when the blend is heated

between the Tg of PVAc and the Tm of PLA. Similarly,

Class IV SMPs can also be prepared by using a semi-

crystalline polymer as the low-transition component.

Examples include the poly(p-dioxanone) (PPDO)/PCL

blends reported by Behl et al. [67] and high-density

polyethylene (HDPE)/poly(ethylene terephthalate)

(PET) [68] blends studied by Li et al.

On the other hand, elastomers do possess the network

structure required for memory, but lack a useful switching

transition (since their Tg’s are typically sub-ambient)

needed for full shape memory. Thus, a second approach

is based on blending a polymer of desired Tg or Tm with an

elastomer. For example, Zhang et al. [69] prepared phase-

separated SMP blends composed of a styrene–butadiene–styrene (SBS) thermoplastic elastomer with a semi-crys-

talline PCL. A slight deviation of this approach (although

following the same basic concept) was presented by Weiss

et al. [70], who blended an elastomeric ionomer (sulfo-

Figure 2

Elastomeric Matrix Thermoplastic F

(a)

(c)

0 s 2 s

CH3

CH2CH 2CH 2CH 2CHCH3

SiOO

Cn

Shape memory elastomeric composites (SMECs). (a) Schematic illustration

morphology and (c) a series of photographs showing the recovery from a fi

80 8C.Reproduced with permission from Ref. [72�].


nated EPDM) with various low-Mw fatty acids and fatty

acid salts. The melting of these fatty acids and salts

constitute the transitions for shape memory.

Although conceptually simple, implementing the blending

strategy in reality can be complicated and challenging.

Blends from different polymers can vary significantly in

morphology, thermal and phase behavior, depending on a

large number of variables including miscibility, molecular

weights, specific interactions, among others. Factors such

as thermal history [66,71], interfacial strength [68], and

morphology [69] all have pronounced impact on shape

memory properties. Even more, it is often difficult to

control one material property without affecting others.

Nevertheless, this still represents an important design

strategy for SMPs.

New design strategies of SMPs

During the past several years, our group has been engaged

in developing new design strategies for SMPs that enable

good shape memory performance, easily tuned shape

memory behavior, good processability and cost-

economics for practical applications. The main achieve-

ment is a new strategy based on the concept of functional

composite materials. Below we highlight some key

examples of SMPs developed under this strategy.

The strategy was first implemented to prepare shape

memory elastomeric composites (SMECs) [72�]. This

ibers

(b)

4 s 8 s

2 - O n 10kV ×850 20 μm 20 40 SE 1


of the composite structure, (b) SEM image showing the bulk composite

xed, temporary shape to the permanent shape on a hot-plate at



material was designed to exhibit a two-phase morphology

in which semi-crystalline PCL exists as non-woven fab-

rics of microfibers evenly distributed in a continuous

silicone rubber (under the commercial name Sylgard

184) matrix (Figure 2A and B). None of the components

has useful shape memory on its own; however, by func-

tioning collectively, with Sylgard providing an entropic

network (‘memory’) and PCL serving as a Tm-based

switching segment, excellent shape memory performance

was observed (Figs. 1 and 2C). It should be noted that this

approach is fundamentally different from the direct

blending strategy outlined above. In contrast to direct

blending, the two components in SMECs are not blended

in a melt or solution state. Rather the material is prepared

by infiltrating an electrospun PCL mat with liquid Syl-

gard and curing the Sylgard below the Tm of PCL. There-

fore the morphology is pre-determined and not affected

by factors such as polymer miscibility, blending

Figure 3

Elastomer

Semi-crystalline/glassythermoplastic

Shape MemoryElastomeric Composites

(SMECs)

SMP or Elastomer


Shape Memory Assisted ShapeMemory (SMASH) Coatings

(a)

(c)Matrix

0 s 2 s

4 s 8 s

Δ

Schematic illustration of the new design strategy for SMPs based on the co

decoupled components (fibers and matrix), a variety of different properties

composites (SMECs), (b) triple-shape polymeric composites (TSPCs), (c) sh

conductive shape memory nanocomposites.Reproduced with permission fro


conditions, or thermal history. Unlike any previous

strategy, this composite design decouples the two func-

tional components (memory and switching) both physi-

cally and chemically, and allows a greater control of shape

memory polymer properties by manipulation of the

underlying components individually.

Following the same basic design strategy, triple-shape

polymeric composites (TSPCs) were developed upon

simple replacement of the rubber matrix (as in SMECs)

with an epoxy based, Class I SMP [73�]. The additional

transition from the matrix Tg, which can be easily con-

trolled via the monomer ratio in the epoxy formulation

with no effect on PCL Tm, enabled triple-shape memory

[74–76,77�,78–82]. As such, the composite demonstrated

an ability to fix two independent temporary shapes and

recover sequentially from the first to the second tempor-

ary shape, and eventually to the permanent shape upon

Fibers

SMP


Triple-ShapePolymeric Composite

(TSPCs)

SMP

Conductive Network(Carbon Nanofibers)

Electrically ConductiveShape Memory

Nanocomposites

0

0.0 0.5 1.0 1.5 2.0 2.5 3.0

102030R

eco

very

(%

)

Time (s)

405060708090

100110

(b)

(d)

25 °C 40 °C 80 °C


ncept of functional composites. By individual manipulation of the two

and functions can be realized, including (a) shape memory elastomeric

ape memory assisted self-healing (SMASH) coatings, and (d) electrically

m Refs. [72�,73�,86].



Figure 4

10 s 25 s

50 s 1140 sCurrent Opinion in Chemical Engineering

Photographs showing the shape recovery of a sponge/hydrogel composite in water at 0 8C. The hydrogel, a PEO–PPO–PEO tri-block copolymer,

exhibits LCST behavior in water. By cooling below the critical LCST temperature, the hydrogel transitions from a gel to a solution and enables

unprecedented, cooling-induced shape recovery as shown in the photographs.

Reprinted with permission from Ref. [88�].

continuous heating. The same SMP system was also

developed to function as self-healing coatings [83,84].

In addition to manipulating the matrix, one can also alter

the fiber phase to achieve novel SMPs such as Sylgard/

PVAc SMECs, by replacing the PCL fibers with PVAc

[85], and electrically conductive shape memory nanocom-

posites, by replacing the fiber phase with PAN-based

carbon nanofibers [86]. A illustrative summary of this

new design strategy is shown in Figure 3.

Table 1

Comparison of different design strategies for shape memory polymer

Design strategy Advantag

Chemical crosslinking of a

high Mw thermoplastic polymer

Conceptually simple; can us

polymers

One-step polymerization of

monomers/pre-polymers and

crosslinking agents

Good control over SM prope

One-step synthesis of

phase-segregated block copolymers

Good control over SM prope

processing methods

Direct blending of different polymers Conceptually simple; potenti

Fiber/matrix based

composite strategy

Widely applicable to a large

good control over SM prope

design flexibility


Very recently, work along similar lines has appeared from

various other groups. For example, Stone et al. [87]

fabricated ananocomposite by incorporating poly(vinyl

alcohol) (PVA) fibers into an elastomeric ethylene-

oxide/epichlorohydrin copolymer matrix. The material

exhibits water-responsiveness and decreases its modulus

by 2 orders of magnitude upon 10–15 min exposure to

water, which can be utilized for water-triggered shape

memory, although this subject was not explored yet by

s

es Disadvantages

e conventional Limited control over SM properties; can be

challenging to achieve high gel fraction and

control side reactions in certain polymer

systems

rties Limited processing methods

rties; flexibility in Resulting material often displays inferior SM

properties, especially shape recovery

ally easy to process Requires either strong interactions or

compatibilization to achieve good SM

properties; controlling the morphology can

be challenging

number of materials;

rties; large material

May require less conventional processing

methods



the authors. In a quite unique embodiment of this same

strategy, Wang et al. [88�] infiltrated a plastic sponge

(elastic owing to the porous structure, composition unspe-

cified) with a hydrogel to make a composite material. The

hydrogel, a polyethylene-polypropylene-polyethylene

(PEO–PPO–PEO) triblock copolymer, was selected

based on its well-known LCST behavior. For this com-

posite, at temperatures higher than the LCST critical

temperature, gelation occurs which can be used as a

mechanism to fix a temporary deformation of the material

(by resisting the elastic recovery of the sponge). At

temperatures below the critical temperature, the hydrogel

becomes a solution and can no longer carry stress, allow-

ing the shape recovery of the sponge to occur. Therefore

this innovative design enables unprecedented, cooling-

induced shape memory (Figure 4).

SummaryIn this article, we have briefly reviewed both common and

emergent design strategies for thermally responsive

SMPs. A summary of these strategies is presented in

Table 1. By design, our review is not comprehensive.

Instead, we hope that it can serve as basic guidance on

what strategy to choose when designing an appropriate

SMP for a specific application. The key factors to consider

when evaluating these strategies include: shape memory

performance, the degree of control over shape memory as

well as other material properties, processing complexities,

and raw material availability/cost. With the rapid progress

in the field of SMPs we envision new and more innovative

design strategies to further emerge in the future.

References and recommended readingPapers of particular interest, published within the period of review,have been highlighted as:

� of special interest

�� of outstanding interest

1.��

Lendlein A, Kelch S: Shape-memory polymers. Angew Chem IntEd 2002, 41:2034-2057.

An important early review of SMPs.

2. Dietsch B, Tong T: A review – features and benefits of shapememory polymers (SMPs). J Adv Mater 2007, 39:3-12.

3.��

Liu C, Qin H, Mather PT: Review of progress in shape-memorypolymers. J Mater Chem 2007, 17:1543.

A comprehensive review that classifies SMPs into four main categories.

4. Sokolowski W, Metcalfe A, Hayashi S, Yahia L, Raymond J:Medical applications of shape memory polymers. BiomedMater 2007, 2:S23-S27.

5. Behl M, Lendlein A: Actively moving polymers. Soft Matter 2007,3:58.

6. Rousseau IA: Challenges of shape memory polymers: a reviewof the progress toward overcoming SMP’s limitations. PolymEng Sci 2008, 48:2075-2089.

7. Ratna D, Karger-Kocsis J: Recent advances in shape memorypolymers and composites: a review. J Mater Sci 2008,43:254-269.

8.�

Mather PT, Luo X, Rousseau IA: Shape memory polymerresearch. Annu Rev Mater Res 2009, 39:445-471.

A review that focuses on newer developments in SMPs.


9. Liu Y, Lv H, Lan X, Leng J, Du S: Review of electro-active shape-memory polymer composite. Compos Sci Technol 2009,69:2064-2068.

10. Leng J, Lu H, Liu Y, Huang WM, Du S: Shape-memorypolymers – a class of novel smart materials. MRS Bull 2009,34:848-855.

11. Meng Q, Hu J: A review of shape memory polymer compositesand blends. Compos Part A Appl Sci Manuf 2009, 40:1661-1672.

12.�

Behl M, Razzaq MY, Lendlein A: Multifunctional shape-memorypolymers. Adv Mater 2010, 22:3388-3410.

A more recent, comprehensive review of SMPs.

13. Hu J, Chen S: A review of actively moving polymers in textileapplications. J Mater Chem 2010, 20:3346-3355.

14. Small I, Ward, Singhal P, Wilson TS, Maitland DJ: Biomedicalapplications of thermally activated shape memory polymers. JMater Chem 2010, 20:3356-3366.

15. Huang WM, Yang B, Zhao Y, Ding Z: Thermo-moistureresponsive polyurethane shape-memory polymer andcomposites: a review. J Mater Chem 2010, 20:3367-3381.

16. Lendlein A, Behl M, Hiebl B, Wischke C: Shape-memorypolymers as a technology platform for biomedicalapplications. Expert Rev Med Dev 2010, 7:357-379.

17. Leng J, Lan X, Liu Y, Du S: Shape-memory polymers and theircomposites: stimulus methods and applications. Prog MaterSci 2011, 56:1077-1135.

18.�

Xie T: Recent advances in polymer shape memory. Polymer2011, 52:4985-5000.

A review with special focus on the mechanistic aspects of shape memoryphenomena.

19. Hu J, Meng H, Li G, Ibekwe SI: A review of stimuli-responsivepolymers for smart textile applications. Smart Mater Struct2012, 21:053001.

20. Sun L, Huang WM, Ding Z, Zhao Y, Wang CC, Purnawali H, Tang C:Stimulus-responsive shape memory materials: a review. MaterDes 2012, 33:577-640.

21. Wornyo E, Gall K, Yang F, King W: Nanoindentation of shapememory polymer networks. Polymer 2007, 48:3213-3225.

22. Reddy S, Arzt E, del Campo A: Bioinspired surfaces withswitchable adhesion. Adv Mater 2007, 19:3833-3837.

23. Davis KA, Burke KA, Mather PT, Henderson JH: Dynamic cellbehavior on shape memory polymer substrates. Biomaterials2011, 32:2285-2293.

24. Le DM, Kulangara K, Adler AF, Leong KW, Ashby VS: Dynamictopographical control of mesenchymal stem cells by cultureon responsive poly(e-caprolactone) surfaces. Adv Mater 2011,23:3278-3283.

25. Burke KA, Mather PT: Soft shape memory in main-chain liquidcrystalline elastomers. J Mater Chem 2010, 20:3449-3457.

26. Ishida K, Hortensius R, Luo X, Mather PT: Soft bacterialpolyester-based shape memory nanocomposites featuringreconfigurable nanostructure. J Polym Sci Part B Polym Phys2012, 50:387-393.

27. Li F, Zhu W, Zhang X, Zhao C, Xu M: Shape memory effect ofethylene – vinyl acetate copolymers. J Appl Polym Sci 1999,71:1063-1070.

28. Liu C, Chun SB, Mather PT, Zheng L, Haley EH, Coughlin EB:Chemically cross-linked polycyclooctene: synthesis,characterization, and shape memory behavior.Macromolecules 2002, 35:9868-9874.

29. Kolesov IS: Multiple shape-memory behavior and thermal-mechanical properties of peroxide cross-linked blends oflinear and short-chain branched polyethylenes. Express PolymLett 2008, 2:461-473.

30.�

Chung T, Romo-Uribe A, Mather PT: Two-way reversible shapememory in a semicrystalline network. Macromolecules 2008,41:184-192.



An early report of two-way shape memory behavior in semi-crystallinepolymer networks.

31. Yu X, Zhou S, Zheng X, Guo T, Xiao Y, Song B: A biodegradableshape-memory nanocomposite with excellent magnetismsensitivity. Nanotechnology 2009, 20:235702.

32. Li J, Rodgers WR, Xie T: Semi-crystalline two-way shapememory elastomer. Polymer 2011, 52:5320-5325.

33. Cuevas JM, Laza JM, Rubio R, German L, Vilas JL, Leon LM:Development and characterization of semi-crystallinepolyalkenamer based shape memory polymers. Smart MaterStruct 2011, 20:035003.

34. Voit W, Ware T, Gall K: Radiation crosslinked shape-memorypolymers. Polymer 2010, 51:3551-3559.

35. Ware T, Voit W, Gall K: Effects of sensitizer length on radiationcrosslinked shape-memory polymers. Radiat Phys Chem 2010,79:446-453.

36. Zhu G, Xu S, Wang J, Zhang L: Shape memory behaviour ofradiation-crosslinked PCL/PMVS blends. Radiat Phys Chem2006, 75:443-448.

37. Zhu G, Liang G, Xu Q, Yu Q: Shape-memory effects of radiationcrosslinked poly (e-caprolactone). J Appl Polym Sci 2003,90:1589-1595.

38. Hearon K, Gall K, Ware T, Maitland DJ, Bearinger JP, Wilson TS:Post-polymerization crosslinked polyurethane shape memorypolymers. J Appl Polym Sci 2011, 121:144-153.

39. Liu C, Mather PT: Thermomechanical characterization of atailored series of shape memory polymers. J Appl Med Plast2002, 6:47-52.

40. Yakacki CM, Shandas R, Lanning C, Rech B, Eckstein A, Gall K:Unconstrained recovery characterization of shape-memorypolymer networks for cardiovascular applications.Biomaterials 2007, 28:2255-2263.

41.�

Safranski DL, Gall K: Effect of chemical structure andcrosslinking density on the thermo-mechanical properties andtoughness of (meth)acrylate shape memory polymernetworks. Polymer 2008, 49:4446-4455.

A comprehensive study of structure–property relationships in Tg based(meth)acrylate SMPs.

42. Yakacki CM, Willis S, Luders C, Gall K: Deformation limits inshape-memory polymers. Adv Eng Mater 2008, 10:112-119.

43. Ortega AM, Kasprzak SE, Yakacki CM, Diani J, Greenberg AR, Gall K:Structure–property relationships in photopolymerizable polymernetworks: effect ofcomposition on the crosslinked structure andresulting thermomechanical properties of a (meth)acrylate-based system. J Appl Polym Sci 2008, 110:1559-1572.

44. Yakacki CM, Shandas R, Safranski D, Ortega AM, Sassaman K,Gall K: Strong, tailored, biocompatible shape-memory polymernetworks. Adv Funct Mater 2008, 18:2428-2435.

45. Smith KE, Temenoff JS, Gall K: On the toughness ofphotopolymerizable (meth)acrylate networks for biomedicalapplications. J Appl Polym Sci 2009, 114:2711-2722.

46. Smith KE, Sawicki S, Hyjek MA, Downey S, Gall K: The effect ofthe glass transition temperature on the toughness ofphotopolymerizable (meth)acrylate networks underphysiological conditions. Polymer 2009, 50:5112-5123.

47. Voit W, Ware T, Dasari RR, Smith P, Danz L, Simon D, Barlow S,Marder SR, Gall K: High-strain shape-memory polymers. AdvFunct Mater 2010, 20:162-171.

48. Smith KE, Trusty P, Wan B, Gall K: Long-term toughness ofphotopolymerizable (meth)acrylate networks in aqueousenvironments. Acta Biomater 2011, 7:558-567.

49. Xie T, Rousseau IA: Facile tailoring of thermal transitiontemperatures of epoxy shape memory polymers. Polymer2009, 50:1852-1856.

50. Rousseau IA, Xie T: Shape memory epoxy: composition,structure, properties and shape memory performances. JMater Chem 2010, 20:3431-3441.


51. Leonardi AB, Fasce LA, Zucchi IA, Hoppe CE, Soule ER, Perez CJ,Williams RJJ: Shape memory epoxies based on networks withchemical and physical crosslinks. Eur Polym J 2011, 47:362-369.

52. Song WB, Wang LY, Wang ZD: Synthesis andthermomechanical research of shape memory epoxy systems.Mater Sci Eng A 2011, 529:29-34.

53. Feldkamp DM, Rousseau IA: Effect of chemical composition onthe deformability of shape-memory epoxies. Macromol MaterEng 2011, 296:1128-1141.

54. Nair DP, Cramer NB, Scott TF, Bowman CN, Shandas R:Photopolymerized thiol-ene systems as shape memorypolymers. Polymer 2010, 51:4383-4389.

55. Lin JR, Chen LW: Shape-memorized crosslinked ester-typepolyurethane and its mechanical viscoelastic model. J ApplPolym Sci 1999, 73:1305-1319.

56. Chen W, Zhu C, Gu X: Thermosetting polyurethanes with water-swollen and shape memory properties. J Appl Polym Sci 2002,84:1504-1512.

57. Lendlein A, Schmidt AM, Langer R: AB-polymer networks basedon oligo(e-caprolactone) segments showing shape-memoryproperties. Proc Natl Acad Sci USA 2001, 98:842-847.

58.�

Rousseau IA, Mather PT: Shape memory effect exhibited bysmectic-C liquid crystalline elastomers. J Am Chem Soc 2003,125:15300-15301.

The first report of one-way shape memory behavior in a liquid crystallineelastomer.

59. Rousseau IA, Qin H, Mather PT: Tailored phase transitions viamixed-mesogen liquid crystalline polymers with silicon-basedspacers. Macromolecules 2005, 38:4103-4113.

60.�

Kim BK, Lee SY, Xu M: Polyurethanes having shape memoryeffects. Polymer 1996, 37:5781-5793.

A classic paper on thermoplastic shape memory polyurethanes.

61.�

Lendlein A, Langer R: Biodegradable, elastic shape-memorypolymers for potential biomedical applications. Science 2002,296:1673-1676.

One of the earliest reports on biodegradable shape memory polymers.

62. Hu JL, Ji FL, Wong YW: Dependency of the shape memoryproperties of a polyurethane upon thermomechanical cyclicconditions. Polym Int 2005, 54:600-605.

63. Mohr R, Kratz K, Weigel T, Moneke M, Lendlein A: Initiation ofshape-memory effect by inductive heating of magneticnanoparticles. Proc Natl Acad Sci USA 2006, 103:3540-3545.

64. Knight PT, Lee KM, Qin H, Mather PT: Biodegradablethermoplastic polyurethanes incorporating polyhedraloligosilsesquioxane. Biomacromolecules 2008, 9:2458-2467.

65. Wu J, Ge Q, Mather PT: PEG–POSS multiblock polyurethanes:synthesis, characterization, and hydrogel formation.Macromolecules 2010, 43:7637-7649.

66. Liu C, Mather PT: Thermomechanical characterization ofblends of poly(vinyl acetate) with semicrystalline polymers forshape memory applications. In Proceedings of the AnnualTechnical Conference of the Society of Plastics Engineers(ANTEC). 2003:1962-1966.

67. Behl M, Ridder U, Feng Y, Kelch S, Lendlein A: Shape-memorycapability of binary multiblock copolymer blends with hardand switching domains provided by different components.Soft Matter 2009, 5:676-684.

68. Li S, Lu L, Zeng W: Thermostimulative shape-memory effect ofreactive compatibilized high-density polyethylene/poly(ethylene terephthalate) blends by an ethylene–butyl acrylate–glycidyl methacrylate terpolymer. J Appl Polym Sci 2009,112:3341-3346.

69. Zhang H, Wang H, Zhong W, Du Q: A novel type of shapememory polymer blend and the shape memory mechanism.Polymer 2009, 50:1596-1601.

70. Weiss RA, Izzo E, Mandelbaum S: New design of shape memorypolymers: mixtures of an elastomeric ionomer and low molarmass. Macromolecules 2008, 41:2978-2980.



71. Campo C, Mather PT: Shape memory binary blends:compositionally tailored fixing and recovery. In TheProceedings of the Annual Technical Conference of the Society ofPlastics Engineers (ANTEC). 2006:1510-1514.

72.�

Luo X, Mather PT: Preparation and characterization of shapememory elastomeric composites. Macromolecules 2009,42:7251-7253.

The first paper that demonstrates the new composite design strategy ofSMPs.

73.�

Luo X, Mather PT: Triple-shape polymeric composites (TSPCs).Adv Funct Mater 2010, 20:2649-2656.

An important implementation of the composite design strategy to preparetriple-shape SMPs.

74. Behl M, Bellin I, Kelch S, Wagermaier W, Lendlein A: One-stepprocess for creating triple-shape capability of AB polymernetworks. Adv Funct Mater 2009, 19:102-108.

75. Xie T, Xiao X, Cheng Y-T: Revealing triple-shape memory effect bypolymer bilayers. Macromol Rapid Commun 2009, 30:1823-1827.

76. Qin H, Mather PT: Combined one-way and two-way shapememory in a glass-forming Nematic network. Macromolecules2009, 42:273-280.

77.�

BellinI, Kelch S, Langer R: Lendlein a: polymeric triple-shapematerials. Proc Natl Acad Sci USA 2006, 103:18043-18047.

The first paper that introduces the concept of triple-shape memory.

78. Behl M, Lendlein A: Triple-shape polymers. J Mater Chem 2010,20:3335-3345.

79. Pretsch T: Triple-shape properties of athermoresponsivepoly(ester urethane). Smart Mater Struct2010, 19:015006.


80. Chen S, Hu J, Yuen CW, Chan L, Zhuo H: Triple shape memoryeffect in multiple crystalline polyurethanes. Polym Adv Technol2009, 21:377-380.

81. Luo H, Hu J, Zhu Y, Zhang S, Fan Y, Ye G: Achieving shapememory: reversible behaviors of cellulose–PU blends in wet–dry cycles. J Appl Polym Sci 2011, 125:657-665.

82. Luo H, Hu J, Zhu Y: Polymeric shape memory nanocompositeswith heterogeneous twin switches. Macromol Chem Phys 2011,212:1981-1986.

83. Luo X, Mather PT: Shape memory assisted self-healingcoatings, in preparation.

84. Mather PT, Luo X: Self-healing product. US Patent Application12/644,766.

85. Luo X: Thermally responsive polymer systems for self-healing,reversible adhesion and shape memory applications. PhDDissertation. Syracuse University; 2010.

86. Luo X, Mather PT: Conductive shape memory nanocompositesfor high speed electrical actuation. Soft Matter 2010, 6:2146.

87. Stone DA, Wanasekara ND, Jones DH, Wheeler NR, Wilusz E,Zukas W, Wnek GE, Korley LTJ: All-organic, stimuli-responsivepolymer composites with electrospun fiber fillers. ACS MacroLett 2012, 1:80-83.

88.�

Wang CC, Huang WM, Ding Z, Zhao Y, Purnawali H: Cooling-/water-responsive shape memory hybrids. Compos Sci Technol2012, 72:1178-1182.

A very innovative design of a shape memory composite that exhibitsunprecedented cooling-induced shape memory.


design strategies for shape memory polymers · shape memory is an intrinsic property to all...

Documents