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Delft University of Technology - Faculty of Aerospace Engineering
2012
Self‐HealinginThermalInterfaceMaterials
Master of Science Thesis
Christian Moreno Belle ‐ LR
1011642
TU Delft
Delft University of Technology Novel Aerospace Materials
Self-Healing
in
Thermal Interface Materials
Master of Science Thesis
Author:
Christian Moreno Belle
Advisors:
Prof. Dr. Ir. S. van der Zwaag
Dr. U. Lafont
Date:
13 August 2012
Contact information:
i
Abstract
Thermal interface materials, TIM’s, are materials that serve to conduct heat from a heat source
surface to a heat sink surface. Aside from their thermal conductive property TIM’s should have other
valuable properties, like adhesive strength, to ascertain structural integrity of the assembled
compound structures. However, over time the thermal interface materials may loose their good
contact with both surfaces due to delamination. This can happen as a result of stresses like
contraction and expansion due to thermal cycling. The damage and integrity of the TIM’s are difficult
to spot and measure. Self‐healing polymers based on reversible chemistry may offer an interesting
new route to autonomously restore interfacial adhesion upon delamination. In this research project
several types of self‐healing polymer composites were synthesized with thermally conductive
granular materials either as random textured or as quasi‐aligned polymer composites, combining
good thermal conductivity with long lasting interfacial adhesion to be used in microelectronics and
LED applications. The experiments conducted in this project indicate how well the different
composites perform for different filler in thermal conductivity, adhesive strength and self‐healing
ability. The results of this project indicate that competitive TIM’s with excellent adhesive properties
can be fabricated with self‐healing abilities.
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Preface
This report is my master thesis for the conclusion of my Master program at the faculty of Aerospace
Engineering at Delft University of Technology, TUDelft.
I take this opportunity to thank both of my supervisors, starting with Prof. Dr. Ir. S. van der Zwaag for
his insights, his guidance and comments, for letting me join the Novel Aerospace Materials group and
giving me the opportunity to work on a very interesting topic with my second supervisor, Dr. U.L.
Lafont, who I thank for his patience and understandings, his guidance and support thru all my work
and for being strict when I needed it the most.
A second word of thanks goes for Nijesh James for his comments and guidance. Furthermore I thank
Daniella Deutz for her insight, her useful critics and reading part of my report.
I also thank all the members of the Novel Aerospace Materials group for their cheering, friendship
and wonderful experience at the TUDelft.
I also would like to thank my family and close friends for their patience and support as some of them
live countries away from The Netherlands.
I really enjoyed working on this topic and the persons involved but it is time to finish this report, this
is just the beginning.
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Table of Contents
Abstract .................................................................................................................................................... i
Preface ..................................................................................................................................................... iii
Table of Contents ..................................................................................................................................... v
Nomenclature ......................................................................................................................................... vii
1 Introduction ..................................................................................................................................... 1
1.1 Thermal interface material ...................................................................................................... 1
1.2 Self‐healing .............................................................................................................................. 6
1.2.1 Additive based self‐healing ............................................................................................. 7
1.2.2 Intrinsic based Self‐healing .............................................................................................. 8
1.3 Particle alignment in composite using dielectrophoresis ..................................................... 12
2 Materials and test methods .......................................................................................................... 16
2.1 Composite synthesis .............................................................................................................. 16
2.2 Composite synthesis using dielectrophoresis ....................................................................... 20
2.3 Cohesion healing test ............................................................................................................ 21
2.4 Adhesion recovery: lap shear test ......................................................................................... 22
2.5 Thermal conductivity test ...................................................................................................... 23
2.6 Other characterization techniques used ............................................................................... 24
3 Experimental results ...................................................................................................................... 26
3.1 Material characterization ...................................................................................................... 26
3.2 Cohesion recovery results ..................................................................................................... 29
3.2.1 Aluminium as filler ......................................................................................................... 29
3.2.2 Aluminium Nitride as filler............................................................................................. 32
3.2.3 Boron Nitride as filler .................................................................................................... 35
3.2.4 Copper as filler ............................................................................................................... 38
3.2.5 Graphite as filler ............................................................................................................ 40
3.2.6 Data summary for cohesion test ................................................................................... 43
3.3 Adhesion recovery results ..................................................................................................... 47
3.3.1 Aluminium as filler ......................................................................................................... 47
3.3.2 Aluminium Nitride as filler............................................................................................. 47
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3.3.3 Boron Nitride as filler .................................................................................................... 48
3.3.4 Copper as filler ............................................................................................................... 48
3.3.5 Graphite as filler ............................................................................................................ 49
3.3.6 Data summary for adhesion test ................................................................................... 50
3.4 Thermal conduction results ................................................................................................... 51
3.4.1 Specimen with non—aligned particles .......................................................................... 51
3.4.2 Comparison between aligned and non‐aligned samples .............................................. 53
3.4.3 SEM analysis of particulate composites/particles ......................................................... 54
4 Discussion ...................................................................................................................................... 59
4.1 Cohesion recovery ................................................................................................................. 59
4.2 Adhesion recovery ................................................................................................................. 62
4.3 Thermal conduction .............................................................................................................. 66
4.4 Valorization strategy ............................................................................................................. 69
5 Conclusions .................................................................................................................................... 73
References ............................................................................................................................................. 74
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Nomenclature
Acronyms DA Diels‐Alder
cl Crosslinker
DEP DiElectroPhoresis
DSC Differential Scanning Calorimetric
EPS Epoxidized PolySulfide
Im Imaginary
rDA Retro Diels‐Alder
Re Real
rms Root mean square
rpm Revolution per minute
SEM Scanning Electron Microscope
TIM Thermal Interface Material
TEM Transmission Electron Microscopy
UV Ultra Violet
List of Symbols Latin symbols
Symbols Unit Description
J/Kg ⋅K Heat capacity
V/m Electric field
eV eV Electron volt
F N Force
f Hz Frequency
g/eq Gram‐equivalent
H% ‐‐ Healing percentage
K ‐‐ Clausius–Mossotti factor
k W/mK Thermal conductivity
m Kg Mass
p Pa Pressure
r m radius
T K or oC Temperature in Kelvin or Celsius
Ti oC Order‐disorder transition temperature
Tg oC Glass transition temperature
Tm oC Melting temperature
t s Time
V V Voltage
v m/s Velocity
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Greek symbols
Symbols Unit Description
‐ Del operator
F/m Permittivity
Pa⋅s Viscosity
Kg/m3 Density
Ω⋅m Electrical conductivity
MPa Shear strength
0 Phase‐angle
rad/s Angular frequency
1
1 Introduction
At present there are very good interface materials designed for micro‐ and optoelectronics. These
interfaces can be tailored to fulfil one or several functions depending on the requirements of the
assembled compounds: Insulate or conduct electricity or heat, hold the compounds together etc.
Aside from these functions the interface materials can contain properties to enhance its functionality
and applicability: Corrosion resistance, very high thermal resistance, fluidity, self‐healing, etc.
If one of these interfaces deteriorates or fails in any other way it may cause damage or even cause
failure to the system they belong. Stresses between the interface bonding agent and the attached
components are the main reason for interfacial failures, i.e. stresses originated by different
expanding coefficients, corrosion stresses, electrical stresses, etc [1]. Those can cause damage to the
bonding interface and with time cause total debonding from its attached component(s).
This research was conducted to investigate an adhesive interface composite provided with good
thermal conductivity and self‐healing ability to restore all its cohesive/ adhesive and thermal
conduction properties upon damage.
The most significant concepts‐tools are introduced in this chapter; Thermal interfaces materials, self‐
healing and dielectrophoresis. The next chapter explains in detail the synthesis of the specimen, the
test methods and processes used on the specimens. The third chapter presents the data results in
the form of graphs, tables and images. The results are discussed in chapter four.
1.1 Thermalinterfacematerial
Heat generated within an electronic device must be removed to maintain the functional temperature
of the component within safe operating limits. Often this heat removal process involves conduction
from the component package surface to a radiator, heat sink or heat spreader, which can transfer
the heat to the ambient environment more efficiently. This radiator has to be joined carefully to the
package to maximize the radiated thermal emission [2].
Attaching a radiator to an electronic device requires that two generally not perfectly flat surfaces are
brought into intimate contact. These surfaces are usually characterized by a microscopic surface
roughness superimposed on a macroscopic non‐planarity that can give the surfaces a concave,
convex or twisted shape represented in Figure 1.1.
Figure 1.1 Magnified surface imperfections containing air gaps [3]
2
When two such surfaces are mechanically joined at moderate contact pressures, contact occurs only
at the high points or peaks of the surfaces. The low points in the surface form air‐filled voids. Typical
contact area can consist of more than 80 percent air voids, which creates a significant resistance to
heat flow [3, 4].
Thermal Interface Materials, or TIM’s, are used to eliminate these interstitial air gaps from the
junction by conforming to the rough and uneven mating surfaces. Since TIM’s have significantly
greater thermal conductivity than the air they replace, the resistance across the interface decreases
and the heat flux is greatly increased leading to a drop in the temperature of the component.
A variety of TIMs has been developed in response to the changing needs of the electronic packaging
market and can be categorized into the following families:
Elastomeric Pads/Insulators
Thermally Conductive Adhesive Tapes
Phase Change Materials
Thermally Conductive Gap Fillers
Thermally Conductive “Cure in Place” Compounds
Thermal Compounds or Greases
Gap Filling Liquids
Thermally Conductive Adhesives
Each of the mentioned families has their own set of advantages and disadvantages, also between
materials within the families. Closely looking at some materials of each family the next advantages
and disadvantages can be found. From Kaveh, A et al. [5]:
Elastomeric Pads/Insulators: Containing ceramic particles which are often reinforced with woven
glass fibers.
Pros:
Very high dielectric strength.
Very high volume resistivity against heat loads.
Long term electrical insulation.
Cons:
Require very high clamping pressures, higher than 1.4 kPa.
Can deform with time.
Thermally Conductive Adhesive Tapes: Fabricated with silicon, fiberglass or silicon elastomers.
Pros:
Easy to use, peel and press. No curing dispensing.
Good for mid‐range thermal performance conductivity.
Replace mounting hardware.
Good for bonding small heat sinks to components, eliminating the need for clips, screws or
mechanical fasteners.
Able to bond surfaces which are significantly rough or bowed.
Reduce stresses, even with relatively high compression, to allow for uneven surfaces.
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Relatively low pressure needed to apply, 35 to 100 Pa.
Cons:
Do not solve components flatness issues. Issues with air gaps.
Only moderate thermal conductivity.
Thermal performance highly dependent on contact area that can be achieved between
bonding surfaces.
Phase Change Materials: Including silicon and organic based versions.
Pros:
Fill interfacial air gaps and surface voids.
Create strong adhesive bonds that can handle high temperatures.
Can achieve complete wet‐out of surface after a mild melt temperature.
Very low mounting force required.
Low thermal resistance.
Will melt at temperatures just above 50oC.
Cons:
Require other forms of attachment.
Some older versions flow out of tight areas.
Require some compressive force.
Do not provide electrical isolation.
Thermally Conductive Gap Fillers: Silicon with optional foam.
Pros:
Can fill large areas.
Offer grease‐like thermal performance with pad‐like handling and installation convenience.
Can blanket multiple components of varying heights.
Useful for low compression force applications.
Can be custom moulded.
Often good for bonding large gaps between hot components and cold surfaces.
Easy application without curing or dispersing.
Can be easily reworked.
Can be provided in thicker sizes or larger offsets than tapes.
Cons:
Inferior to phase change materials and thermal grease in high dissipation situations.
High clamping pressures, higher than 1.4 kPa.
“Cure in Place” Compounds: includes silicon, silicon free, ceramic filled polyurethane and graphite
materials.
Pros:
Provide electrical isolation along with thermal conductivity.
Offer superior resistance to tear and cut‐through form burrs on heat sinks.
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Cons:
Typically require special storage, have limited shelf life and require the final application work.
Greases and Gels: Including silicones, ceramic powder suspending in a liquid or gelatinous silicone, a
metal‐base version containing silver or aluminum particles and a carbon base version with diamond
powder.
Pros:
Easy to apply.
Do not need curing.
Can flow and conform to interfaces.
Offer re‐workable thermal interface layers.
Can achieve high thermal conductivity of 10 W/mK.
Since bond line thickness is very thin, less than 25 microns, the resulting thermal impedance
cross the interface can be low.
Silicon components do not leak out of the compounds.
No special storage requirements.
Insulated.
Cons:
Over time some can degrade, pump‐out or dry out.
Often present messy application issues.
Require careful application or it can lead to the formation of air gaps or leakages.
The actual bulk thermal conductivity is not high.
They have been regarded as “user unfriendly”.
No resistance to long term mechanical loads.
Gap Filling Liquids:
Pros:
Conforms like grease with respect to mating uneven surfaces.
Reduced material pomp out.
Low modulus.
Cons:
Curing time.
No resistance to long term mechanical loads.
Liquid Adhesives: Applied through dispensing or stencil printing.
Pros:
Provide structural support, eliminating the need for mechanical clip.
Cons:
Can be messy
5
After considering the different types of TIM together with the intention of making a polymer‐
granular conductor composite a closer look will be given to conductive adhesives. Thermal Adhesives
are one or two part adhesive systems which have been usually loaded with metallic or ceramic fillers
to enhance the thermal conductivity of the bulk polymer material. They are typically used to bond
small heat sinks to board level components, thus eliminating the need for clips, screws or other
mechanical fasteners to hold the heat sink in place. As a structural adhesive, thermal adhesives are
particularly useful for bonding surfaces which are significantly rough or curved.
Adhesives offer a number of advantages over mechanical fasteners:
Provide a relatively uniform distribution of stress across the joint.
Employ larger stress‐bearing areas.
Join similar or dissimilar materials of different thicknesses and shape.
Provide joints with smooth contours.
Seal joints against a variety of environments.
Can act as an insulator slowing heat transfer across the joint or act as a TIM facilitating heat
flow.
Five factors affect the choice, use, and performance of the interface material used between the
processor and the heat‐sink:
Thermal conductivity of the material.
Electrical conductivity of the material.
Gap Filling characteristics of the material.
Long‐term stability and reliability of the material.
Applicability.
When taking the above mentioned into account the ideal TIM see Figure 1.2, would be/have:
High thermal conductivity.
Easily conforms to both contours to be joined by small contact pressures .
Minimal thickness.
No leakage from the interface.
No deterioration over time.
Non‐toxic.
Easy to apply/remove.
However, when the actual performance of TIM is taken into account as in Figure 1.3, we can say that:
Gaps will not be completely filled, leaving some air pockets.
Some leakage may occur by the material by flowing out of its place due to pressure and/or
heat.
Performance may deteriorate over time.
Not always “manufacture friendly".
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Figure 1.2 Ideal TIM gap filling performace [6] Figure 1.3 Actual TIM gap filling performance [6]
1.2 Self‐healing
Self‐Healing is a bio‐mimicking process to repair existing damage on a system by itself by using some
or no energy from outside the system. Currently there are not many self‐healing processes that can
restore the damaged system to its original state [7, 8]. We label a material to have “Self‐healing”
properties when it can restore some properties by itself to some extent to keep that material
fulfilling its requirements, even if it is just the action of stopping crack growth. In this last case
“damage management” would be a more accurate label rather than self‐healing [9]. It should be
realized that the conditions during damage accumulation are always different (e.g. lower stress or
higher temperature, or additional energy input) from those during healing.
Self‐healing systems are differentiated using the accumulation of damage over the elapsed time as
parameter. With this, three cases are distinguished:
a. Cases where self‐healing occurs only once, this means that the damage diminishes in some
degree from the material and it starts piling up again until it breaks see Figure 1.4 a.
b. Cases where multiple sessions of healing can occur, healing the material to some extent but
never perfect and/or never to a fixed amount of damage, eventually leading to failure of the
material see Figure 1.4 b.
c. The ideal case where the material gets multiple healing processes of some extent but never
allowing the material to reach critical damage value see Figure 1.4 c. The ideal case will be
when the material can do this an infinite number of times during its service life.
Figure 1.4 Damage over time [8]
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For self‐healing processes to occur self‐healing properties will have to be added to the material in the
form of additives or by manipulating the material granting it with intrinsic properties allowing self‐
healing to be externally triggered. The trigger can be temperature, light, electrolytes, pressure etc.
Either of these will bring engineering challenges to the system.
1.2.1 Additivebasedself‐healing
To obtain an autonomous self‐healing material using additives means imbuing the material with
healing agents. Healing agents are mainly kept in a fluid state, in a container, until damage occurs,
then flow to seal the damage and solidify using help form a catalyst or another fluid to trigger curing.
Two different types of systems to contain healing agents are:
Encapsulated systems: Using capsules which can be spherical or other specially designed forms as
shown in Figure 1.5. Forms can be tailored according to the matrix they are in, the forces they have
to endure without breaking and the direction of the forces to optimize crack encounters. A crack has
to encounter these capsules for the self‐healing mechanism to occur. After the capsule has been
broken and its healing agent has cured that particular sphere will be expended and will no longer
participate in future healing processes [10‐12].
Vascular systems: Hollow tubes, filled with a liquid healing agent, are used to create vascular
systems as represented in Figure 1.6. These tubes can be connected with each other to help supply
the healing agent [12]. These systems can be refilled and they can be interconnected. These vascular
systems take a great amount of volume from the surrounding matrix, altering the entire system
properties on a bigger scale than the encapsulated system.
Using additives will change the properties of that material to some extent. It may reduce the desired
properties on which that material was chosen in the first place. Two important parameters for these
systems are how much healing substance can be added onto the material while remaining usable and
if that amount is enough for self‐healing. Self‐healing means that something somehow needs to
“move” to the open space of the crack, fill it and restrain it from further opening. Movable parts or
fluids are not desired on a load carrying material but the mobility of the healing agent is a necessary
condition for autonomous self‐healing.
Figure 1.5 Encapsulated system [12]
Figure 1.6 Vascular system [12]
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1.2.2 IntrinsicbasedSelf‐healing
The second approach to create a self‐healing material is to create materials with intrinsic self‐healing
properties, as represented in Figure 1.7, which have to be stimulated to trigger the healing
mechanism [12]. Heat is the most applied trigger for healing stimulation, by heating thermal reactive
self‐healing materials bonds will open up to later reform upon cooling down. This reversible bond
breaking lowers the viscosity making the material more or less fluid while at the same time giving the
material the mobility to seal the cracks. Surfaces need to be in contact with each other to close the
gap by creating new bonds and entangle, as shown in Figure 1.8. This holds for any healing
mechanism. After the temperature is lowered new bonds are created allowing the material to
recover an amount of damage and fixating the material as if new [12]. Problems related to
temperature stimulation are that the material may lose its shape and, during the healing process it
will not be able to carry loads.
Self‐healing is also a process that requires time. Instant healing responding to damage, using damage
as the trigger, would be the ideal process. For some self‐healing systems it will be almost impossible
to respond and heal as long as the material is carrying loads. Cyclic loads, against tensile static loads,
on the material can help in the self‐healing process, as healing can occur easier during resting periods
of cyclic loading or during long periods of compression loading which helps closing the crack making
surfaces to contact each other.
Self‐healing processes are very dependable on the material they are paired with and the
requirements of the material during its life. Some self‐healing materials can be seen as “tailored
products”, that means that when applying a known self‐healing system into a new material it should
be studied and tested to corroborate its compatibility.
Figure 1.7 Intrinsic principle [12]
Figure 1.8 Entanglement and reconnection options [13]
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When talking about intrinsic self‐healing it is usually referred to reversible bonding ability based
system including supramolecular chemistry. Supramolecular chemistry includes all intermolecular
bonding using non‐covalent bonds, reversible covalent bonds and hydrogen bonding [12, 14].
Some of the supramolecular chemistry reactions, most commonly applied for self‐healing, are briefly
presented below:
Coordination complex processes: In chemistry a coordination complex or metal complex happens
when an atom or ion, usually metallic, is bonded to a surrounding array of molecules or ions, which
are in turn known as “ligands” or “complexing agents”. Many metal‐containing compounds consist of
coordination complexes. Anything that forms a bond with a metal ion is called a "ligand", and the
structure of the resulting complex may be termed the "ligation structure" or "coordination
structure". Coordination chemistry might be of interest if metallic additives are used to enhance
electric and or thermal conductivity of a polymer [15].
Diels‐Alder reaction: This reaction, see Figure 1.9, is named after its discoverers Otto Diels and Kurt
Alder. They discovered how a 4+2 cycloaddition reaction between an electron rich diene, in their
case a furan, and an electron poor dienophile, in their case a maleinide, join to form a cyclohexene
system [16]. Diels‐Alder reaction is an organic chemical reaction that not only forms carbon to
carbon bonds but also heteroatom‐heteroatom bonds, making it a highly prized reaction to
synthesize polymers. A quality of the DA reaction is their thermal reaction to debond the
cyclohexene system obtaining again free dienes and dienophiles. This reversible reaction is called
retro‐Diels‐Alder (rDA) reaction and has been well studied in the case of furan and maleimide
substances. These thermally activated polymers using rDA reaction are good candidates for self‐
healing materials, especially if the healing temperature lies not too far above the working
environmental temperature the product will sustain during its service life.
Figure 1.9 Diels‐Alder reaction [16]
Hydrogen bond interactions: The hydrogen bond is really a special case of dipole forces. A hydrogen
bond is the attractive force between the hydrogen attached to an electronegative atom of one
molecule and an electronegative atom of a different molecule. Usually the electronegative atom is
oxygen, nitrogen, or fluorine, which has a partial negative charge. The hydrogen then has the partial
positive charge [17].
Hydrogen bonding is usually stronger than normal dipole forces between molecules. Of course
hydrogen bonding is not nearly as strong as normal covalent bonds within a molecule, about 1/10 as
strong. This is still strong enough to have many important ramifications on the properties of the
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substances they occur i.e. water. Increase in the melting point, boiling point, solubility, and viscosity
of many compounds can be explained by the concept of hydrogen bonding [18].
When the hydrogen bond density is made to be locally high, such as in the hydrogen quadruple
material developed at the Tue by Prf. Meyer, adequate mechanical properties can be obtained..
Ionomeric interactions: Ionomers are a type of copolymers, with less than 20mol% ionizing
monomeric units usually less than 10%, and contains acids [19, 20]. This may have a heavy impact at
the chemical and physical properties of the material. What makes the Ionomers interesting for self‐
healing is that the acidic content is being neutralized, partially or completely, by ions creating ionic
groups. Ions concentrate in the material in groups of ion‐pairs known as multiplets seen Figure 1.10.
With increasing number of multiplets they will start to overlap with each other, creating clusters of
ionic content. It is because of these that the ionomers create regions of increased rigidity within the
material.
Figure 1.10 Ionomer multiplet [21]
Figure 1.11 Ionomer mapping [22]
These clusters are microphase separated from the rest of the material. This will cause these zones to
have a different glass transition temperature than de rest of the material. When this temperature is
reached multiplets will dislocate and gain mobility with respect to each other. This temperature is
known as “order‐disorder transition temperature” Ti, which normally lies lower than the melting
temperature Tm of the crystalline structure they are in. During Ti the physical properties of the
structure are reduced as the multiplets weaken [6].
As the semi‐crystalline structure of the ionomer, is heated towards Ti the bonds with the multiplets
are weaken and can “jump” creating bonds somewhere else. If bonds were already broken, i.e. due
to crack growth, separated cluster of ions are waiting to make contact with the material again to
reform new bonds repairing the damage. For such process the only thing that is needed for the self‐
healing process is some mobility after the damage occurs to bring surfaces together.
Photodimerization process: Photodimerization is a bimolecular photochemical process involving an
electronically excited unsaturated molecule that undergoes addition with an unexcited molecule of
the same kind.
Reversible photo‐cross‐linkable nano‐particles can be used as building blocks to create self‐healing
hydro gel films. The mobility necessary to close crack faces can be achieved through swelling
obtained during an exposure to a certain wavelength of UV light. During this exposure bonds are
broken and free to rearrange with other bonds. To promote swelling even further a solvent can be
used to some experiments with positive results. After an exposure time of a determined UV
wavelength another wavelength is applied to fixate the newly formed bonds. This method was used
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by Cho et al. [21]. They targeted the reversible‐photo‐cycloadition bonded polymer gels for their test
subjects.
π‐interactions: In chemistry, π‐effects or π‐interactions are a type of non‐covalent reversible
interaction that involves so called π bonds between closely separated aromatic units in the polymer
backbone. Just like in an electrostatic interaction where a region of negative charge interacts with a
positive charge, the electron‐rich π system can interact with a metal, cationic or neutral, an anion,
another molecule and even another π system [23]. At elevated temperatures π‐ π associations tend
to find each other if close enough and form an intermediate state where all π systems are
momentarily together before separating with partner’s exchanged. This exchange gives the matrix a
certain degree of relaxation resulting in some fluidity and thus mobility to deform and repair[24].
Sulfur‐sulfur interaction: In terms of strength, non‐covalent bonds like hydrogen bonds are the
weakest in the supramolecular chemistry, even when they have good repairing properties for self‐
healing the strength obtained between the repaired crack surfaces might be insufficient for the
desired application. On the other hand there is i.e. the DA reaction bonding, these reactions generate
strong bonds that need an amount of heat to break and reverse, in other words, to heal. This amount
of heat or the needed duration for the healing might be too high for the surrounding structure. If the
end properties allow it, there are intermediate strength bonds that can be used for healing that
require less amount of heat for the reaction to take place. This type of self‐healing was chosen for
our experiments. Sulfur to sulfur in the form of disulfide to tetra‐sulfide bonds are such intermediate
bonds [25].Sulfur‐sulfur mechanism is shown in Figure 1.12
Figure 1.12 Mechanism of disulphide bond exchanges [25]
Sulfur bonds have the tendency to cleave under stress [26] they cleave and reattach as in Figure 1.13.
But after reaching a certain amount of stress there is more cleaving than re‐bonding creating
scissions in the material, stimulating degradation in its properties, it is also mentioned that disulfides
are more stable than other kind of sulfides having less problems from the sulphide scission
phenomena.
Figure 1.13 Sulfur bonds reattaching while under stress
Polymers containing sulfur‐sulfur bonds as the healing mechanism were chosen for the graduate
research project described in this thesis.
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1.3 Particlealignmentincompositeusingdielectrophoresis
As polymers and polymer adhesives have a low thermal conductivity by themselves, they are not
attractive candidate materials as TIMs.
To combine the good adhesive and thermo mechanical properties of the self‐healing polymer, with
adequate thermal conductivity values, granular materials with good intrinsic thermal conductivity,
such as Copper, Diamond or Boron Nitride, are mixed into the polymer matrix to obtain a functional
composite material.
It will be clear that the thermal conductivity will increase with the volume fraction of conductive
material. However high volume fractions of inert conductive material are likely to reduce the
adhesion and the attractive mechanical properties of the composite material.
However, in case of the granular particles are to be aligned in the direction of the leak flow, the heat
conduction is likely to go up, while the loss in other (mechanical) properties is likely to be small.
Recently, dielectrophoresis (DEP) was presented as an alternative and cheap method to align inert
functional particles into thread like structures in a low viscosity matrix, such as a polymer at an
elevated temperature [27].
In this chapter the physical principle of the DEP process is explained.
When an external electric field is applied across a particle suspended in a fluid medium, both the
particle and the suspending medium are being polarized. The result is the formation of unpaired
surface charges cumulated at the interface between the particle and the fluid medium. These
surface charges generate another electric field and distort the original electric field as represented in
Figure 1.14. The amount of charges at the interface depends on the field’s strength and the electrical
properties of the particle and the suspending medium. The most important electrical properties
involved are conductivity and permittivity, where conductivity is a measure of the ease with which
charges can move through a material, while permittivity is a measure of the energy storage or charge
accumulation in a system [28].
Figure 1.14 Dielectrophoresis typical electric field [28]
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The surface charges interact with the electric field to produce Coulomb forces. Since the electric field
distribution is not uniform, drawn in Figure 1.14, the electric field density is higher on the right than
on the left, resulting in a net force in the drawn direction.
Few methods have been developed to find the total electrical force on the particle, including
effective moment method and Maxwell Stress Tensor method.
Assuming that the observation point is far enough, relative to the size of the particle, the surface
charges on the particle in Figure 1.14 can be approximated as a dipole, which is oriented with the
direction of the electric field.
With this approximation, the total electrical force on the particle is found as in equation (1.1).
∙ (1.1)
where is the effective dipole moment specific to the particle‐fluid system and is a del operator.
This electrical force is termed as dielectrophoretic (DEP) force [28].
When the dipole approximation is not accurate, higher order multipoles have to be considered. The
general solution has been solved by Jones and Washizu.
One of the most important applications of dielectrophoresis is particle separation as represented in
Figure 1.15. It relies on the fact that one particular sub‐population of particles has unique frequency‐
dependent dielectric properties, which is different from any other population. The relative
magnitude and direction of the dielectrophoretic force exerted on a given population of particles
depends on the conductivity and permittivity of the suspending medium, together with the
frequency and magnitude of the applied field. Therefore, differences in the dielectric properties of
particles manifest themselves as variations in the dielectrophoretic force magnitude or direction,
resulting in separation of particles. Particle manipulation is achieved by controlling the applied
frequency, to change the direction of the movement of the particles. The design of the electrodes,
the choice of the suspending medium, and the applied peak voltage can be pre‐determined to
optimize the operation of the device.
Figure 1.15 Representation of the particle distribution a) Normally distributed b) Distribution after DEP
14
Dielectrophoretically aligned composites can be obtained by applying an electric field to a composite
medium of particles dispersed in a low medium such as an uncured thermoset resin or a intrinsically
self‐healing polymer heated to a temperature above the reversible bond dissociation temperature.
The time averaged DEP force acting upon a dielectric sphere with a complex permittivity ∗ and
radius r, suspended in a medium with a complex permittivity ∗ and subjected to an electric field
Erms, can be generalized using the previous equation as in equation (1.2) [29],
2 ′ ∗ ∗ (1.2)
where ′ is the real part of the complex permittivity of the matrix and Erms is the applied sinusoidal
electric field having magnitudes , , and phases , , . Re[] and Im[] denote the real
and the imaginary part [30]. ∗ is the complex Clausius–Mossotti factor which is a function, see
equation (1.3), of the complex permittivities ′ , ′ and of the direct current conductivities of both
phases , of the ceramic particles and the polymer matrix, respectively, and of the angular
frequency of the electric field , where 2 .
∗
∗ ∗ /∗ 2 ∗ 2 /
(1.3)
Bellow the Clausius–Mossotti factor is plotted for spherical particles and oblate spheroid models in
Figure 1.16. It can be seen how the Clausius–Mossotti factor changes according to the frequency. The
frequency changes the phase of the electrical field which the Clausius–Mossotti factor. The Clausius–
Mossotti factor has the biggest impact on the force applied on the particles when the phase‐angle is
closest to 900. The Clausius–Mossotti factor directly affects the force exerted on the particle by the
electric field. This force will try to move the particle resulting in a translation, a rotation or a rotation
by cause of the translation. The real and imaginary parts of the Clausius–Mossotti factor affect the
translation and the rotation of the particle respectively. With this, translation only or rotation only of
the particles can be achieved by tuning the Clausius–Mossotti factor.
The translational motion of particles due to DEP is strongest for particles with diameters ranging
from approximately 1 to 1000 µm, since above 1000 µm, gravity overwhelms DEP, while below 1 µm
the Brownian motion becomes the dominant force [30].
The sign on the Clausius–Mossotti also have significance in the movement of the particles. It seems
that the positive Clausius–Mossotti factor will force the particles to orientate parallel to the electrical
field while negative will orientate then perpendicular to the electrical field.
15
Figure 1.16 Clausius–Mossotti factors plotted for spherical particles and oblate spheroid models for . ⁄ , Left the real part Right the imaginary part [29]
As stated the Another important parameter affecting the alignment of the particles is the viscosity of
the polymer matrix. An increase in viscosity results in a higher drag force acting on the particles. The
drag force can be approximated using Stokes’s law for flow at low Reynolds numbers, equation (1.4).
6 (1.4)
Where is the viscosity of the medium, r is the radius of the particle, and v is the velocity of the
particle. A high drag force leads to minimal alignment, but the high viscosity will be beneficial for the
final mechanical properties.
With this it can be said that the factors affecting the dielectrophoresis are:
The viscosity of the medium
The frequency of the electrical field.
The voltage of the electrical field
The phase of the electrical field
The size of the particle
The electrical conductivity of the medium and the particles
16
2 Materials and test methods
In this chapter the structure and properties of the two polymers used are presented. Furthermore
the processing of the unstructured and DEP structured composites is described.
Finally the test methods used to determine the cohesive and adhesive self‐healing ability as well as
the thermal conductivity and other physical properties are presented.
2.1 Compositesynthesis
For our experiment a self‐healing material based on sulphur‐sulphur supramolecular chemistry has
been chosen as the matrix for the composite matrix while several inert, granular materials with
different conductive properties were chosen as filler.
The matrix is prepared mixing epoxidized polysulfide, Thioplast EPS25 or EPS70 as the primary
material together with a thiol based cross‐linker , pentaerythritol tetrakis (3‐mercaptopropionate) or
4‐SH, together they form the self‐healing polymer. 1 weight percentage of 4‐Dimethylamino pyridine
(DMAP) was added to the mixture as catalyst for the curing reaction.
Figure 2.1 EPS Chemistry Figure 2.2 Crosslinker
With the Thioplast as start point the amount of cross‐linker is calculated by equation (2.1).
(2.1)
where m is the mass of the material [g], ‘eps’ for the Thioplast and ‘cl’ for the cross‐linker, and the
gram‐equivalent value [g/eq]. Examples of some values can be seen in Table 2.1.
Table 2.1 Typical synthesis of the pristine matrix
Precursors EPS25[g] EPS70[g] 4SH[g] Catalyst[g]
Matrix1 10 ‐ 1.9088 0.11908
Matrix2 ‐ 10 3.9408 0.13940
Gram‐eq
reaction
linker ha
giving th
Before m
composi
are put t
is expres
mixer. T
were mi
and the
where m
quivalent is c
. The Thiopl
as a molar m
he values of
mixing the T
ite compoun
together ins
ssed in volu
he amount o
ixed for test
filler materia
m is the mass
calculated di
ast EPS25 ha
mass of 488.
640
Figure 2.3 Co
Thioplast and
nd. The Thiop
ide a special
ume percent
of filler is det
ting. For this
al has to be k
s, the dens
Figure 2
ividing the m
as a molar m
66 g/mol wi
0 and
ombination of T
d the 4‐SH a
plast EPS25
l container a
age. This co
termined by
s calculation
known and is
ity and % th
.4 Mixing cont
molar mass b
mass of 1280
ith 4 active r
122.165.
Thioplast EPS25
a filler mate
or EPS70, th
as seen in Fig
ontainer is d
its volume p
n the densiti
s calculated
he desired vo
tainer Fig
by the numb
0 g/mol with
radicals as s
5 or EPS70 + cr
erial is added
he crosslinke
gure 2.4. In a
designed to b
percentage a
es of the m
by equation
% 100⁄
1 % 10⁄
olume perce
gure 2.5 Speed
ber of radica
2 active rad
een in Figur
rosslinker 4SH
d to the mo
r 4‐SH, the c
all this work
be used in a
and different
atrix, Thiopl
(2.2).
0
entage of fille
Mixer
ls taking pla
dicals while t
re 2.1 and Fi
onomers to
catalyst and
the filler pe
a speed mix
t volume per
last plus cro
er.
17
ace in the
he cross‐
gure 2.2,
form the
the filler
ercentage
xer speed
rcentages
oss‐linker,
(2.2)
18
The composite compound was mixed using the Speed Mixer DAC 150.1 shown in Figure 2.5, at 2110
rpm for 80 s. After that they are set on a 1 mm thick Teflon mould as arranged as shown in Figure
2.6.
The mould contains six rectangular cavities of 78x30x1 mm for six specimens in case multiple
specimens are made at the same time.
Figure 2.6 Mould set‐up Figure 2.7 Oven
After the material Is placed into the Teflon mould, two big aluminium plates holds the mould and the
material fixed. This setup is taken into de oven shown in Figure 2.7 to cure for 2 hours at 650C. In the
oven a weight is used to inflict pressure and obtain good specimen surfaces.
Many kinds of fillers were used to manufacture several kinds on specimens. What is left of the
samples after testing shows the variety of the fabricated specimens in Figure 2.8. The types of
composites produced are listed in Table 2.2.
Figure 2.8 Examples of prepared specimens containing the following fillers‐Silver colour: Aluminium‐ Grey colour: Aluminium Nitride ‐ Brown: Copper – Transparent: No filler – White: Boron Nitride – Black: Graphite
The samples in Figure 2.8 were all synthesised using EPS25. At 10% they were prone to retain some
bubbles form mixing. Surfaces were smooth on low values of fillers and very flexible. This flexibility
was reduced significantly with the increase of filler content.
19
Table 2.2 shows all the materials prepared for testing.
Graphite Aluminum Copper AlN BN Diamond
EPS25‐4SH‐2,5% X
EPS70‐4SH‐2,5% X
EPS25‐4SH‐4% X
EPS70‐4SH‐4% X
EPS25‐4SH‐5% XA
EPS70‐4SH‐5% XA
EPS25‐4SH‐7,5% X
EPS70‐4SH‐7,5% X
EPS25‐4SH‐10% XA X X X XA
EPS70‐4SH‐10% X X X X X
EPS25‐4SH‐20% XA X X X XA
EPS70‐4SH‐20% X X X X X
EPS25‐4SH‐30% XA X X XA X
EPS70‐4SH‐30% X X X X
EPS25‐4SH‐40% XA X X XA
EPS70‐4SH‐40% X X X X
Table 2.2 Prepared materials. X: normal; A: Aligned
20
2.2 Compositesynthesisusingdielectrophoresis
After the compound has being mixed it is poured into the DEP mould Figure 2.10, a Teflon sheet with
a form of 25x25x1 mm. Two aluminium sheets are placed under and on top of the material where
the current will be applied. The material is strongly pressed using two heavy plates to improve the
contact of the aluminium sheets. This set up is represented in Figure 2.10. The heavy plates are
fastened using several bolts for an uniform pressure distribution. The set‐up is then placed in a safety
box where a function generator coupled with an high voltage amplifier is used to apply the electrical
field for the DEP alignment. The voltage for each specimen was chosen beforehand and the
frequency was set according to the phase‐angle between the voltage‐ current before and after going
through the set‐up.
Figure 2.9 Equipment for DEP a) Function generator b) Amplifier c) Oscilloscope d) Heater
Figure 2.10 DEP test Set‐up
The oscilloscope seen in Figure 2.9 gives the representative output voltage across the composite. The
sinusoidal voltage‐currents applied on the specimen and, the phase‐angle difference is graphically
given as seen in Figure 2.11 and Figure 2.12. The phase‐angle, determined by the frequency, affects
the Clausius–Mossotti factor witch directly affect the strength of the force the electrical field,
generated by the sinusoidal voltage‐current, exerts on the particles as mentioned in section 1.3. The
higher the force the better the alignment and that is achieve by applying a phase angle as close to
900 as possible [30].The set‐up was placed on top of a heater at 500C and left for 2 hours while under
current.
Figure 2.11 View of the sinusoidal electrical currents
Figure 2.12 Phase‐angle between the electrical currents
21
2.3 Cohesionhealingtest
A small piece of material, 10x15 mm, is prepared by inflicting two cuts of around 5 mm using a razor
blade. The cuts inflicted forms a cross with one of its ends meeting an edge of the sample. The first
part of the test consists on monitoring the state of the cut as function of the temperature and time.
An oven is set to simulate two different operating environments, 65oC or 100oC. Both are below the
decomposition temperature of the material.
For monitoring a microscope was used to observe the changes using a 2.5x zooming lens.
Figure 2.13 Microscope Figure 2.14 Setup
For the test Procedure
Cut small piece of the specimen
Cut a cross form incision to monitor during healing
Take an image of the incision
Sandwich the specimen using two microscope slides
Fix it with to clamps to simulate operating situations
Introduce the specimens into the oven to simulate operating environment
Wait a predetermined amount of time
Remove the specimen from the oven
Remove clamps and one crystal to expose the incision
Take an image operating the microscope to record the healing progress
This procedure keeps monitoring the progress of the healing until the cut disappears or a maximum
time is exceeded.
The cohesive test was realized by recording images of the healing progress. To translate al the
analogue data to digital data the surface separation of the cut was measured and compared to its
original aperture at 0 min. With this the healing efficiency is defined and 100% healing means that
the cut has closed completely.
22
2.4 Adhesionrecovery:lapsheartest
Lap shear test was conducted to measure the adhesion properties of the material as it may change
with the volume percentage of the filler added. The test took ASTM D1002 “Apparent Shear Strength
of Single‐Lap‐Joint Adhesively Bonded Metal Specimens by Tension Loading” as a model for
preparation and conduction of the test.
The prepared lap shear specimen consists of two plates of aluminium 6082 T6 that have been joined
by using a current specimen on each end where the two plates overlap, Figure 2.16. The Aluminium
plates were cleaned using acetone. From a synthesised TIM, 3 pieces were cut, while avoiding
surface imperfections like air bubbles. The obtained pieces were around 25x12x1 mm. To initially
hold the aluminium plates in place, clamps were used. The specimens where placed in an oven at
65oC for 2 hours to simulate working conditions and promote adhesion.
During the lap shear test, the aluminium plates are pulled in opposite directions at a rate of 1
mm/min to produce a shearing stress on the adhesive. An overlap of around 12 ±3 mm is used since
the yield point of the aluminium plate is not expected to be exceeded during the test. The distance
between the jaws was kept constant for all tests.
While careful consideration should be given to the grips used to hold the lap shear specimen, since
improper grips and setting alignment can lead to grip slippage and cleavage stresses, for our
specimens vice grips were chosen while looking at the maximum expected force.
Vice grips with serrated inserts were used for the lap shear tests. The serrated grip inserts are
designed to dig into the material and prevent it from slipping. If slippage occurs with a vice grip, self‐
tightening grips of pneumatic or wedge design may have been used. The specimen was mounted in
the tensile bench shown in Figure 2.15 Tensile bench, so that the centre line of the adhesive is
aligned with the centreline of the force exerted by the machine.
For the test procedure, all these steps represent 1 healing cycle;
Measure the contact area where both aluminium plates overlap.
Load each end of the specimen in the tensile grips and fasten them. The starting grip
distances was 90 mm. The grip area was around 25x43 mm per grip.
Apply a force that causes a displacement of 1mm/min between the plates until the specimen
breaks and, record the force history during the displacement and the type of joint failure.
After the test the specimens were prepared again by joining those using clamps with enough
force to keep the setup in place and prevent misalignment between the aluminium plates.
They were then placed in an oven for 2 hours at 65oC.
From each TIM created, 3 specimens for lap shear testing were prepared and, this procedure was
conducted seven times per specimen.
23
2.5 Thermalconductivitytest
Thermal conductivity testing was performed using the C‐Therm TCi thermal sensor, Figure 2.17.
This sensor is based on the Modified Transient Plane Source Method to determine the thermal
resistivity and effusivity of the material.
Figure 2.17 C‐Therm TCi [32]
Figure 2.18 Experiment set up [32]
The prepared specimen for this test must have a diameter of around 17 mm to cover the entire
sensor. The sensor works by being heated up by a small current and monitoring how it responses
while being in contact with the specimen. The resistivity and the effusivity of the specimen are
measured and obtained directly from the sensor. From the inverse of the resistivity the conductivity
is obtained. Using the effusivity concept other thermal properties like heat capacity and diffusivity
can be derived. The effusivity is given by equation (2.3).
kρc . (2.3)
where k is the thermal conductivity / ∙ , ρ is the density / and is the heat
capacity / ∙ .
Figure 2.15 Tensile bench Figure 2.16 Specimen set up [31]
24
This heating, reading and cooling will be repeated 6‐10 times per specimen to obtain an average of
the readings.
For the test procedure;
Set up the sensor
Wet the sensor with distilled water to improve contact
Apply de specimen on the sensor and a weight above it to press the specimen on the sensor,
Figure 2.18
Commence the sensing by heating up the sensor several times for several data points and
obtain an average
2.6 Othercharacterizationtechniquesused
To better understand the prepared specimens, their characteristics and parameters, the next set of
tests were conducted.
Differential scanning calorimetric (DSC) techniques were conducted using the PerkinElmer Sapphire
DSC shown in Figure 2.19 from ‐80 to 100°C at 3°C /min. This was conducted on a pristine specimen,
no filler added, and on a specimen with 30% volume of graphite to determine if there was a change
in the value of the glass transition temperature.
Figure 2.19 DSC
Figure 2.20 TEM Figure 2.21 SEM
Transmission electron microscopy (TEM) was performed using the FEI Tecnai TF20 electron
microscope seen in Figure 2.20, operated at 200 kV. Samples were mounted on Quantifoil® microgrid
carbon polymer supported on a copper grid by dropping sample suspension on the grid. This was
done to determine particle morphology of the added filler.
25
Scanning electron microscope (SEM) was used by the JEOL JSM‐7500F scanning electron micrograph
seen in Figure 2.21. Since our specimens are soft the specimens prepared for SEM were first frozen
by submerging them into liquid nitrogen and then breaking them. Since these specimens where
prepared with electrically conductive fillers they were directly mounted on the SEM for surface
observation.
Figure 2.22 Gold sputter
Figure 2.23 Set up
Later specimens were prepared differently. The material was first embedded in a polymer base
holder polished and covered by gold using the gold sputter seen Figure 2.22 for sputtering gold to
make the surface. This makes the surface conductive and more responsive for the image processing.
This is done because some specimens are not electric conductive.
26
3 Experimental results
In this chapter the results obtained by the tests explained on the previous chapter are presented.
First the materials characteristics are presented followed by the cohesion recovery results, the
adhesion recovery results and the thermal conduction results of the made specimens.
3.1 Materialcharacterization
All the data given by the DSC was plotted and presented below. Two cycles were performed per
sample.
In Figure 3.1 the plotted results of EPS25‐4SH for both cycles are given. The Tg for EPS25‐4SH was
determined, from both graphs, to be around ‐460 C.
Figure 3.1 DSC results for EPS25‐4SH 1st and 2nd cycle respectively
In Figure 3.2 the plotted results of EPS70‐4SH for both cycles are given. The Tg for EPS25‐4SH was
determined, from both graphs, to be around ‐3.50C.
Figure 3.2 DSC results for EPS70‐4SH 1st and 2nd cycle respectively
‐700
‐200
300
800
1300
1800
‐140 ‐120 ‐100 ‐80 ‐60 ‐40 ‐20 0 20
DSC
‐DDSC
Temperature [0C]
EPS25‐4SH 1st cycle
DSC [uW]DDSC [uW/min]
‐700
‐200
300
800
1300
1800
‐140 ‐120 ‐100 ‐80 ‐60 ‐40 ‐20 0 20
DSC
‐DDSC
Temperature [0C]
EPS25‐4SH 2nd cycle
DSC [uW]DDSC [uW/min]
‐700
‐200
300
800
1300
1800
‐130 ‐110 ‐90 ‐70 ‐50 ‐30 ‐10 10
DSC
‐DDSC
Temperature [0C]
EPS70‐4SH 1st cycle
DSC [uW]DDSC [uW/min]
‐700
‐200
300
800
1300
1800
‐130 ‐110 ‐90 ‐70 ‐50 ‐30 ‐10 10
DSC
‐DDSC
Temperature [0C]
EPS70‐4SH 2nd cycle
DSC [uW]DDSC [uW/min]
27
In Figure 3.3 the plotted results of EPS25‐4SH with 40% Graphite for both cycles are given. The Tg for
EPS25‐4SH‐40% Graphite was determined, from both graphs, to be around ‐430C.
Figure 3.3 DSC results for EPS25‐4SH‐40%Graphite 1st and 2nd cycle respectively
From the DSC around same values for the glass transition temperature Tg was obtained for the 0%
and 40% of graphite content. As expected, the fraction of interfacial material and the possible shift of
Tg due to molecular confinement at the interface was too small to lead to a measurable shift in glass
transition temperature. No DSC measurement were conducted for other samples.
‐1500
‐1000
‐500
0
500
1000
1500
2000
‐120 ‐100 ‐80 ‐60 ‐40 ‐20 0 20
DSC
‐DDSC
Temperature [0C]
EPS25‐4SH‐40%Gra 1st cycle
DSC…DDSC…
‐1500
‐1000
‐500
0
500
1000
1500
2000
‐120 ‐100 ‐80 ‐60 ‐40 ‐20 0 20DSC
‐DDSC
Temperature [0C]
EPS25‐4SH‐40%Gra 2nd cycle
DSC [uW]DDSC [uW/min]
28
From the TEM the next pictures were obtained, shown in Figure 3.4. These TEM pictures were taken
to characterize the powders and to know about morphology of the crystal agglomeration for several
of the used fillers.
Figure 3.4 TEM micrographs of (a) graphite (b) hBN and (c) Al (d) AlN particles used in the composites
From the images above it was observed that the particles of graphite and Aluminium are flakes and
that they heavily clustered together. Boron Nitride particles are more spherical and don’t tend to
cluster that much. Aluminium Nitride seems to have similar characteristics as Boron Nitride.
29
3.2 Cohesionrecoveryresults
The values obtained are plotted according to the time they were in the oven. The dots plotted are
the experimental data while the lines are calculated trend lines to simulate the healing progress of
that specimen. This section is arranged by the filler used to fabricate the TIM composite and ends
with section 3.2.6 comparing the filler used. Typical uncertainty in the healing fraction is ± 10 % and
an accuracy of 2.2 µm.
3.2.1 Aluminiumasfiller
The following graphs represent the results obtained using Aluminium as filler content.
Cohesion recovery at 65oC
Below it shows in Figure 3.5 the results for EPS25‐4SH and EPS70‐4SH combined with a) 10%, b) 20%,
c) 30% and d) 40% of Aluminium for a temperature of 65oC.
a) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 10 vol% Al at 65
oC
b) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 20 vol% Al at 65
oC
c) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 30 vol% Al at 65
oC
d) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 40 vol% Al at 65oC
Figure 3.5 Healing performance for EPS25‐4SH and EPS70‐4SH with Aluminium at 650C. Typical uncertainty in the healing fraction is ± 10 %.
0102030405060708090100
0 50 100 150 200 250
Healing %
Time [min]
10% Aluminium at 65o C
EPS25 + 10 vol% Al
EPS70 + 10 vol% Al
0
20
40
60
80
100
0 50 100 150 200 250
Healing %
Time [min]
20% Aluminium at 65o C
EPS25 + 20 vol% Al
EPS70 + 20 vol% Al
0
20
40
60
80
100
0 50 100 150 200 250
Healing %
Time [min]
30% Aluminium at 65o C
EPS25 + 30 vol% Al
EPS70 + 30 vol% Al0
20
40
60
80
100
0 50 100 150 200 250
Healing %
Time [min]
40% Aluminium at 65o C
EPS25 + 40 vol% Al
EPS70 + 40 vol% Al
30
Cohesion recovery at 100oC
Below it shows in Figure 3.6 the results for EPS25‐4SH and EPS70‐4SH combined with a) 10%, b) 20%,
c) 30% and d) 40% of Aluminium for a temperature of 1000C.
a) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 10 vol% Al at 100oC
b) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 20 vol% Al at 100oC
c) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 30 vol% Al at 100
oC
d) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 40 vol% Al at 100
oC
Figure 3.6 Healing performance for EPS25‐4SH and EPS70‐4SH with Aluminium at 1000 C. Typical uncertainty in the healing fraction is ± 10 %.
0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
10% Aluminium at 100o C
EPS25 + 10 vol% Al
EPS70 + 10 vol% Al
0
20
40
60
80
100
0 50 100 150 200Healing %
Time [min]
20% Aluminium at 100o C
EPS25 + 20 vol% Al
EPS70 + 20 vol% Al
0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
30% Aluminium at 100oC
EPS25 + 30 vol% Al
EPS70 + 30 vol% Al
0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
40% Aluminium at 100oC
EPS25 + 40 vol% Al
EPS70 + 40 vol% Al
31
In Figure 3.7 the results are given for Aluminium based EPS70‐4SH composite. All the specimens
experience high recovery rate at the start. Only the specimens of 30% and 40% at 1000C do not reach
80% of healing recovery.
Figure 3.7 Healing performance for EPS70‐4SH with different concentration of Aluminium. Typical uncertainty in the healing fraction is ± 10 %.
In Figure 3.8 the results are given for Aluminium based EPS70‐4SH composite. Specimens show a high
recovery rate stopping at much lower healing values than for EPS25‐4SH. Only the specimen
containing 10% of Aluminium at 1000C shows healing percentage values higher than 50%.
Figure 3.8 Healing performance for EPS70‐4SH with different concentration of Aluminium. Typical uncertainty in the healing fraction is ± 10 %.
0
10
20
30
40
50
60
70
80
90
100
0 50 100 150 200 250
Healing %
Time [min]
EPS25‐4SH with Aluminum
EPS25 + 10vol% Al 65CEPS25 + 20vol% Al 65CEPS25 + 30vol% Al 65CEPS25 + 40vol% Al 65CEPS25 + 10vol% Al 100CEPS25 + 20vol% Al 100CEPS25 + 30vol% Al 100CEPS25 + 40vol% Al 100C
0
10
20
30
40
50
60
70
80
90
100
0 50 100 150 200 250
Healing %
Time [min]
EPS70‐4SH with Aluminum
EPS70 + 10vol% Al 65CEPS70 + 20vol% Al 65CEPS70 + 30vol% Al 65CEPS70 + 40vol% Al 65CEPS70 + 10vol% Al 100CEPS70 + 20vol% Al 100CEPS70 + 30vol% Al 100CEPS70 + 40vol% Al 100C
32
3.2.2 AluminiumNitrideasfiller
The following graphs represent the results obtained using Aluminium Nitride as filler.
Cohesion recovery at 65oC
Below it shows in Figure 3.9 the results for EPS25‐4SH and EPS70‐4SH combined a) 10%, b) 20% and
c) 30% of Aluminium Nitride for a temperature of 65oC.
a) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 10 vol% AlN at 65
oC
b) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 20 vol% AlN at 65
oC
c) Healing performance for EPS25‐4SH and EPS70‐
4SH combined with 30 vol% AlN at 65oC
Figure 3.9 Healing performance for EPS25‐4SH and EPS70‐4SH with Aluminium Nitride at 650C. Typical uncertainty in the healing fraction is ± 10 %.
0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
10% Aluminum Nitride at 65oC
EPS25 + 10 vol% AlN
EPS70 + 10 vol% AlN
0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
20% Aluminum Nitride at 65o C
EPS25 + 20 vol% AlN
EPS70 + 20 vol% AlN
0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
30% Aluminum Nitride at 65o C
EPS25 + 30 vol% AlN
EPS70 + 30 vol% AlN
33
Cohesion recovery at 100oC
Below it shows in Figure 3.10 the results for EPS25‐4SH and EPS70‐4SH combined a) 10%, b) 20% and
c) 30% of Aluminium Nitride for a temperature of 100oC.
a) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 10 vol% AlN at 100oC
b) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 20 vol% AlN at 100oC
c) Healing performance for EPS25‐4SH and EPS70‐
4SH combined with 30 vol% AlN at 100°C
Figure 3.10 Healing performance for EPS25‐4SH and EPS70‐4SH with Aluminium Nitride at 1000 C. Typical uncertainty in the healing fraction is ± 10 %.
0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
10% Aluminum Nitride at 100o C
EPS25 + 10 vol% AlN
EPS70 + 10 vol% AlN0
20
40
60
80
100
0 50 100 150 200Healing %
Time [min]
20% Aluminum Nitride at 100o C
EPS25 + 20 vol% AlN
EPS70 + 20 vol% AlN
0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
30% Aluminum Nitride at 100o C
EPS25 + 30 vol% AlN
EPS70 + 30 vol% AlN
34
In Figure 3.11 the results are given for Aluminium Nitride based EPS70‐4SH composite. Except for the
30% specimen at 650C all the specimens experience a high recovery and high recovery rates reaching
complete or near complete recovery.
Figure 3.11 Healing performance for EPS25‐4SH with all the different filler concentrations
In Figure 3.12 the results are given for Aluminium Nitride based EPS70‐4SH composite. All the
specimens experience high recovery rate at the start of the recovery except the 30% at 650C. At
1000C all the specimens reach or almost reach complete recovery while at 650C the recovery seems
to stop before 80% for all the specimens.
Figure 3.12 Healing performance for EPS70‐4SH with all the different filler concentrations
0
10
20
30
40
50
60
70
80
90
100
0 50 100 150 200
Healing %
Time [min]
EPS25‐4SH with Aluminium Nitride
EPS25 + 10 vol% AlN 65C
EPS25 + 20 vol% AlN 65C
EPS25 + 30 vol% AlN 65C
EPS25 + 10 vol% AlN 100C
EPS25 + 20 vol% AlN 100C
EPS25 + 30 vol% AlN 100C
0
10
20
30
40
50
60
70
80
90
100
0 50 100 150 200
Healing %
Time [min]
EPS70‐4SH with Aluminium Nitride
EPS70 + 10 vol% AlN 65C
EPS70 + 20 vol% AlN 65C
EPS70 + 30 vol% AlN 65C
EPS70 + 10 vol% AlN 100C
EPS70 + 20 vol% AlN 100C
EPS70 + 30 vol% AlN 100C
35
3.2.3 BoronNitrideasfiller
The following graphs represent the results obtained using Boron Nitride as filler content.
Cohesion recovery at 65oC
Below it shows in Figure 3.13 the results for EPS25‐4SH and EPS70‐4SH combined a) 10%, b) 20%,
c) 30% and d) 40% of Boron Nitride for a temperature of 65oC.
a) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 10 vol% BN at 65
oC b) Healing performance for EPS25‐4SH and EPS70‐4SH combined
with 20 vol% BN at 65oC
c) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 30 vol% BN at 65oC
d) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 40 vol% BN at 65oC
Figure 3.13 Healing performance for EPS25‐4SH and EPS70‐4SH with Boron Nitride at 650 C. Typical uncertainty in the healing fraction is ± 10 %.
0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
10% Boron Nitride at 65o C
EPS25 + 10 vol% BN
EPS70 + 10 vol% BN0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
20% Boron Nitride at 65o C
EPS25 + 20 vol% BN
EPS70 + 20 vol% BN
0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
30% Boron Nitride at 65o C
EPS25 + 30 vol% BN
EPS70 + 30 vol% BN0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
40% Boron Nitride at 65o C
EPS25 + 40 vol% BN
EPS70 + 40 vol% BN
36
Cohesion recovery at 100oC
Below it shows in Figure 3.14 the results for EPS25‐4SH and EPS70‐4SH combined a) 10%, b) 20%,
c) 30% and d) 40% of Boron Nitride for a temperature of 100oC.
a) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 10 vol% BN at 100oC
b) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 20 vol% BN at 100oC
c) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 30 vol% BN at 100
oC
d) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 40 vol% BN at 100
oC
Figure 3.14 Healing performance for EPS25‐4SH and EPS70‐4SH with Boron Nitride at 1000C. Typical uncertainty in the healing fraction is ± 10 %.
0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
10% Boron Nitride at 100o C
EPS25 + 10 vol% BN
EPS70 + 10 vol% BN
EPS70 + 10 vol% BN H20
20
40
60
80
100
0 50 100 150 200Healing %
Time [min]
20% Boron Nitride at 100o C
EPS25 + 20 vol% BN
EPS25 + 20 vol% BN H2
EPS70 + 20 vol% BN
0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
30% Boron Nitride at 100o C
EPS25 + 30 vol% BN
EPS70 + 30 vol% BN0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
40% Boron Nitride at 100o C
EPS25 + 40 vol% BN
EPS70 + 40 vol% BN
37
In Figure 3.15 the results are given for Boron Nitride based EPS25‐4SH composite. Most of the
samples experience a high recovery rate at the start, clearly higher for those at 1000C. Most of them
reach healing values higher than 90% within 80 min. The specimen containing 40% at 65oC recovers
very slow after a recovery of 30%.
Figure 3.15 Healing performance for EPS25‐4SH with all the different filler concentrations. Typical uncertainty in the healing fraction is ± 10 %.
In Figure 3.16 the results are given for Boron Nitride based EPS25‐4SH composite. All the samples
experience a right healing rate before 30 min. The specimen of 40% at 65oC switches to slow
recovery after 20 min and cannot get higher than 20% of recovery. The other specimens reach 70%
or higher after 150 min
Figure 3.16 Healing performance for EPS70‐4SH with all the different filler concentrations. Typical uncertainty in the healing fraction is ± 10 %.
0
10
20
30
40
50
60
70
80
90
100
0 20 40 60 80 100 120 140 160 180 200 220 240 260 280
Healing %
Time [min]
EPS25‐4SH with Boron Nitride
EPS25 + 10 vol% BN 65C
EPS25 + 20 vol% BN 65C
EPS25 + 30 vol% BN 65C
EPS25 + 40 vol% BN 65C
EPS25 + 10 vol% BN 100C
EPS25 + 20 vol% BN 100C
EPS25 + 30 vol% BN 100C
EPS25 + 40 vol% BN 100C
0
10
20
30
40
50
60
70
80
90
100
0 20 40 60 80 100 120 140 160 180 200 220 240 260 280
Healing %
Time [min]
EPS70‐4SH with Boron Nitride
EPS70 + 10 vol% BN 65C
EPS70 + 20 vol% BN 65C
EPS70 + 30 vol% BN 65C
EPS70 + 40 vol% BN 65C
EPS70 + 10 vol% BN 100C
EPS70 + 20 vol% BN 100C
EPS70 + 30 vol% BN 100C
EPS70 + 40 vol% BN 100C
38
3.2.4 Copperasfiller
The following graphs represent the results obtained for applying Copper as the filler content and
healing under an environment of 65oC or 100oC
Cohesion recovery at 65oC
Below it shows in Figure 3.17 the results for EPS25‐4SH and EPS70‐4SH combined a) 10%, b) 20 of
Copper for a temperature of 65oC.
a) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 10 vol% Cu at 65oC
b) Healing performance for EPS70‐4SH combined with 20 vol% Cu at 65oC
Figure 3.17 Healing performance for EPS25‐4SH and EPS70‐4SH with Copper at 650 C. Typical uncertainty in the healing fraction is ± 10 %.
Cohesion recovery at 100oC
Below it shows in Figure 3.18 the results for EPS25‐4SH and EPS70‐4SH combined a) 10%, b) 20 of
Copper for a temperature of 100oC.
a) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 10 vol% Cu at 100oC
b) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 20 vol% Cu at 100oC
Figure 3.18 Healing performance for EPS25‐4SH and EPS70‐4SH with Copper at 1000 C. Typical uncertainty in the healing fraction is ± 10 %.
0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
10% Copper at 65o C
EPS25 + 10 vol% Cu
EPS70 + 10 vol% Cu0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
20% Copper at 65o C
EPS70 + 20 vol% Cu
0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
10% Copper at 100o C
EPS25 + 10 vol% Cu
EPS70 + 10 vol% Cu0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
20% Copper at 100o C
EPS25 + 20 vol% Cu
EPS70 + 20 vol% Cu
39
In Figure 3.19 the results are given for all Copper based EPS25‐4SH composite. The healing rate
experienced appear to be very linear. They all reach healing values above 50%.
Figure 3.19 Healing performance for EPS25‐4SH with all the different filler concentrations. Typical uncertainty in the healing fraction is ± 10 %.
In Figure 3.20 the results are given for all Copper based EPS25‐4SH composite. They show a fast
healing rate at the beginning and much slower after at 20 min all the specimens seem to stabilize
between 40 and 70 healing percentage.
Figure 3.20 Healing performance for EPS70‐4SH with all the different filler concentrations. Typical uncertainty in the healing fraction is ± 10 %.
0
10
20
30
40
50
60
70
80
90
100
0 20 40 60 80 100 120 140 160 180
Healing %
Time [min]
EPS25 with Copper
EPS25 + 10 vol% Cu 65C
EPS25 + 10 vol% Cu 100C
EPS25 + 20 vol% Cu 100C
0
10
20
30
40
50
60
70
80
90
100
0 20 40 60 80 100 120 140 160 180
Healing %
Time [min]
EPS70 with Copper
EPS70 + 10 vol% Cu 65C
EPS70 + 20 vol% Cu 65C
EPS70 + 10 vol% Cu 100C
EPS70 + 20 vol% Cu 100C
40
3.2.5 Graphiteasfiller
The following graphs represent the results obtained for applying Graphite as the filler content and
healing under an environment of 65oC or 100oC
Cohesion recovery at 65oC
Below it shows in Figure 3.21 the results for EPS25‐4SH and EPS70‐4SH combined a) 10%, b) 20%,
c) 30% and d) 40% of Graphite for a temperature of 65oC.
a) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 10 vol% Graphite at 65
oC b) Healing performance for EPS25‐4SH and EPS70‐4SH combined
with 20 vol% Graphite at 65oC
c) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 30 vol% Graphite at 65oC
d) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 40 vol% Graphite at 65oC
Figure 3.21 Healing performance for EPS25‐4SH and EPS70‐4SH with Graphite at 650 C. Typical uncertainty in the healing fraction is ±10 %.
0
20
40
60
80
100
0 20 40 60 80 100
Healing %
Time [min]
10% Graphite at 65o C
EPS25 + 10 vol% Graphite
EPS70 + 10 vol% Graphite0
20
40
60
80
100
0 20 40 60 80 100
Healing %
Time [min]
20% Graphite at 65o C
EPS25 + 20 vol% Graphite
EPS70 + 20 vol% Graphite
0
20
40
60
80
100
0 20 40 60 80 100
Healing %
Time [min]
30% Graphite at 65o C
EPS25 + 30 vol% Graphite
EPS25 + 30 vol% Graphite H2EPS70 + 30 vol% GraphiteEPS70 + 30 vol% Graphite H2
0
20
40
60
80
100
0 20 40 60 80 100
Healing %
Time [min]
40% Graphite at 65o C
EPS25 + 40 vol% Graphite
EPS25 + 40 vol% Graphite H2
EPS70 + 40 vol% Graphite
EPS70 + 40 vol% Graphite H2
41
Cohesion recovery at 100oC
Below it shows in Figure 3.22 the results for EPS25‐4SH and EPS70‐4SH combined a) 10%, b) 20%,
c) 30% and d) 40% of Graphite for a temperature of 100oC.
a) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 10 vol% Graphite at 100oC
b) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 20 vol% Graphite at 100oC
c) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 30 vol% Graphite at 100
oC
d) Healing performance for EPS25‐4SH and EPS70‐4SH combined with 40 vol% Graphite at 100
oC
Figure 3.22 Healing performance for EPS25‐4SH and EPS70‐4SH with Graphite at 1000C. Typical uncertainty in the healing fraction is ± 10 %.
0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
10% Graphite at 100o C
EPS25 + 10 vol% Graphite
EPS70 + 10 vol% Graphite0
20
40
60
80
100
0 50 100 150 200Healing %
Time [min]
20% Graphite at 100o C
EPS25 + 20 vol% Graphite
EPS70 + 20 vol% Graphite
0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
30% Graphite at 100o C
EPS25 + 30 vol% Graphite
EPS70 + 20 vol% Graphite0
20
40
60
80
100
0 50 100 150 200
Healing %
Time [min]
40% Graphite at 100o CEPS25 + 40 vol% Graphite
EPS70 + 40 vol% Graphite
42
In Figure 3.23 the results are given for all Graphite based EPS25‐4SH composite. Every specimen
show fast healing rate at the start. Only 40% experience an improvement in healing due to the higher
temperature. Most of the specimens reach healing values higher than 70%.
Figure 3.23 Healing performance for EPS25‐4SH with all the different filler concentrations. Typical uncertainty in the healing fraction is ± 10 %.
In Figure 3.24 the results are given for all Graphite based EPS25‐4SH. Every specimen show fast
healing rate at the start as in EPS25‐4SH. Many specimens do not experience an improvement in
healing due to the higher temperature. Specimens containing less than 30% of Graphite reach
healing values higher than 60%.
Figure 3.24 Healing performance for EPS70‐4SH with all the different filler concentrations. Typical uncertainty in the healing fraction is ± 10 %.
0
10
20
30
40
50
60
70
80
90
100
0 20 40 60 80 100 120 140 160 180 200 220 240 260
Healing %
Time [min]
EPS25‐4SH with Graphite
EPS25 + 10 vol% Gra 65C
EPS25 + 20 vol% Gra 65C
EPS25 + 30 vol% Gra 65C
EPS25 + 40 vol% Gra 65C
EPS25 + 10 vol% Gra 100C
EPS25 + 20 vol% Gra 100C
EPS25 + 30 vol% Gra 100C
EPS25 + 40 vol% Gra 100C
0
20
40
60
80
100
0 20 40 60 80 100 120 140 160 180 200 220 240 260
Healing %
Time [min]
EPS70‐4SH with Graphite
EPS70 + 10 vol% Gra 65C
EPS70 + 20 vol% Gra 65C
EPS70 + 30 vol% Gra 65C
EPS70 + 40 vol% Gra 65C
EPS70 + 10 vol% Gra 100C
EPS70 + 20 vol% Gra 100C
EPS70 + 30 vol% Gra 100C
EPS70 + 40 vol% Gra 100C
43
3.2.6 Datasummaryforcohesiontest
In Figure 3.25 all the fillers tested with a volume percentage of 10% are plotted for EPS25‐4SH. All
specimens get high values of healing percentage in a short amount of time making their healing
curve very linear.
Figure 3.25 Healing performance for EPS25‐4SH with all the different fillers at 10 vol% . Typical uncertainty in the healing fraction is ± 10 %.
In Figure 3.26 all the fillers tested with a volume percentage of 20% are plotted for EPS25‐4SH. All
specimens get high values of healing percentage in a short amount of time but not as good with 10%
of filler. Already some fillers exit the fast recovery rate period before reaching 90% and stabilizing
around that value.
Figure 3.26 Healing performance for EPS25‐4SH with all the different fillers at 20 vol%. Typical uncertainty in the healing fraction is ± 10 %.
0
10
20
30
40
50
60
70
80
90
100
0 20 40 60 80 100 120 140 160 180 200 220 240 260
Healing %
Time [min]
EPS25‐4SH with 10% filler
EPS25 + 10 vol% Al 65CEPS25 + 10 vol% AlN 65CEPS25 + 10 vol% BN 65CEPS25 + 10 vol% Cu 65CEPS25 + 10 vol% Gra 65CEPS25 + 10 vol% Al 100CEPS25 + 10 vol% AlN 100CEPS25 + 10 vol% BN 100CEPS25 + 10 vol% Cu 100C
0
10
20
30
40
50
60
70
80
90
100
0 20 40 60 80 100 120 140 160 180 200 220 240 260
Healing %
Time [min]
EPS25‐4SH with 20% filler
EPS25 + 20 vol% Al 65CEPS25 + 20 vol% AlN 65CEPS25 + 20 vol% BN 65CEPS25 + 20 vol% Gra 65CEPS25 + 20 vol% Al 100CEPS25 + 20 vol% AlN 100CEPS25 + 20 vol% BN 100CEPS25 + 20 vol% Cu 100CEPS25 + 20 vol% Gra 100C
44
In Figure 3.27 all the fillers tested with a volume percentage of 30% are plotted for EPS25‐4SH. Most
of the specimens lose a great amount of recovery rate at 30% of filler. Specimens containing Nitride
show better healing than the rest for both temperature settings. Their behaviour for this volume
percentage seem to widen the differences between fillers.
Figure 3.27 Healing performance for EPS25‐4SH with all the different fillers at 30 vol%. Typical uncertainty in the healing fraction is ± 10 %.
In Figure 3.28 all the fillers tested with a volume percentage of 40% are plotted for EPS25‐4SH. They
all show a fast recovery rate at the start. Boron Nitride shows a good recovery for its filler content.
The differences between fillers are more noticeable.
Figure 3.28 Healing performance for EPS25‐4SH with all the different fillers at 40 vol%. Typical uncertainty in the healing fraction is ± 10 %.
0
10
20
30
40
50
60
70
80
90
100
0 20 40 60 80 100 120 140 160 180 200 220 240 260
Healing %
Time [min]
EPS25‐4SH with 30% filler
EPS25 + 30 vol% Al 65CEPS25 + 30 vol% AlN 65CEPS25 + 30 vol% BN 65CEPS25 + 30 vol% Gra 65CEPS25 + 30 vol% Al 100CEPS25 + 30 vol% AlN 100CEPS25 + 30 vol% BN 100CEPS25 + 30 vol% Gra 100C
0
10
20
30
40
50
60
70
80
90
100
0 20 40 60 80 100 120 140 160 180 200 220 240 260
Healing %
Time [min]
EPS25‐4SH with 40% filler
EPS25 + 40 vol% Al 65C
EPS25 + 40 vol% BN 65C
EPS25 + 40 vol% Gra 65C
EPS25 + 40 vol% Al 100C
EPS25 + 40 vol% BN 100C
EPS25 + 40 vol% Gra 100C
45
In Figure 3.29 all the fillers tested with a volume percentage of 10% are plotted for EPS70‐4SH. They
all show a fast recovery rate at start. Their healing values are spread between 50% and 100% giving
already clear differences between fillers.
Figure 3.29 Healing performance for EPS70‐4SH with all the different fillers at 10 vol%. Typical uncertainty in the healing fraction is ± 10 %.
In Figure 3.30 all the fillers tested with a volume percentage of 20% are plotted for EPS70‐4SH. They
all show a fast recovery rate at start. Their healing values are spread between 40% and 100%.
Widening the differences between fillers with respect to 10%.
Figure 3.30 Healing performance for EPS70‐4SH with all the different fillers at 20 vol%. Typical uncertainty in the healing fraction is ± 10 %.
0
10
20
30
40
50
60
70
80
90
100
0 20 40 60 80 100 120 140 160 180 200 220 240 260
Healing %
Time [min]
EPS70‐4SH with 10% filler
EPS70 + 10 vol% Al 65C EPS70 + 10 vol% AlN 65CEPS70 + 10 vol% BN 65C EPS70 + 10 vol% Cu 65CEPS70 + 10 vol% Gra 65C EPS70 + 10 vol% Al 100CEPS70 + 10 vol% AlN 100C EPS70 + 10 vol% BN 100CEPS70 + 10 vol% Cu 100C EPS70 + 10 vol% Gra 100C
0
10
20
30
40
50
60
70
80
90
100
0 20 40 60 80 100 120 140 160 180 200 220 240 260
Healing %
Time [min]
EPS70‐4SH with 20% filler
EPS70 + 20 vol% Al 65C EPS70 + 20 vol% AlN 65CEPS70 + 20 vol% BN 65C EPS70 + 20 vol% Cu 65CEPS70 + 20 vol% Gra 65C EPS70 + 20 vol% Al 100CEPS70 + 20 vol% AlN 100C EPS70 + 20 vol% BN 100CEPS70 + 20 vol% Cu 100C EPS70 + 20 vol% Gra 100C
46
In Figure 3.31 all the fillers tested with a volume percentage of 30% are plotted for EPS70‐4SH. They
all show a fast recovery rate at start but entering the slow rate before reaching a healing percentage
of 50%. Their healing values are spread between 20% and 80% for most of them.
Figure 3.31 Healing performance for EPS70‐4SH with all the different fillers at 30 vol%. Typical uncertainty in the healing fraction is ± 10 %.
In Figure 3.32 all the fillers tested with a volume percentage of 40% are plotted for EPS70‐4SH. They
all show a fast recovery rate at start but entering the slow rate early in the healing. Their healing
values are spread between 5% and 25% for most of them.
Figure 3.32 Healing performance for EPS70‐4SH with all the different fillers at 40 vol%. Typical uncertainty in the healing fraction is ± 10 %.
0
10
20
30
40
50
60
70
80
90
100
0 20 40 60 80 100 120 140 160 180 200 220 240 260
Healing %
Time [min]
EPS70‐4SH with 30% filler
EPS70 + 30 vol%Al 65CEPS70 + 30 vol%AlN 65CEPS70 + 30 vol%BN 65CEPS70 + 30 vol%Gra 65CEPS70 + 30 vol%Al 100CEPS70 + 30 vol%AlN 100CEPS70 + 30 vol%BN 100CEPS70 + 30 vol%Gra 100C
0
10
20
30
40
50
60
70
80
90
100
0 20 40 60 80 100 120 140 160 180 200 220 240 260
Healing %
Time [min]
EPS70‐4SH with 40% filler
EPS70 + 40 vol%Al 65C
EPS70 + 40 vol%BN 65C
EPS70 + 40 vol%Gra 65C
EPS70 + 40 vol%Al 100C
EPS70 + 40 vol%BN 100C
EPS70 + 40 vol%Gra 100C
47
3.3 Adhesionrecoveryresults
The results are first presented divided by the type of filler used and later a comparison between
fillers is given. A typical uncertainty of 15% can be applied.
3.3.1 Aluminiumasfiller
The adhesion recovery data for the specimens containing Aluminium as filler divided in two graphics
sorted by the composite matrix EPS25‐4SH and EPS70‐4SH with all volume percentages of
Aluminium, both shown in Figure 3.33 a) for EPS25‐4SH and b) for EPS70‐4SH.
a) Shear stress of EPS25‐4SH with Aluminium for several healing events
b) Shear stress of EPS70‐4SH with Aluminium for several healing events
Figure 3.33 Shear stress for the matrixes a) EPS25‐4SH and b) EPS70‐4SH with all Aluminium filler content. Typical uncertainty in the healing fraction is ±15 %.
3.3.2 AluminiumNitrideasfiller
The adhesion recovery data for the specimens containing Aluminium Nitride as filler divided in two
graphics sorted by the composite matrix EPS25‐4SH and EPS70‐4SH with all volume percentages of
Aluminium Nitride, both shown in Figure 3.34, a) for EPS25‐4SH and b) for EPS70‐4SH.
a) Shear stress of EPS25‐4SH with Aluminium Nitride for several healing events
b) Shear stress of EPS70‐4SH with Aluminium nitride for several healing events
Figure 3.34 Shear stress for the matrixes a) EPS25‐4SH and b) EPS70‐4SH with all Aluminium Nitride filler percentages. Typical uncertainty in the healing fraction is ±15 %.
‐0,5
0,5
1,5
2,5
3,5
0
0,1
0,2
0,3
0 2 4 6 8
Shear strength [Kg/cm
2]
Shear strength [MPa]
Healing events
EPS25‐4SH with Aluminium10%
20%
30%
‐0,5
0,5
1,5
2,5
3,5
0
0,1
0,2
0,3
0 2 4 6 8
Shear strength [Kg/cm
2]
Shear strength [MPa]
Healing events
EPS70‐4SH with Aluminum
10%20%30%40%
0
1
2
3
4
5
6
7
0
0,1
0,2
0,3
0,4
0,5
0,6
0 2 4 6 8
Shear strength [Kg/cm
2]
Shear strength [MPa]
Healing events
EPS25‐4SH with Aluminum Nitride
10 vol% Al
20 vol% Al
30 vol% Al
0
1
2
3
4
5
6
7
0
0,1
0,2
0,3
0,4
0,5
0,6
0 2 4 6 8
Shear strength [Kg/cm
2]
Shear strength [MPa]
Healing events
EPS70‐4SH with Aluminum Nitride
10 vol% Al20 vol% Al30 vol% Al
48
3.3.3 BoronNitrideasfiller
The adhesion recovery data for the specimens containing Boron Nitride as filler divided in two
graphics sorted by the composite matrix EPS25‐4SH and EPS70‐4SH with all volume percentages of
Boron Nitride, both shown in Figure 3.35, a) for EPS25‐4SH and b) for EPS70‐4SH.
a) Shear stress of EPS25‐4SH with Boron Nitride for several healing events
b) Shear stress of EPS70‐4SH with Boron Nitride for several healing events
Figure 3.35 Shear stress for the matrixes a) EPS25‐4SH and b) EPS70‐4SH with all Boron Nitride filler content. Typical uncertainty in the healing fraction is ±15 %.
3.3.4 Copperasfiller
The adhesion recovery data for the specimens containing Copper as filler divided in two graphics
sorted by the composite matrix EPS25‐4SH and EPS70‐4SH with all volume percentages of Copper,
both shown in Figure 3.36, a) for EPS25‐4SH and b) for EPS70‐4SH.
0
1
2
3
4
5
6
7
0
0,1
0,2
0,3
0,4
0,5
0,6
0 2 4 6 8
Shear strength [Kg/cm
2]
Shear strength [MPa]
Healing events
EPS25‐4SH with Boron Nitride
10%
20%
30%
40%
0
1
2
3
4
5
6
7
0
0,1
0,2
0,3
0,4
0,5
0,6
0 2 4 6 8
Shear strength [Kg/cm
2]
Shear strength [MPa]
Healing events
EPS70‐4SH with Boron Nitride
10%
20%
30%
40%
49
a) Shear stress of EPS25‐4SH with Copper for several healing events
b) Shear stress of EPS70‐4SH with Copper for several healing events
Figure 3.36 Shear stress for the matrixes a) EPS25‐4SH and b) EPS70‐4SH with all Copper filler content. Typical uncertainty in the healing fraction is ±15 %.
3.3.5 Graphiteasfiller
The adhesion recovery data for the specimens containing Graphite as filler divided in two graphics
sorted by the composite matrix EPS25‐4SH and EPS70‐4SH with all volume percentages of Graphite,
both shown in Figure 3.37, a) for EPS25‐4SH and b) for EPS70‐4SH.
a) Shear stress of EPS25‐4SH with Graphite for several healing events
b) Shear stress of EPS70‐4SH with Graphite for several healing events
Figure 3.37 Shear stress for the matrixes a) EPS25‐4SH and b) EPS70‐4SH with all Graphite filler content. Typical uncertainty in the healing fraction is ±15 %.
0
0,5
1
1,5
2
2,5
0
0,05
0,1
0,15
0,2
0 2 4 6 8
Shear strength [Kg/cm
2]
Shear strength [MPa]
Healing events
EPS25‐4SH with Copper
10%
20%0
0,5
1
1,5
2
2,5
0
0,05
0,1
0,15
0,2
0 2 4 6 8
Shear strength [Kg/cm
2]
Shear strength [MPa]
Healing events
EPS70‐4SH with Copper
10%l
20%
0
1
2
3
4
5
6
7
0
0,1
0,2
0,3
0,4
0,5
0,6
0 2 4 6 8 10
Shear strength [Kg/cm
2]
Shear strength [MPa]
Adhesion Cycle
EPS25‐4SH with Graphite
2.5%
3.5%
5%
7.5%
10%
20%
30%
40%
0
1
2
3
4
5
6
7
0
0,1
0,2
0,3
0,4
0,5
0,6
0 2 4 6 8 10
Shear strength [Kg/cm
2]
Shear strength [MPa]
Adhesion Cycle
EPS70‐4SH with Graphite
2.5%
3.55%
5%
7.5%
10%
20%
30%
40%
50
3.3.6 Datasummaryforadhesiontest
In Figure 3.38 the adhesion shear strength of fillers tested are plotted for EPS25‐4SH. It shows how
the values for metallic fillers go down linearly while the other fillers experience an improvement at
start resulting on a maximum.
Figure 3.38 Shear strength of EPS25‐4SH with several fillers
In Figure 3.39 the adhesion shear strength of fillers tested are plotted for EPS70‐4SH. It shows how
the values for metallic fillers go down linearly while the other fillers experience an improvement at
start resulting on a maximum. The position of this maximum is spread in a larger range than in
EPS25‐4SH.
Figure 3.39 Shear strength of EPS70‐4SH with several fillers
0
1
2
3
4
5
6
0
0,1
0,2
0,3
0,4
0,5
0% 5% 10% 15% 20% 25% 30% 35% 40% 45%
Shear strength [Kg/cm
2]
Shear strength [Mpa]
Filler volume precentage
EPS25‐4SH with FillerAluminiumAlNBNCopperDiamond
0
1
2
3
4
5
6
0
0,1
0,2
0,3
0,4
0,5
0% 5% 10% 15% 20% 25% 30% 35% 40% 45%
Shear strength [Kg/cm
2]
Shear strength [Mpa]
Filler volume percentage
EPS70‐4SH with fillerAluminium
AlN
BN
Copper
51
3.4 Thermalconductionresults
The next results were found for the thermal test. First the data for the specimens prepared without
alignment are presented. Then the aligned specimens are presented together with the results of the
not aligned specimens for comparison. Typical uncertainty is ± 1%.
3.4.1 Specimenwithnon—alignedparticles
In Figure 3.40 the thermal conductivity is given for EPS25‐4SH and EPS70‐4SH with all the volume
percentages for the fillers: a) Aluminium b).Aluminium Nitride c) Boron Nitride d) Copper .e) Graphite
a) Thermal conductivity for EPS25‐4SH containing Aluminium b) Thermal conductivity for EPS25‐4SH containing Aluminium Nitride
c) Thermal conductivity for EPS25‐4SH containing Boron Nitride
d) Thermal conductivity for EPS25‐4SH containing Copper
e) Thermal conductivity for EPS25‐4SH containing Graphite
Figure 3.40 Thermal conductivity for EPS25‐4SH and EPS0‐4SH with the fillers: a) Aluminium b).Aluminium Nitride c) Boron Nitride d) Copper e) Graphite. Typical uncertainty is ± 1%.
‐0,5
0,5
1,5
2,5
0 10 20 30 40
Therm
al conductivity
[W/m
K]
Volume percentage of filler
Aluminium
EPS25
EPS70
‐0,5
0,5
1,5
2,5
0 10 20 30 40Th
erm
al conductivity
[W/m
K]
Volume percentage of filler
Aluminium Nitride
EPS25
EPS70
‐0,5
0,5
1,5
2,5
0 10 20 30 40
Therm
al conductivity
[W/m
K]
Volume percentage of filler
Boron Nitride
EPS25
EPS70
‐0,5
0,5
1,5
2,5
0 10 20 30 40Therm
al conductivity
[W/m
K]
Volume percentage of filler
Copper
EPS25
EPS70
0
0,5
1
1,5
2
2,5
0 10 20 30 40Therm
al conductivity
[W/m
K]
Volume percentage of graphite
Graphite
EPS25
EPS70
52
In Figure 3.41 the thermal conductivity for EPS25‐4SH is plotted for all the different filler used. All the
specimens experience a linear increase in thermal conduction The different between filler seem to
remain constant under 40%. At 40% Graphite experiences a major improvement compared to
previous volume fractions.
Figure 3.41 Thermal conductivity for EPS25‐4SH and filler. Typical uncertainty is ± 1%.
In Figure 3.42 the thermal conductivity for EPS70‐4SH is plotted for all the different filler used. All the
specimens experience a linear increase in thermal conduction. For this matrix the difference between
fillers increase after 20% where Graphite improves faster than the other fillers.
Figure 3.42 Thermal conductivity for EPS70‐4SH and filler. Typical uncertainty is ± 1%.
0
0,5
1
1,5
2
2,5
0 10 20 30 40
Therm
al conductivity [W/m
K]
Volume percentage of Filler
Thioplast EPS25
Graphite
Boron Nitride
Copper
Aluminium Nitride
Aluminium
0
0,5
1
1,5
2
2,5
0 5 10 15 20 25 30 35 40
Therm
al conductivity [W/m
K]
Volume percentage of Filler
Thioplast EPS70
Graphite
Boron Nitride
Copper
Aluminium Nitride
Aluminium
53
3.4.2 Comparisonbetweenalignedandnon‐alignedsamples
The data for the aligned specimens, processed using DEP, are plotted below together with their not‐
aligned version for comparison. In Figure 3.43 he thermal conductivity for EPS25 is plotted for:
a) Graphite aligned and not aligned and b) Boron nitride aligned and non‐aligned.
From both graphs the difference between alignment gets noticeable after a high amount of filler.
Larger amount that 20% for Graphite and 30% for Boron Nitride.
a) Thermal conductivity for EPS25‐4SH and Graphite, aligned and not‐aligned
b) Thermal conductivity for EPS25‐4SH and Boron Nitride, aligned and not‐aligned
Figure 3.43 Thermal conductivity for EPS25‐4SH with the fillers: a) Graphite b)) Boron Nitride. Typical uncertainty is ± 1%.
0
0,5
1
1,5
2
2,5
0 10 20 30 40
Therm
al conductivity
[W/m
K]
Volume percentage of filler
Aligning Graphite
EPS25
EPS25 aligned
0
0,5
1
1,5
2
2,5
0 10 20 30 40
Therm
al conductivity
[W/m
K]
Volume percentage of filler
Aligning Boron Nitride
EPS25
EPS25 aligned
54
3.4.3 SEManalysisofparticulatecomposites/particles
The results, obtained using the Scanning Electron Microscope, are presented below. These results
consist on surface images, Energy dispersion spectroscopy data and images and, weight analysis
using the atom count from the energy dispersion spectroscopy.
In Figure 3.44 the surface images for EPS25‐4SH containing not aligned Graphite for 40% of the
specimen volume is presented.
Figure 3.44 SEM for EPS25‐4SH with 40vol% Graphite‐Not Aligned. a) 60x b)200x c) 500x
In Figure 3.45 the energy dispersion spectroscopy electron count and surface mapping images for
EPS25‐4SH containing not aligned Graphite for 40% of the specimen volume is presented.
Figure 3.45 Energy Dispersion Spectroscopy for EPS25‐4SH with 40vol% Graphite‐Not Aligned. Left: element detection. Right: element mapping (Grey picture, CK Carbon, OK Oxygen, SK sulphur).
55
In Table 3.1 the weight analysis using the atom count from the energy dispersion spectroscopy SEM
for EPS25‐4SH with 40vol% Graphite, not aligned, is presented.
Element
Line
Net
Counts
Net Counts
Error
Weight %
Weight %
Error
Atom %
Atom %
Error
C K 69879 +/‐ 323 84.12 +/‐ 0.39 90.66 +/‐ 0.42
O K 7143 +/‐ 185 7.22 +/‐ 0.19 5.85 +/‐ 0.15
S K 73169 +/‐ 452 8.66 +/‐ 0.05 3.50 +/‐ 0.02
S L 0 +/‐ 58 ‐‐‐ ‐‐‐ ‐‐‐ ‐‐‐
Total 100.00 100.00
Table 3.1 Energy Dispersion Spectroscopy weight analysis for EPS25‐4SH containing not aligned 40 vol% Graphite
In Figure 3.46 and Figure 3.47 the surface images for EPS25‐4SH containing Graphite for 40% of the
specimen volume is presented.
Figure 3.46 SEM for EPS25‐4SH with 40 vol% of Graphite‐Aligned. a) 500x b) 2500x c) 10000x
(c)
56
Figure 3.47 SEM for EPS25‐4SH with 40 vol% of Graphite‐Aligned. a) 500x b) 2500x c) 2500x
In Figure 3.48 the energy dispersion spectroscopy electron count and surface mapping images for
EPS25‐4SH containing aligned Graphite for 40% of the specimen volume is presented.
Figure 3.48 Energy Dispersion Spectroscopy for EPS25‐4SH with 40 vol% Graphite aligned‐Aligned. Left: element detection. Right: element mapping (Grey: picture, SK: Sulphur, CK: Carbon, Au M: Gold, OK: Oxygen)
In Table 3.2the weight analysis using the atom count from the energy dispersion spectroscopy SEM
for EPS25‐4SH with 40 vol% Graphite, aligned, is presented.
Element
Line
Net
Counts
Net Counts
Error
Weight %
Weight %
Error
Atom %
Atom %
Error
C K 12658 +/‐ 118 67.05 +/‐ 0.63 94.28 +/‐ 0.88
O K 388 +/‐ 77 1.40 +/‐ 0.28 1.48 +/‐ 0.29
S K 676 +/‐ 131 3.48 +/‐ 0.67 1.83 +/‐ 0.36
S L 0 +/‐ 13 ‐‐‐ ‐‐‐ ‐‐‐ ‐‐‐
Au M 3975 +/‐ 188 28.07 +/‐ 1.33 2.41 +/‐ 0.11
Total 100.00 100.00
Table 3.2 Energy Dispersion Spectroscopy weight analysis for EPS25‐4SH containing 40 vol% Graphite‐Aligned
57
In Figure 3.49 the surface images for EPS25‐4SH containing Boron Nitride for 20% of the specimen
volume is presented.
Figure 3.49 SEM for EPS25‐4SH with 20 vol% of Boron Nitride. a) 60x b) 500x c) 3000x d) 10000x e) 30000x f) 50000x
In Figure 3.50 the surface images for EPS25‐4SH containing Boron Nitride for 300% of the specimen
volume is presented.
Figure 3.50 SEM for EPS25‐4SH with 30 vol% of Boron Nitride‐Aligned. a) 1000x b) 2000x c) 2000x
58
In Figure 3.51 the energy dispersion spectroscopy electron count and surface mapping images for
EPS25‐4SH containing aligned Boron Nitride for 40% of the specimen volume is presented.
Figure 3.51 Energy Dispersion Spectroscopy for EPS25‐4SH with 40% Boron Nitride‐Aligned. Left: element detection. Right: element mapping (Grey: picture, NK: Nitrogen, BK: Boron, CK: Carbon, OK: Oxygen, SK: Sulphur, Au M: Gold).
In Table 3.3 the weight analysis using the atom count from the energy dispersion spectroscopy SEM
for EPS25‐4SH with 40vol% Boron Nitride, aligned, is presented.
Element
Line
Net
Counts
Net Counts
Error
Weight %
Weight %
Error
Atom %
Atom %
Error
B K 2858 +/‐ 116 15.79 +/‐ 0.64 20.80 +/‐ 0.84
C K 16359 +/‐ 243 31.85 +/‐ 0.47 37.75 +/‐ 0.56
N K 14934 +/‐ 240 30.69 +/‐ 0.49 31.20 +/‐ 0.50
O K 8084 +/‐ 259 6.73 +/‐ 0.22 5.99 +/‐ 0.19
S K 44198 +/‐ 480 8.54 +/‐ 0.09 3.80 +/‐ 0.04
S L 0 +/‐ 68 ‐‐‐ ‐‐‐ ‐‐‐ ‐‐‐
Au L 0 0 ‐‐‐ ‐‐‐ ‐‐‐ ‐‐‐
Au M 21718 +/‐ 600 6.40 +/‐ 0.18 0.46 +/‐ 0.01
Total 100.00 100.00
Table 3.3 Energy Dispersion Spectroscopy weight analysis for EPS25‐4SH containing 40 vol% Boron Nitride
59
4 Discussion
In this chapter the results given in chapter 3 are treated and discussed. First the results concerning
the cohesion ability of the specimens are discussed followed by the adhesion ability and the thermal
conductivity of the composed materials. The chapter ends with a valorisation and characterization of
the different types of composites tested giving a tool with the purpose of identifying the most
suitable composite for the engineering needs of the application.
4.1 Cohesionrecovery
In this subsection the results of the cohesion recovery from section 3.1 are treated. The cohesion
recovery is directly related to healing of the damage by reconnecting the surfaces forming the crack.
In this section first the reproducibility of the test is discussed, and then the theories concerning the
cohesion recovery are presented, starting by discussing the influence of the matrix, the influence of
the filler and finishing with a discussion of the temperature dependence during healing.
Reproducibility
As explained in section 2.3, the data of the cohesion results were obtained from images taken using a
microscope equipped with a digital camera. To translate al the analog data to digital data the
distance between surfaces was measured and compared to its original aperture at 0 min. With this
100% healing means that the cut has closed completely. The values obtained are plotted according to
the healing time: the time they were in the oven.
There are several points that should be mentioned before discussing the results which may affect the
reliability of the data obtained. These points may affect the reproducibility of the tests.
‐ The thickness of the samples: All the samples do start with an approximate thickness of 1
mm. During the test, pressure was applied to the samples by the clamps in thickness
direction reducing this thickness during the test, the lower the viscosity the thinner the
thickness of the specimen at the end. This increase of flow helps to seal the damaged area
before healing can take place.
‐ The removal of the microscope slide: To successfully take an image of the sample the
microscope slide from the top side was removed, since the microscope light was reflected
disturbing the imaging. While removing the slide stresses are applied to the specimen. While
this procedure was carefully made it may produce separation of the healing surfaces as it
bonded on the slide. Separation of the surfaces by removing the microscope slide negatively
affects in sample performance. Saying this, the sample of copper for 20 volume percentage
was lost this way several times as it bonded too well on the slide to be removed.
‐ Sharpness and light of the image: While recording the image the image should be sharp and
well lit to distinguish the scission and its edges. Shadows make it difficult to locate the
scission edge. The sharpness of the image was also found to be a variable for the location of
the surface edges. Focusing the image was done by moving the sample closer or further
away from the camera. The edge of the scission has to be at the exact same distance from
the camera for every sample since the further the sample the smaller the perceived damage.
60
‐ Damage of samples: The initial damage of the samples was all reproduced using the same
cutting edge but the cuts procedure yielded samples containing more or less damage to heal
with respect to each other. This difference in damage is not reflected in the results. Two
samples completely healed after the same amount of time are seeing as having the same
healing properties.
‐ Surface contact: The contact of the surface is a must for self‐healing, especially if the material
has poor flow properties. Surfaces that were found to separate during test and not coming
into contact where not count in the results. The cut inflicted into the material was cross
formed counting 4 pair of surfaces that can move and heal at their own individual rate. This
can be seen as 4 healing reading per sample.
‐ The number of tests: Due to the short time to do all the tests, each test was performed only
once for most of the samples. Normally a number of tests of the same sample is always
desired to filter errors as much as possible.
Influence of the matrix
From the figures in section 3.2 it can be deduced that the healing depends on the matrix, the filler
content, the temperature of the environment, the type of filler and the time spent in the oven.
‐ In sections 3.2.1‐3.2.5 it can be observed that EPS25‐4SH has generally better healing recovery
properties than EPS70‐4SH. Many of the EPS25‐4SH samples manage to completely heal, as shown in
Figure 4.1. On the other hand many of the EPS70‐4SH do not completely heal leaving a scar, as
shown in Figure 4.2, or not heal at all if there was no connection between surfaces. There is healing,
but not enough flow for the material to move and seal the damage completely in most of the EPS70
cases.
Figure 4.1 EPS25‐4SH‐10%BN‐130min Figure 4.2 EPS70‐4SH‐10%BN‐190min
From the molecular architecture of the Thioplast [33, 34] EPS25‐4SH and EPS70, as shown in Figure
2.1, it is expected that EPS25‐4SH, to have better self‐healing properties than EPS70‐4SH. This can be
explained by two factors concerning their chemistry; their chain flexibility and their glass transition
temperature Tg.
61
Chain flexibility factor: Looking at the chemistry of the EPS25 [33] and EPS70 [34], shown Figure 2.1,
it can be seen that EPS70 is composed of molecules with a high aromatic content while EPS25 is
compose by aliphatic molecules. The aromatic rings of the EPS70 increases the chain rigidity and
reduces the flexibility of the chains and subsequently of the entire material, as compared to EPS25.
The molecular rigidity and flexibility will affect the viscosity of the compound [35]. The healing of the
material will happen when surfaces meet giving the chance to the molecules to entangle or
reconnect as shown in Figure 1.8 [12]. The less flexible the chains are the more difficult it will be for
the healing to take place since viscosity is a key parameter in healing. These factors make the EPS25
more favourable for self‐healing than EPS70.
Glass transition temperature factor: Viscosity deals with the relative displacement of entire chains
along each other and only occurs at high temperatures and in no‐crosslinked systems.
For the slightly crosslinked systems explored here, the glass transition temperature, which gives the
minimum temperature for substantial motion of molecular segments may be more relevant [26, 36].
The DSC measurements yielded Tg of ‐400 C and ‐100 C for EPS25‐4SH and EPS70‐4SH materials
respectively. See section 3.1. Clearly The EPS70 has the higher Tg. Heat temperatures of 650 C and
1000 C are well above the respective Tg values.
The difference for EPS25, being lower than for EPS70, contributes to the faster healing for EPS25 at
the fixed healing temperatures.
Influence of the filler
It is also expected that the rigidity of the compound to be significantly affected by the type and
volume fraction. Fillers are basically impurities added into a compound, making the compound the
matrix and the impurity the filler. A filler particle, or conglomerate, will obstruct a matrix molecule
from moving and making bonds to other molecules that are in the other side. If it happens that the
other side forms part of the damage surface, it will prevent healing to take place on that part of the
surface. Hanneman et al. [37] studied the influence of alumina fillers on unsaturated polyester resin
polymer matrix with results increasing viscously along with the amount of filler.
It should be pointed out that the filler particles themselves have no healing ability, given their
covalent or metallic bond structure and the healing temperatures well below the particulate
materials melting temperatures.
Environment influence
‐ From section 3.2.6 the differences between tested fillers can be observed in Figure 3.25 to Figure
3.28 It can be seen that graphite tends to be the best in EPS25 for 650C. While for 1000C Boron
Nitride and Aluminum Nitride performances increases substantially compared to the rest.
Graphite and Aluminum Nitride seem to be negatively affected by the increase of temperature for
less than 30 volume percentage.
‐ From Figure 3.29 to Figure 3.32 it can be observed that graphite is a good choice for a temperature
of 650C. Aluminum Nitride has a good performance compared to 10 and 20 volume percentages.
Increasing the temperature to 1000C seems to increase the recovery of Boron Nitride significantly,
especially at 30 volume percentage. Graphite is in EPS70 also negatively affected under 30 volume
percentage.
62
It can be concluded that from this section that EPS25‐4SH is the best choice when looking at the
cohesion recovery, this was found when looking at the matrix, the type of filler and environment
applied. It was also found that the results obtained are not completely reproducible, especially when
only one sample per material configuration was tested. More tests should be made with the same
material configuration to filter errors and increase its reliability.
4.2 Adhesionrecovery
The results of the adhesion test shown in section 3.3 were conducted using the procedure explained
in section 2.4.
In this section, the influence of amount of filler on adhesion will be discussed first. The reliability of
the bond will be next mentioned followed by the influence of time and the type of filler.
It can be seen from all figures from section 3.3, Figure 3.33 to Figure 3.39 that the adhesion
properties of the composite does change with the amount of filler used. As a compound gets more
filler inside, decreasing the amount of matrix per volume percentage, a decrease of the adhesive
properties was expected for all the specimens
In Table 4.1 lap shear strength of several materials is given to compare how well the synthesized
materials perform with respect to commercial TIM’s.
LapshearStrength[MPa]
ThermallyConductiveAdhesives(TechFilm®) 7‐28
EPS70‐4SH10%Al 0.1142
EPS70‐4SH20%AlN 0.544
EPS70‐4SH30%BN 0.517
EPS70‐4SH20%Cu 0.138
EPS70‐4SH20%Graphite 0.51
EPS25‐4SH10%Al 0.2078
EPS25‐4SH20%AlN 0.276
EPS25‐4SH30%BN 0.484
EPS25‐4SH10%Cu 0.199
EPS25‐4SH30%Graphite 0.39
Pads(Chomerics®) 0.3‐1.1
Tapes(Chomerics®) 0.1‐1.1
Table 4.1 Lap shear strength of several commercial TIM’s and best synthesized specimens per filler
63
‐ It can be observed that for some of the fillers that the adhesive property of the compound
increased with the volume percentage of the material up to an optimum where it decreased again,
best seen in Figure 3.38 and Figure 3.39.
To explain why this phenomenon occurs, two possible approaches are exposed for discussion.
Stiffness approach: The fillers used for the experiments are stiff and hard compared to the polymer
matrix. These are metals, semimetals or ceramic particles. Filler particles move within the matrix and
along with the flow of the matrix but they do not deform. Clusters of particle do deform but not the
particles. Fillers and clusters made of the filler material do block and impede the matrix to flow and
interact with the material at the other side, reducing the kinetic energy of the material. This means
increasing the viscosity. The matrix responds to the fillers positively increasing the viscosity [38] and
sequentially the rigidity of the overall compound. Rigidity of the material can increase the adhesive
property of the composite until a maximum optimum is reached and it decreases from that point
downwards. The form of the particle, their cluster formation affinity and the bonding strength
between filler and matrix can explain to understand why some filler did get better while increasing
the amount of fillers while other fillers were weaken from the start.
With this said it should be noted that from the fillers used only the non‐metallic fillers did get an
improvement and a maximum in their adhesive properties.
Figure 4.3 Effect of stiffness on adhesive bonds
More rigidity to a soft material can mean that the stresses going thru the material are better
distributed within the material becoming less concentrated at the edges where adhesives are the
weakest as represented in Figure 4.3. From Figure 4.3 it can be deduced that the deformation caused
by the soft material approaches mode I seen in Figure 4.4. Mode I is the weakest mode of the
material increasing the chances for failure of the bond between the adhesive and the adherent.
Different forms of failure between adhesive and adherent are presented in Figure 4.5. After a certain
amount of filler the adhesion of the specimen fails because it is too stiff and the stresses concentrate
again at the edges instead of evenly distributed through the entire adhesive causing a Mode II
failure. This could explain the maximum in the shear strength.
It was noted that the failures of the specimens where Adhesive or interfacial failures as seen in
Figure 4.5 in the right‐up corner and adhesive or interfacial failure with jumping fractures as seen in
Figure 4.5 in the button‐center position. This makes the bonding between the adhesive and the
adherent surface the weakness in the specimen.
64
Figure 4.4 Stress modes on a adhesive juncture
Figure 4.5 Failure modes of adhesives
Filler interaction approach: For this approach we look at the fact how the filler added into the matrix
will bond with the matrix and how this may affect the macroscopic adhesion. The strength of the
bonds, the type of bonds and the amount of bonds depend on the type of filler added. When looking
at the surface of the specimen to be bonded to the adherent it can be found that the surface has a
population of filler in it. This filler has an effect on the matrix in contact with him and the adherent as
schematized in Figure 4.6. Different cases could be resulting from the presence of the filler.
Case where the filler has a good bonding affinity with the matrix taking all the free radical of
the matrix around him for itself leaving none near him to interact with the adherent
surface.
Case where the matrix does have poor affinity with the matrix. The filler only takes a few
bonds and the rest are free to interact with the adherent surface.
Case where the filler does have good bonding affinity with the adherent surface and make
some kind of non‐covalent bonding with it, h‐bonding, ionic bonding, etc., reducing the
bonds that the matrix can make with the adherent around the filler. This can have positive
or negative effect depending on the strength of the bonds between the filler and the
adherent surface compared to the bonds between the matrix and the adherent surface as.
Case where the filler has bad bonding affinity, or even experiencing repulsion, giving more
chances for the matrix to create more bonds in the area directly around the filler.
Figure 4.6 Filler‐surface iteration representation
65
These theoretical cases may help understand why the metallic fillers were significantly worse
compared to the non‐metallic and semi‐metallic fillers. Metallic materials do not really like to make
bonds with new surfaces unless greatly heated up or being affected by a magnetic field.
‐ From the results exposed in Figure 3.33 to Figure 3.37 it can be seen that there is a good recovery of
the adhesion strength for all the fillers. In other words, the adhesion strength remains around the
same value for every made cycle. This behavior in favorable is cases where the adhesive separates
from the surfaces and has the opportunity to re‐bond with the surface, as long as there is contact
and sufficient time. This means that the adhesion recovery can heal up to a 100% of its original
strength. From this observation it follows that there is no need to increase the temperature of the
recovery periods to values above 650 C, unless healing time is critical.
‐ From the same figures last mentioned it can observed that most specimens experiences peak in
their 4th testing period. This is caused by a longer resting period between tests since not all the tests
were able to be performed at the same day. This demonstrate that time is a variable affecting
adhesion. When the adhesive and the adherent surface have contact bonds between both
substances start to create. When they first meet there is a fixating time where adhesive and
adherent sticks to each other but then time is needed to strengthen the bonding by increasing the
number of bonds during time. Akabori et al. [39] researched the effect time on the strength of an
adhesive concluding that times is indeed a variable for bonding strength.
‐ From section 3.3.6 looking at Figure 3.38 and Figure 3.39 the difference between fillers in bonding
strength can be observed. Graphite can be seen as the best filler overall. Boron‐Nitride exposed very
good results for its 30% compound. A big difference between these two fillers is that graphite is
electric conductor while Boron Nitride acts as an insulator. This makes both fillers a good choice to
make depending on the desired electrical conductivity of the TIM. Aluminum Nitride also yielded
good values when combined with EPS25 at 20 volume percentage.
It can be concluded when looking at these results that the EPS70‐4SH matrix is the best choice when
comparing the adhesive strengths, both from a relative and absolute perspective.
66
4.3 Thermalconduction
In section 2.5 the test for thermal conductivity is explained and in section 3.4.1 the thermal
conduction can be observed.
In Table 4.2 thermal conductivity of several materials is given to compare how well the synthesized
materials perform with respect to commercial TIM’s.
TIM’s(Source) Thermalconductivity[W/mK]
ThermallyConductiveAdhesives(TechFilm®) 0.31‐2.63
EPS70‐4SH‐40%Al 1.447
EPS70‐4SH‐30%AlN 0.952
EPS70‐4SH‐40%BN 1.191
EPS70‐4SH‐20%Copper 0.883
EPS70‐4SH‐40%Graphite 2.215
EPS25‐4SH‐40%Al 1.456
EPS25‐4SH‐30%AlN 0.919
EPS25‐4SH‐40%BN(aligned) 1.318
EPS25‐4SH‐20%Copper 0.793
EPS25‐4SHGraphite(aligned) 2.35
Pads(Chonerics®) 0.6‐0.7
Tapes(Chomerics®) 0.35‐0.4
Table 4.2 Thermal conductivity of several commercial TIM’s and best synthesized specimens per filler
First, the results for the specimens that were not aligned are discussed followed by the discussion of
the aligned specimens together with the SEM discussion
Discussion about the specimens not aligned
‐ As the value of the volume percentage of the filler increases it is expected to obtain higher
conductivity as seen in Figure 3.40. This is because the filler is a thermal conductor. Thermal
conduction refers to the easy of which the heat is transferred through the material. The more
67
material is present in the specimens that make the heat transfers easier, compared to a specimen
composed to only of Thioplast and a Crosslinker, the higher the thermal conductivity.
‐ Also from Figure 3.41 and Figure 3.42 it can be seen that EPS70‐4SH performs better than EPS25‐
4SH for all the fillers and their volume percentages.
‐ The difference in thermal conductivity between filler used can be seen in Figure 3.41 and Figure
3.42, from these graph it can be said that graphite is the best filler for thermal conductivity at high
volume percentages. Looking at Table 4.3 it can be seen that graphite has superior thermal
conductivity compared to the other fillers.
Material(Source) Thermalconductivity[W/mk]
Aluminum 237 (120‐180 alloys)
AluminumNitride 285
BoronNitride 600║; 30 ┴
Copper 401
Graphite 200–2000║; 2–800┴
Table 4.3 Thermal conductivity of the used fillers [40]
Discussion about the aligned specimens
To test if the filler particles could be aligned and if they would improve the conductivity of the
material materials where synthesized using dielectrophoresis. See section 1.3
From Figure 3.43 it can be seen that the dielectrophoresis did make a difference but only at higher
volume fractions. At low volume fractions the effect of the redistribution in average particle
separation distance in the direction of heat flow is too small to have a measurable effect.
Dielectrophoresis was used with the intention to not only orientate the particles to facilitate the
conductivity but also to try and cluster the particles in a way to facilitate the conduction as seen in
Figure 4.7.
Figure 4.7 Particle distribution a) Normally distributed b) Distribution after DEP
68
To find out if there was an alignment SEM pictures were conducted to see if there was cluster
formations.
‐ In section 3.4.3 the results from the SEM are given. First the results of a not aligned graphite sample
were given for comparison against aligned samples. A normal surface scanning image is given in
Figure 3.44. Disperse spectroscopy was performed to try to differentiate the different regions
composed by the matrix polymer and the filler, in this case graphite. Figure 3.45 gives the number of
hits obtaining for each element on the left side while the right side plots the founded elements in the
scanned surface.
It can be deduced form these images that the graphite is well dispersed through the matrix. Knowing
the amount of molecules in the surface the SEM gives as an approximation of the amount of each
founded elements. This can be found in Table 3.1. These values give an idea of the composition of
the surface in that particular area.
The next results given are from another graphite sample, the surface was polished to facilitate the
detection of particles and their alignment if any. This was done since the previous results were not
clear to differentiate what was polymer and what the graphite. Figure 3.46 and Figure 3.47 give
images for Graphite with 40%. Looking at then no clear particle alignment is spotted. Energy
Dispersion X‐Ray Spectroscopy was performed using low energy, up to around 5eV shown in Figure
3.48 left side. This was done to not to penetrate the surface much during the scanning as it. The
element distribution found can be seen from Figure 3.48 right side. No clear alignment was found
from the images taken and the data obtained. The volume percentage obtained from the SEM for
this specimen was given on Table 3.2.
Next the results for Boron Nitride were given. First images for 20% and 30% of Boron Nitride are
given followed by the Dispersion Spectroscopy for the 40%. A table of the volume percentages found
for the 40 volume percentage of Boron is also given, Table 3.3.
From the above results no alignment was spotted for Boron Nitride same as with graphite.
No particle separation or clusters were spotted. While looking for particles it was clear that they
were smaller than 1 µm, maybe in the nanometer range, when they were supposed to be around
5µm. This makes DEP difficult as mentioned in section 1.3.
Even so it was found that DEP worked and the results show an increase of thermal conductivity as
seen in Figure 3.43. Two theories could be applied here.
Particle rotation: It could be that the particles were not able to translate through the medium, in our
case the polymer matrix. Either the DEP force was too weak to produce translation or the viscosity
was too high. The increased effect can be explained in this situation by the rotation of the particles.
Some particles might have been rotated in line with the current [30].
Alignment in the surface: It has been observed that the surface of the specimens may contain less
filler content that the rest of the material. DEP might just affect the alignment on the surface by
bringing more filler content to the surface area. This facilitates the entrance and exit of the thermal
energy.
Various models have been tried and tested on different researches for thermal conductivity for best
fitting on their results i.e. Wattanakul et al. [41].For future work it would be a good idea to try model
69
the results obtained for our specimens. It was found that the Lewis–Nielsen model, equation (4.1),
has good predictability for thermal conductivity models [41]. This model however does utilize the
size of the particles. After looking at the SEM results it was concluded that the graphite morphology
differenced from the TEM results. Its particle size was greatly reduced during the specimen
preparation. Investigation is necessary on the mixed particle sizes. This is for modelling preparation.
11
(4.1)
where A and B are geometry factors, is the volume fraction of filler, is the maximum packing
density of filler, is the thermal conductivity of the polymer and k the thermal conductivity of the
compound.
It can be concluded that the Graphite makes the best filler when focusing on the thermal
conductivity. It can also be said that the alignment was favorable for amounts of 30% and higher. It is
recommended to model the thermal conductivity of aligned particulate composites to determine
requested degrees of alignment for substantial improvements in thermal conduction.
4.4 Valorizationstrategy
In this chapter a strategy is proposed to help choosing a compound between the many tested. To this
end all the results are handled to try to find an acceptable formula for their efficiency to
accommodate all the variations and give an idea of how well that material will perform compared
between the self‐made specimens.
The experiments conducted in the material were those that heals find out the characteristics of the
material according to the goal of the experiment. The goal of the experiment was to create a good
composite adhesive material to be used a thermal interface material while at the same time
containing self–healing and thermal conductivity properties. This means that the three major factors
involve to choose our material is their performance in:
Self‐sealing for their self‐healing property
Thermal conduction for their thermal conductivity property
The adhesive strength for their adhesive functionality.
The variations on the specimens will determine the variables for the quantification of the different
materials. These are:
The type of filler used: Aluminium, Aluminium Nitride, Boron Nitride, Copper and Graphite
The type of Matrix: EPS70‐4SH and EPS25‐4SH.
The volume percentage of filler present in the matrix
The alignment of the particles
These variables determine Table 4.4 shown below.
70
Form the results the efficiency determination of each specimen according to their three required
functionalities are explained.
Cohesion recovery efficiency: To obtain the efficiency of for the cohesion recovery, which represents
the self‐healing of the material, the next formula was used, see equation (4.2)
% (4.2)
Where H% is the healing recovery founded at the maximum exposed time te and tmin is the minimum
time a specimen was healed or the time the best specimen was healed.
Something to note is that this particular efficiency is not the real efficiency for all the materials
were % 100%. Since the healing is not linear, but is forms a curve when plotted see section 3.2,
it greatly depends on the when the test was stopped before complete healing. If the healing of a
specimen shows a healing recovery curve similar to a logarithmic function the end value of the
efficiency will become really low at % of 100 while the efficiency found will be much bigger.
Because of the above mentioned this efficiency should be taken as a soft referential value.
Adhesion recovery efficiency: To obtain this efficiency from the results the adhesive strength of all
the specimens was normalized against the largest value found. This was the case for EPS70‐4 SH with
20% volume percentage of Aluminium Nitride, its value will be called ∗ . The next formula,
equation (4.3) was used to calculate the efficiency for all the specimens:
∗ (4.3)
Where is the maximum adhesion strength for the current specimen.
Thermal recovery efficiency: To obtain these efficiency their founded conductivity values, k, where
normalized against the best value found, . This value belongs to EPS25‐4HS + 40vol% of
Graphite. This makes the formula:
(4.4)
71
All these efficiencies are separately shown on Table 4.4.
EPS25 EPS70
10% 20% 30% 40% 10% 20% 30% 40%
Aluminum
17 12 6 5 9 4 3 2
21 16 4 2 38 25 2 0
24 34 44 62 32 37 45 61
Aluminum Nitride
58 52 12 11 11 11
37 51 50 ‐‐ 72 100 73 ‐‐
20 28 40 21 30 39
Boron Nitride
92 42 11 8 35 15 9 7
24 43 90 53 26 49 95 60
18 (17) 25 (27) 37(40) 47 (56) 19 29 40 51
Copper
92 40 6 5
37 22 ‐‐ ‐‐ 23 26 ‐‐ ‐‐
29 34 31 37
Graphite
100 46 9 8 19 19 11 4
35 64 72 63 91 94 33 4
25 (25) 38 (41) 44 (75) 84 (100) 96 (86) 44 (44) 67 94
Table 4.4 Material valorisation – Cohesion (dark grey), Adhesion (light gray) and Thermal Conductivity empirical efficiencies‐ (Aligned)
This table only miss one detail, the desired properties a specific engineer or customer may want or
need for the material.
To further reduce these values to a single value per filler vs. their volume percentage the next
equation can be used on Table 4.4.
∗ ∗ ∗ (4.5)
Where a, b and c are factors representing the importance of their corresponding efficiency for
choosing a specimen. The next should hold:
0 , , , 1 1
72
An example of the reduction of Table 4.4 using equation (4.5) is given in Table 4.5, taking a=b=c=1/3.
EPS25 EPS70
0 0 0 0 0 0 0 0
Aluminum
21 21 18 23 26 22 17 21
Aluminum Nitride
39 44 34 ‐‐ 35 47 41 ‐‐
Boron Nitride
45 (44) 36 (37) 46 (47) 36 (39)
26 31 48 39
Copper 53
32 ‐‐ ‐‐ 20 23 ‐‐ ‐‐
Graphite 53 (35) 49(50) 42 (52) 52 (57) 69 (65) 52 (52)
37 34
Table 4.5 Example for factors a=b=c=1/3
Looking at the above table EPS70 + 10%Graphite would be taken as the best choice.
A valorisation technique was found that can be used as an indication for the most suitable material
depending on the engineering needs for a given application. The accuracy of this valorisation
technique will improve with the reliability of the cohesion results.
73
5 Conclusions
Throughout this research the results of this project have indicated that competitive TIM’s with
adhesive properties can be synthesized to have self‐healing properties. The cohesion, adhesion and
thermal conductivity experiments support this result.
The two polymer matrices used in this work, deriving their self‐healing ability from the reversible
sulfur‐sulfur bond formation, both showed attractive and fast cohesive and adhesive self‐healing
behaviour upon healing to 65‐1000C. Furthermore, the polymers had good processability
characteristics making it possible to create sound composite materials with loading fraction of up to
40% inert granular particle loadings.
From the cohesion experiments it can be concluded that Graphite and Boron Nitride both impact the
efficiency of the self‐healing effect the least, and are therefore the best suited fillers to be used for
the manufacturing self‐healing TIM’s. In order to confirm these results, it is recommended to conduct
more test with the same material configuration. The best material for cohesion was found to be
EPS25‐4SH‐10% Graphite completely recovering within 10 min at 650C and EPS25‐4SH‐10% Boron
Nitride completely recovering within 10 min at 1000C.
There is a maximum of adhesive strength, for non‐metallic fillers, between a volume percentage of
15% and 30%. The adhesion tests have shown that the amount of filler necessary to increase the
adhesive strength depends on the type of filler used. For Aluminium Nitride and Boron Nitride a filler
content of 20% and 30% respectively have been shown to facilitate this increase. EPS70‐4SH‐20% AlN
was the best composite with 5.44 MPa lap hear strength followed by EPS70‐4SH‐30% BN with 5.17
MPa lap hear strength.
The thermal conductivity of the manufactured TIM’s increases with the filler content. At these high
volume contents of filler, the thermal conductivity increases even more by structuring with DEP. The
increase in thermal conductivity, as compared to the non‐aligned samples, only occurs above 20% for
Graphite and 30% for Boron Nitride. This makes DEP a recommended process to increase the thermal
conductivity without having to increase the filler content of the compound. EPS25‐4SH‐40% Graphite
had an increase of 19.1% in thermal conductivity using DEP process, while EPS25‐4SH‐40% BN had an
increase of 19.5%. Construction of a model of the thermal conductivity as a function of the filler
content is recommended. The best synthesized specimen was EPS70‐4SH‐40% Graphite aligned with
a thermal conductivity of 2.35 W/mK.
Both Graphite and Boron Nitride favourably affect the thermal conductivity, self‐healing and
adhesive properties as TIM’s as compared to all the other investigated fillers. From the results it can
be said that Graphite is the most favourable filler material to increase the thermal conductivity of
TIM’s up to 20%. Higher values of volume percentages show that Boron Nitride becomes more
favourable. This should be corroborated with more empirical results.
The engineering application itself should be the deciding factor on which filler to use since Graphite
is an electrical conductor while Boron Nitride is an insulator.
74
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