thermally conductive polymer-based composites for electronic packaging applications

1

Thermally Conductive Polymer-Based Composites

for Electronic Packaging Applications

AHMED MAHMOUD

A thesis submitted in partial fulfillment

of the requirements for the degree of

BACHELOR OF APPLIED SCIENCE

SUPERVISOR: DR. HANI E. NAGUIB

Department of Mechanical and Industrial Engineering

2

Abstract

The objective of this thesis was to develop an electrically-insulative material with a

high thermal conductivity for electronic packaging applications. A heat-transfer

analysis study found that a thermal conductivity of at least 10 W/m.K would be

required in order to provide a viable alternative to the current electronic packaging

and heat sink assembly. To that end, a composite comprising a poly(p-phenylene

sulphide) matrix and Boron Nitride filler was investigated. The choice of matrix was

predicated upon the need to use a resin which has a low melt viscosity and excellent

affinity with the filler to ensure that air gaps within the composite are minimized,

while the choice of filler was based upon the favourable thermomechanical properties

of Boron Nitride, as well as encouraging previous research. Initial thermal

conductivity testing as well as SEM analysis using four different grades of Boron

Nitride singled out one polymorph – PTX60 – for further study; due to its spherical

shape, it allowed for maximization of filler-packing throughout the matrix, thereby

increasing the likelihood of filler-filler contact and reducing the percolation

threshold. At 7.8 W/m.K, however, the highest obtained thermal conductivity was

well below the goal of the thesis, as well as theoretically-predicted values. It was

conjectured that this was due to high interfacial resistance resulting from

incompatibility between the Boron Nitride and the matrix. This issue was addressed

by surface-treating PTX60 with a coupling agent, which was shown in SEM images to

enhance the adhesion of Boron Nitride to the matrix, thereby reducing phonon

scattering at interfacial barriers and lattice defects, and bringing the percolation

threshold within reach. The final result was a 13% improvement in thermal

conductivity, achieving a very remarkable value of 8.8 W/m.K using 74 wt% Boron

Nitride in a poly(p-phenylene sulphide) matrix. Methods to increase this value to the

desired 10 W/m.K, including use of multi-modal Boron Nitride filler and a novel

epoxy matrix, are explored at the end of the report.

3

Table of Contents

I Introduction............................................................................................................................... 1

1.1 Heat Transfer Analysis .............................................................................................................. 2

II Literature Review ...................................................................................................................... 5

2.1 Polymer Research..................................................................................................................... 5

2.2 Boron Nitride Research ............................................................................................................ 6

2.3 Percolation Theory and Previous Research on Fillers .............................................................. 7

III Phase One: Preliminary Research using Single-Phase and Hybrid Fillers .................................... 8

3.1 Methodology .......................................................................................................................... 10

3.2 Results .................................................................................................................................... 13

3.2.1 Single-Phase Composite Results ............................................................................ 13

3.2.2 Hybrid-Filler Composite Results ............................................................................. 16

3.3 SEM Analysis .......................................................................................................................... 18

3.2.1 Methodology .......................................................................................................... 18

3.3.2 SEM Micrograph Results ........................................................................................ 19

3.3.2.1 Single-Phase Composite Micrographs ................................................... 19

3.3.2.2 Hybrid-Filler Composite Micrographs ................................................... 21

3.4 Compression Molding Pressure Analysis ............................................................................... 24

IV Phase 2: Coupling Agents ........................................................................................................ 28

4.1 Background Research ............................................................................................................. 28

4.2 Methodology .......................................................................................................................... 30

4.3 Thermogravimetric Analysis (TGA)......................................................................................... 31

4.3.1 Methodology .......................................................................................................... 31

4.3.2 Results .................................................................................................................... 32

4.3.2.1 Calibration .............................................................................................. 32

4.3.2.2 PTX60 vs. PT110 ..................................................................................... 32

4.4 Design of Experiments ........................................................................................................... 36

4.5 Thermal Conductivity Results................................................................................................. 40

4.6 SEM Analysis .......................................................................................................................... 43

V Future Research Directions ...................................................................................................... 46

5.1 Multi-Modal hBN Fillers ......................................................................................................... 46

5.2 Ishida Method ........................................................................................................................ 47

5.2 Multifunctional Fillers ............................................................................................................ 48

VI Conclusion.............................................................................................................................. 49

1

Figure 1: An Aluminum heat sink and fan

I Introduction

As electronic devices are made smaller and more

powerful, they generate more heat in a smaller

volume of space, and so the need arises to develop

optimum heat dissipation solutions. Heat sinks are

used to transfer the heat generated by the

processor or chipset to the surrounding air; these

heat sinks are traditionally made out of a metal,

usually Aluminum, fabricated into a multi-fin arrangement to maximize heat dissipation.

However, Aluminum has a high electrical conductivity, which prompts the need for

micro-processor packaging solutions to prevent the heat sink from short-circuiting the

processor. [1] These packages are usually made of a copolymer, such as epoxy, which has a

high electrical resistivity and excellent processability, but also a low thermal conductivity

– in the range of 0.1 to 0.5 W/m.°K – which reduces the overall effective heat dissipation

of the heat sink. [2]

To address this problem, researchers have experimented with composites which

could exhibit both a high thermal conductivity and a low dielectric constant, the aim

being to develop a material which would perform the function of a heat sink, while

forgoing the need for electronic packaging. They started by embedding ceramic fillers,

such as alumina (Al2O3) [3], silica (SiO2) [4], aluminum nitride (AlN) [5][6][7], and boron

nitride (BN),[8][9][10] in a polymer matrix. Among these materials, hexagonal BN (hBN)

showed the greatest potential due to its high thermal conductivity (up to 400 W/mk) and

relatively low dielectric constant, compared with SiC, Al2O3, and AlN, which suffer from

high reactivity with moisture and a poor affinity with resin. Further, hBN exhibits

excellent resistance to oxidation and chemical corrosion. [11]

For the matrix, a wide array polymers have been explored by researchers to varying

success. Two polymers in particular have proven to be good candidates: poly(p-phenylene

sulfide) (PPS) and Low-Density Polyethylene (LDPE). Both exhibit similar thermal

2

properties but have slightly varying mechanical properties owing to differences in

molecular weight and degrees of cross-linking. [12] Though they are not as good as

epoxies in terms of affinity to BN, they are the best thermoplastic choices available since

they are easily processable.

The thermal conductivity of the polymer-filler composite can be maximized by

minimizing thermal barrier resistance along the heat flow path and forming a thermal

conductive network in the composites. Once a conductive network is formed by the filler,

the composite shows percolation behaviour, i.e., the thermal conductivity increases

steeply.

The objective of this thesis was to expand on current research on thermally-

conductive polymers in order to develop prototypes a composite with a ceramic filler, in

order to achieve a high thermal conductivity but low electrical conductivity.

1.1 Heat Transfer Analysis

Heat transfer across the heat sink can be modeled by a series of heat resistors between

the processor and ambient air

representing:

1. The epoxy packaging which

has a thermal conductivity

of ~0.3 W/m.K [13]

2. The thin layer of thermal

compound used to promote

heat conductivity from the

processor; a typical silver-

based thermal compound

has a thermal conductivity

of approximately 5 W/m.K

3. The Aluminum heat sink,

the thermal conductivity of which is 237 W/m.K

4. Heat convection from the heatsink

TAmbient

Rconvection

3

For this analysis, the following assumptions are made:

• The thickness of the epoxy packaging is 1 mm and that of the thermal compound is

0.5 mm

• The height of the heat sink is 10 cm

• The processor has the same dimensions as an Intel LGA775 socket processor: 0.6 in

x 0.6 in [14]

• Heat loss is by simple convection only, and therefore the heat transfer coefficient

is given by

ℎ =�

�∆�

where:

h = heat transfer coefficient, W/(m2K) q = heat flow in input or lost heat flow , W A = heat transfer surface area, m2

ΔT = difference in temperature between the solid surface and surrounding fluid area, which is �� − ��

A study by Rebay et al found that the heat transfer coefficient for a typical commercial

heat sink is roughly 49W/m2K. [15] This factor is a function of the geometry of the heat

sink and not the material from which it is made.

Therefore, calculating the effective heat resistivity across a commercial heat sink, we get:

�� = �� + �� + �� ,�� + ��

=!��

"�� +

!��

"�� +

!��

"�� +

1

ℎ�

=0.001

0.35 × (2.3 × 10+,)+

0.0005

5 × (2.3 × 10+,)+

0.1

237 × (2.3 × 10+,)+

1

49 × (2.3 × 10+,)

= 103.4 °2

3

4

If we are to replace the current arrangement with just a single heat sink that incorporates

the electronic packaging, only two resistivies exist: one due to the composite heatsink and

the other due to convection. Therefore:

�� =!��

"�� +

1

ℎ�

where Lcomposite is the height of the heat sink which, as stated above, is 10 cm.

Then the required k for the composite is:

"�� =!��

(�� −1

ℎ�� ) �

=0.1

(103.4 −1

49 × (2.3 × 10+,))(2.3 × 10+, )

= 29.63

5. 2

This figure approximates the thermal conductivity required by the composite which

would result in the same dissipative power as the current Aluminum heatsink

arrangement. However, due to time constraints, the target keff for this thesis is set to for

10 W/m.K, which is a more realistic expectation.

5

II Literature Review

There exists a substantial body of literature on attempts to develop thermally-conductive

composites for enhanced electronic packaging applications. This section summarizes the

research that has been done on the topic in the run-up of to experimental prototyping.

2.1 Polymer Research

Most studies were carried out using a polymer or epoxy for the matrix, the reason

being that they are affordable, easily processed and have a low dielectric constant [16].

However, almost all polymers have very poor thermal conductivities due to their

semicrystalline nature; specifically, in a spherulitic polymer, the chains fold into highly

ordered crystalline lamellae, but are separated by amorphous regions that disrupt phonon

heat transport (by scattering), therefore resulting in poor thermal conductivity. [17]

Therefore, it becomes important to choose a polymer which has a low viscosity so that it

is easily processed, has a high tendency to crystallize to promote thermal conductivity, a

high service temperature to withstand the heat generated by the processor, and most

importantly, it must allow for excellent filler dispersion. Research indicates that two

particular polymers: poly(p-phenylene sulfide) (PPS), Liquid Crystal Polymer (LCP), and

polyethylene (PE) are excellent candidates based on these criteria. [18][19] Whereas PPS is

chosen for its “outstanding mechanical properties, high thermal stability, and good

solvent resistance,” LCP and PE are equally as qualified for our application; though they

have slightly lower thermal conductivity than PPS, they can be stretched and aligned to

produce a high uni-directional thermal conductivity. A recently-published and critically-

acclaimed study by Shen el al. reported achieving thermal conductivities as high as 104

W/mK using high-quality ultra-drawn polyethylene nanofibres. The high thermal

conductivity achieved is attributed to “the restructuring of the polymer chains by

stretching, which improves the fibre quality toward an ‘ideal’ single crystalline fibre.”[20]

The methods used to achieve these results, however, are expensive and time consuming,

so the focus for now will be on embedding filler materials within a PPS matrix to the

desired thermal conduction network.

6

Figure 2: Hexagonal Boron Nitride Crystal Structure

2.2 Boron Nitride Research

Boron nitride exists in several allotropic forms; most commonly, it assumes one of

two structures: hexagonal (hBN, similar to graphite), and cubic (cBN, similar to

diamond). The hexagonal form is extremely soft and has a layered structure, where Van

der Waal’s forces hold sheets of covalently bonded boron and nitrogen atoms together.

As a consequence of the layered structure, hBN

crystals are anisotropic. This anisotropy is clearly seen

in the thermal conductivity: “The in-plane thermal

conductivity [for hBN] has been measured to be more

than 300 W/mK, and is attributed to good conduction

of phonons through boron nitride bonds, whereas the

through-plane conductivity has been measured to be

only about 3 W/mK, a significant difference, most likely due to poor phonon transfer

across layers.”[29]

Numerous studies have been carried out that

confirm the ability of Boron Nitride to show

percolation in a polymer matrix, thereby resulting in a

high thermal conductivity composite. One such study

by Sato et al was able to achieve a thermal conductivity

of 7 W/mK.

Using a polyimide matrix embedded with 60%

hBN.[30] On the other hand, Yung et al were able to

achieve 20 W/mK using multimodal (hybrid) fillers of

hBN and cBN.[31] Their results are shown in figure 3 on the right.

Much higher values for composite thermal conductivity have been obtained in other

studies, one of which is briefly touched on in section V.

Figure 3: Yung et al’s results for thermal conductivity of BN

resins with various filler contents.

7

2.3 Percolation Theory and Previous Research on Fillers

Previous studies indicate that embedding highly-conductive ceramic filler particles

in the polymer matrix is the most widely used method to develop a composite with high

thermal conductivity. The process which governs the enhancement in thermal

conductivity is called Percolation, which is a phenomenon in which the highly

conducting filler particles form at least one continuous low-resistance chain connecting

the opposite faces of the matrix. Percolation theory predicts that the thermal conductivity

of the composites increases according to a scaling law with increasing concentration of

the high thermal conductivity constituent after percolation. However, “when the

characteristic size of the particles in the nanocomposites is comparable to or smaller than

the phonon mean free path, the phonon scattering at interfaces between two materials

can introduce significant thermal resistance in the highly conductive phonon pathway.

Such interfacial thermal resistance can reduce the thermal conductivity of the

nanoparticle composites.” The thermal conductivity of the random composites thus

deviates significantly from the predictions of the percolation theory. [21][22]

In early studies on the topic, oxide fillers such as alumina (Al2O3) and silica (SiO2)

were used due to their affordability and processability in mixing procedures. However,

they have always yielded poor results inasmuch as the thermal conductivities of the oxide

filler composites were at most 1–3 W/mK. [23] Subsequent research focused on nitride

ceramics, particularly Aluminum Nitride (AlN) and Boron Nitride (BN), which are now

considered the best qualified fillers for thermally-conductive polymers. [24][25] Both

exhibit very high thermal conductivities, as evident in table 1, are affordable, and they

disperse well in polymers.

Table 1: Thermal Properties for Various Materials [26][27]

Material Density

(g/cc)

CTE

[ppm/°K]

Specific Heat

[J/kg-°K] @ 25°C

Thermal Conductivity

[W/m°K]

Boron Nitride 2.25 1.20 794 300+

Aluminum Nitride 3.26 4.10 734 260

Aluminum Oxide 3.98 7.1 798 30

Silica 2.20 0.5 689 1.4

Zinc Oxide 5.64 0 [28] 523 54

8

III Phase One: Preliminary Research using Single-Phase

And Dual ‘Hybrid’ Fillers

Based on the findings in the last section, it was decided to go forward with PPS and

Boron Nitride as the baseline constituents of the composite. This was primarily due to their

favourable properties as postulated by previous research.

In line with that strategy, the aim of this research phase is to gain an understanding of

how different amounts and types (polymorphs) of Boron Nitride embedded in a PPS matrix

would affect the thermal conductivity of the composite by conducting a battery of tests using

as many different compositions as possible.

Two different parameters known to affect thermal conductivity are going to be explored in

this section

1. Type of Boron Nitride: Four different polymorphs of hexagonal Boron Nitride

comprising different shapes and sizes were decided are going to be used in order to

compare their performance1. SEM images, along with physical properties, of these

polymorphs can be seen in the figure 4 below.

1 Obtained from Momentive Performance Materials, Inc.

Figure 4: SEM micrographs of the polymorphs of Boron Nitride which will be tested in this thesis

9

2. Amount of Boron Nitride in a thermal conductivity sample: Based on previous

research, we know that the higher the Boron Nitride content in the composite, the

high the thermal conductivity. However, there is both a theoretical and practical limit

as to how much Boron Nitride one can embed in a composite.

The theoretical limit can be easily determined by calculating the maximum theoretical

atomic packing factor (APF) of Boron Nitride spheres in the PPS matrix:

�67 =898:; <=ℎ>?> @9;A5>

898:; 7BB ACD8 E>;; @9;A5> =

FG

FH=

(163 )I�J

16�J√2= 0.74

This then tells us that the composition at which the Boron Nitride particles are closest

packed in the PPS matrix is 74 wt%. At this composition, however, the sample is

speculated to be too brittle to be viable. Therefore, an additional composition – 33

wt% Boron Nitride – will be tested in order to establish a meaningful relationship

between Boron Nitride content and Thermal Conductivity.

In addition to the above tests, we will explore the effect of using hybrid-filler composites,

containing 2 or more polymorphs of Boron Nitride, on thermal conductivity. The purpose

behind these tests is to attempt to maximize the thermal conductivity by combining the

positive effects of various shapes and sizes of Boron Nitride in the same matrix.

We will then conclude the section by analyzing a number of SEM micrographs of a

representative number of compositions in order to examine the morphologies of the

prototyped samples.

10

3.1 Methodology

For the thermal conductivity tests, a 2 cm diameter disc-shaped prototype is used. The

steps involved in making the fabricating this sample are as follows:

1. The constituents for the desired composition are weighed using a digital scale then

mixed thoroughly in a glass container.

2. The mixture is then placed in a compounder which melts the constituents and

then, using a pair of screws, extrudes the mixture into a long strand [32]. The

purpose of this process is to ensure that the filler particulates are properly

distributed and well dispersed within the polymer matrix

3. The strands are then inserted in a freeze mill which pelletizes them into a finely-

ground thoroughly dispersed powder. This is done by cooling the sample using

liquid nitrogen to make it sufficiently brittle and then hammering it into a powder;

the process is carried over three 2-minute cycles in order to give the hammer and

sample time to cool down before continuing to grind it down. The end result is a

thoroughly-mixed powder consisting of the polymer and filler(s)

4. The powder samples are then inserted in the mold and are compacted at room

temperature under 2000 psi to ensure that the powder solidifies in the mold before

moving on to the next sample. Otherwise, the power might be blown away as the

other samples are added.

11

5. Finally, when all samples are compacted, they are molded at 310°C and 2000 psi

for 15 minutes. The mold is then quenched in ice-cold water and the discs are

removed.

Two molds may be used which produce different sized samples: one is used for thermal

conductivity analysis, and is 1 cm in diameter and 2 cm thick. The other is used for SEM

inspection, and is the same diameter but only 1 cm thick in order to be easily shattered

during SEM preparation.

If the composition of the sample is over 45% BN or 20% CNT, the compounder is

unable to process the blend since it becomes too viscous, and it would therefore have to

be dry-blended directly using the compression molder. This entails weighing out and

mixing the samples in a glass container by shaking the container by hand – to ensure the

constituents are well dispersed – compacting them individually in the mold, and then

finally compressing them at 310°C, 2000 psi.

This method produces samples in which the filler is poorly dispersed in the polymer since

the compounding and freeze milling steps are forgone.

The final step is to then measure the thermal conductivity of the samples using a custom-

built analyzer which conforms to ASTM standard E-1255-04[33].

This is carried out by placing the test specimen under load between two steel bars having

the same diameter as the specimen. A heater at the top of the test stack is then turned on

and a temperature gradient is established across the stack; heat losses are minimized by

use of a thick insulation layer as well as a longitudinal guard having approximately the

same temperature gradient. At equilibr

measured temperature gradients in the respective specimens and the thermal

conductivity of the reference materials by using the following equation:

" =L

�

where,

Zi are positions measured from the top of Ti are temperatures at Zi kM is the thermal conductivity of the met

This calculation is carried out through software which monitors the temperatures across

the gradient using 9 thermocouples.

Figure 5: Schematic of the thermal conductivity analyze showing the comparative

Guard Heater

Section

Metal or

ceramic guard

shell at Tg

12


same temperature gradient. At equilibrium, the thermal conductivity is derived from the

gradients in the respective specimens and the thermal

conductivity of the reference materials by using the following equation:

L, − LJ

�, − �J."M

2. (

�N − �O

LN − LO+

�P − �Q

LP − LQ)

are positions measured from the top of the column and given by figure 5

is the thermal conductivity of the metal reference bars


the gradient using 9 thermocouples.

Schematic of the thermal conductivity analyze showing the comparative-guarded longitudinal heat


, the thermal conductivity is derived from the

gradients in the respective specimens and the thermal

5


guarded longitudinal heat flow system

13

3.2 Results

In line with the introductory discussion, 13 samples with different compositions were

prepared and tested for thermal conductivity. Six of those samples were single-phase

composites, meaning they contained only one polymorph of Boron Nitirde, while the

other four were hybrid (dual) composites, comprising two different polymorphs of Boron

Nitride, dispersed in a PPS matrix.

3.2.1 Single-Phase Composite Results

The purpose of the single-phase tests was two-fold:

1. To understand how different polymorphs of Boron Nitride affect the thermal

conductivity of BN-PPS composites: This is accomplished by testing 4 different

samples each containing the same concentration (33 wt%) of Boron Nitride but

with different polymorphs

2. To determine how much thermal conductivity increases with increasing Boron

Nitride concentration in the composite (from 33 wt% to 74 wt%)

0

1

2

3

4

5

6

7

8

9

Pure PPS PTX25 PTX60 PT371 PT110

Th

erm

al

Co

nd

uct

ivit

y (

W/m

.K)

Chart 1: Thermal Conductivity Results For Different Polymorphs of Boron Nitride

33 wt% Boron Nitride

74 wt% Boron Nitride

14

Looking at the chart 1 on the previous page, we observe that, for 33 wt% Boron Nitride

composites, three of the polymorphs, PTX25, PTX60 AND PT371, have an identical effect

on thermal conductivity, raising it only slightly above that of neat PPS. PT110, on the

other hand, performs relatively poorly, falling almost 30% short of the thermal

conductivities attained by the other polymorphs. This may be due to the fact that the

PT110 platelets are pulverized, or otherwise flattened across the width of the sample,

during compression molding, therefore diminshing the thermal network which forms

across the matrix and resulting in a breakdown of percolation. In fact, this is true of all

the other polymorphs, though to a lesser extent than in the case of PT110. Using a

modified version of the Maxwell-Garnett formula:

we can estimate that the theoretical thermal conductivity of a composite consisting of 33

wt% Boron Nitride within a PPS matrix to be 44 W/m.K, which is well above any of the

obtained results[46].

Generally speaking, this discrepancy between theoretical and experimental thermal

conductivities is due to a high thermal resistance at the interfacial boundaries between

PPS and the Boron Nitride particulates due to

the inherent incompatibility of the two

compounds. This issue can be resolved using

coupling agents, which will be addressed in

section III.

Another reason for the deviation of results from

theoretical predictions is due to the imperfect

dispersion of Boron Nitride in the PPS matrix.

Since the only method used to mix the two

Figure 6:

Schematic

showing (a)

theoretical, (b)

(likely) actual

packing of BN

particulate

fillers in PPS

matrix

15

components is manual shaking, there is usually an uneven distribution of matrix and filler

powders during compression molding. As a result, filler particulates tend to clump

together into clusters throughout the matrix with regions of pure PPS in between, rather

than percolating by arranging into a proper close-packed geometry as can be seen in

figure 6 on the previous page.

Referring back to chart 1 on page 13, we observe that increasing the Boron Nitride content

of the samples vastly improved their thermal conductivity. At 7.8 W/m.K, PTX60 achieves

the highest thermal conductivity attained so far, edging out PT371 by about 0.4 W/m.K.

The reason for this slight discrepenacy relates to differences in the microstructures of the

PTX60 and PT371 composites which will be explored in detail the next section using SEM

micrographs.

Since 74 wt% Boron Niride implies that most of the sample is

ceramic in nature, prototypes which were fabricated at this

composition very brittle and difficult to handle. In fact, all

samples containing 74 wt% PTX25 and PT110 fractured either

during molding or drilling, and so were rendered un-testable

(see figure 7a).

Though the value achieved for 74 wt% PTX60 is encouraging, it is not recommended to

develop a material with such a high content of ceramic since it would be very difficult to

machine into a multi-fin heatsink. In addition, it will be liable to fail due to fatigue early

on in its lifecycle as unstable cracks would propagate very quickly after initiating at sites

of stress concentration, such as at the corners of the fins.

Figure 7a: Cracked 74 wt% PTX25 sample

16

3.2.2 Hybrid Filler Composite Results

As was pointed out in the

previous section, one of the

two main reasons behind

the discrepancy between

empirical predictions of

thermal conductivity and

experimental results is due

to the coalescence of the

Boron Nitride particulates

in the matrix during

compression molding, leaving vast regions of poorly-conductive PPS across the

composite.

To address that issue, dual-phase PTX60:PTX25 hybrid fillers were attempted, predicated

on the understanding that PTX25 spheres are small enough to fit in the interstitial sites

between the larger PTX60 spheres, thereby achieving an ordered arrangement of filler

particulates in the matrix and forming the desired thermal conductivity network.

At 33 wt% Boron Nitride, three different samples with different ratios of PTX60 to PTX25

were prototyped and tested in order to determine the optimal proportion in the sample

which would ensure the highest thermal conductivity; these ratios are 2:1, 3:1 and 4:1

PTX60:PTX25. Looking at the results in chart 2 above, we notice that there is a weak,

though positive correlation between the ratio of PTX60:PTX25 and thermal conductivity.

Based on these results, we can hypothesize that PTX60 has a better thermal conductivity

in Boron Nitride-PPS composites than PTX25 since, in samples containing identical

amounts of boron nitride but with different ratios of PTX60 and PTX25, increasing the

proportion of PTX60 in the sample resulted in an increase in thermal conductivity of the

composite.

0

1

2

3

4

5

6

2:1

PTX60 : PTX25

3:1

PTX60 : PTX25

4:1

PTX60 : PTX25

15:1

PTX60 : PT110

Th

erm

al C

on

du

ctiv

ity

(W

/m.K

)

Chart 2: Thermal Conductivity Results For Hybrid-Filler BN Composites

17

We also conclude that the assumption made regarding better percolation was not fulfilled

since there is almost no improvement in thermal conductivity using hybrid fillers than

one-phase fillers, both of which achieve ~2 W/m.K at 33 wt% Boron Nitride, which is well

below our target of 10 W/m.K. The underlying reasons for this, and as to why PTX60

performs better than PTX25 will be explained using SEM micrographs in the next section

In addition to the PTX60:PTX25 hybrid-filler composites, one sample containing 74%

PTX60 and 5% PT110 – a 15:1 ratio of PTX60:PT110 – was tested. This was based upon the

assumption that the crushing of PT110 platelets during compression molding may serve to

disperse them throughout the matrix, thereby connecting together the PTX60

particulates in the matrix; this then forms an interconnected network of highly-

conductive Boron Nitride particulates throughout the matrix, leading to a high thermal

conductivity.

The result, however, indicates that this is not the case; at 5.6 W/m.K, the thermal

conductivity of the hybrid-filler sample is 40% less than the 74 wt% PTX60 sample, which

suggests that PT110 particulates have a detrimental effect on thermal conductivity. Likely

this is due to the high incompatibility between the PT110 platelets and PPS, leading to a

high thermal resistance at the interfacial boundaries. As was mentioned earlier, this

problem may be addressed by treating the Boron Nitride with a compatibilizing agent to

improve its bonding to the matrix. However, in the case of PT110, even if surface

treatment is carried out, the platlets will still tend to line up across the width of the

specimen, therefore providing asymmetric thermal conductivity in the composite.

A 15:1 PTX60:PTX25 sample was also prototyped, but due to excessive brittleness, it

shattered during extraction from the mold.

18

3.3 SEM Analysis

The Scanning Electron Microscope (SEM) is a powerful tool which can provide us with a

valuable insight into the microstructure of the prototypes , giving information about

dispersion, morphology, percolation and integrity of the sample. Faults such as cracks or

air pockets, which elevate thermal resistivity within the composite, can also be identified

on the micrographs.

3.3.1 Methodology

Two methods were used to obtain SEM samples for

analysis: The first was to compression-mold a thin disc

specially made for SEM analysis (see figure 7b); the

second was to cut slots into thermal conductivity

samples using a band saw after they were tested using

the thermal conductivity analyzer. After that, the following steps are carried out [34]:

1. The sample is dipped in liquid nitrogen for about one minute then, using a pair to

tongs, snapped in order to expose a clean fracture surface with good topology for

analysis.

2. Next, the sample is mount sample onto stub using glue

3. The surface is then polished with SiC sandpaper in order to enhance grain

boundaries

4. The metallic stub is covered with Carbon Black in order to insulate it so that it

doesn’t interfere with the electron beam

5. The sample is then sputter-coated with a 7.5 – 30 nm gold platinum layer at ~ 10 Pa

in order to impart electrical conductivity to the fractured surface. This results in a

higher rate of secondary and backscattered electron emissions which would yield a

higher resolution image. If the sample is not properly coated, the samples

accumulate charge when scanned by the electron beam, which can cause beam

Figure 7b: 74 wt% PT371 SEM sample

19

deflection and increased emissions of secondary electrons which cause scanning

faults and other image artifacts.

6. Finally, the samples are placed under the microscope, analyzed, and photographed

3.3.2 SEM Micrograph Results

As with before, analysis was carried out on both single-phase and hybrid-filler

composites. All samples were imaged at 50x, 500x and 1000x magnifications in order to

provide a cascade of morphology, from a macro overview to a high-resolution insight into

the grain structures of the composite constituents.

3.3.2.1 Single-Phase Composite Micrographs

SEM analysis was carried out on composites consisting of 74 wt% PTX25, PTX60 and

PT371, as well as 33 wt% PTX60 and PT371 in a PPS matrix.

The purpose behind analyzing these compositions is to show us how different

polymorphs of Boron Nitride disperse within the PPS matrix, how well they retain their

shape after compression molding, and to confirm the hypotheses postulated in section

3.2.2 regarding the thermal conductivity results obtained for these compositions.

SEM micrographs of the aforementioned compositions can be seen in the following two

pages.

20

Figure 8: 74% PTX25 in PPS matrix at 50X, 500X and 1000X respectively

Figure 9: 74% PTX60 in PPS matrix at 50X, 500X and 1000X respectively

Figure 10: 74% PT371 in PPS matrix at 50X, 500X and 1000X respectively

21

Figures 8, 9 and 11 show the Boron Nitride PTX25 and PTX60 spheres have largely

disintegrated during compression molding, resulting in a breakdown of their thermo-

mechanical properties.

This breadown occurs when Boron Nitride sheets slip past one another as they are

compressed under a high pressure, thereby deforming the hexagonal structure of the

Boron Nitride crystal. This results in steep changes in its crystallographic directions,

resulting in phonon scattering both within the Boron Nitride crystals and at the

interfacial barrier between Boron Nitride and PPS [31]. This scattering is the root cause of

the poor thermal conductivities obtained in the previous section. Therefore, the next

section (3.4) will attempt to address the issue of Boron Nitride pulverization during

compression molding by adjusting the process conditions

Figures 10 and 12 shows a similar pattern with the PT371 agglomerates broken down into

small flakes randomly dispersed throughout the matrix; these flakes are not only poorly

conductive relative to their intact counterparts, but they are also spaced apart in the

matrix, and therefore not forming a proper 3D thermal conductivity network.

3.3.2.2 Hybrid-Filler Composite Micrographs

As with the single phase samples, SEM analysis was conducted for two compositions, 15:1

PTX60: PT110 (74% PTX60, 4% PT110), and 15:1 PTX60:PTX25, which can be seen in figures

13 and 14 on the next page.

Figure 11: 33% PTX60 in PPS matrix at 500X Figure 12: 33% PT371 in PPS matrix at 500X

22

Figure 13: 74% PTX60 + 5% PT110 in PPS matrix

micrographs at 50X, 500X and 1000X respectively

Figure 14: 74% PTX60 + 5% PTX25 in PPS matrix

micrographs at 50X, 500X and 1000X respectively

23

In both samples, it is clear that, despite good dispersion, there is severe breakdown of the

Boron Nitride particulates in the matrix. This is due to the fact the matrix is inundated

with copious amounts of Boron Nitride (79 wt% in total), which results in their

immediate pulverization as they press up against each other during compression

molding. This is particularly apparent in figure 14, where it can be seen that both

polymorphs of Boron Nitride have completely broken down. On the other hand the

sample in figure 13 shows that some particulates retained their integrity during

compression molding. Nevertheless, the disintegration of was so extensive, that we

cannot consider either composition viable.

24

3.4 Compression Molding Pressure Analysis

As was mentioned in the last section, Boron Nitride particulates undergo extensive

damage due to the high pressure (2,000 psi) sustained during compression molding. This

prompts us to attempt to understand how we can address this issue; particularly, how

varying this pressure may produce better percolation.

Pressure plays a huge role in determining the final morphology of compression-molded

samples. In the case of ceramic-polymer composites, there are two dimensions to the

effect of pressure:

1. On the polymer matrix: The effect of molding pressure on the thermo-

mechanical properties of mouldable polymers has been extensively studied and is

widely understood. One paper by Parasnis and Ramini summarized this effect very

well; by conducting compression molding runs on samples compressed at different

pressures, they found that the stiffness and crystallinity of the molded polymer

increased as the pressure is increased. Past a certain pressure, these characteristics

decline rapidly, thereby diminishing the thermo-mechanical integrity of the

molded samples. That is to say, they found that there is a narrow pressure band in

which the crystallinity and stiffness of the polymer are maximized. For thermal

conductivity of ceramic-polymer composites, achieving crystallinity is not crucial,

but it may improve the obtained results due to the fact that neatly-crystallized

polymer speherulites tend to conduct heat better than amorphous polymers with

randomly-distributed strands.[43]

2. On the ceramic filler: As noted previously, damage sustained by the Boron

Nitride particles can result in a breakdown of their thermomechanical properties,

rendering them far less conductive than they would be if they were intact.

In order to understand how different moulding pressures affect the above mentioned

parameters, prototypes consisting of 33 wt% PTX60 in PPS were compression molded at 4

different pressures – 500, 1000, 1500 and 2000 psi – and analyzed using SEM.

25

Figure 15: 33% PTX60 in PPS matrix compression-molded at 500 psi – 50X

Figure 17: 33% PTX60 in PPS matrix compression-molded at 1,500 psi – 50X Figure 18: 33% PTX60 in PPS matrix compression-molded at 2,000 psi – 50X

Figure 16: 33% PTX60 in PPS matrix compression-molded at 1,000 psi – 50X

26

Figure 19: 33% PTX60 in PPS matrix compression-molded at 500 psi – 500X Figure 20: 33% PTX60 in PPS matrix compression-molded at 1,000 psi – 500X

Figure 21: 33% PTX60 in PPS matrix compression-molded at 1,500 psi – 500X Figure 22: 33% PTX60 in PPS matrix compression-molded at 2,00 psi – 500X

27

Two sets of images were taken of the samples compressed at the 4 pressures, one at 5ox

magnification to give a macroscopic view of the morphology of the samples (figures 15

through 18), and the other at 500x magnification to provide information on Boron Nitride

integrity after compression molding (figures 19 through 22).

The following observations are made:

• At low pressures, large microvoids, cracks and air pockets form throughout the

cross-section of the sample. These are and are a result of insufficient pressure

during compression molding, and are extremely detrimental to the thermal

conductivity of the final composite since the air in these gaps has a high thermal

resistivity. Therefore, we conclude that higher pressure yields a higher thermal

conductivity based on the 50x magnification micrographs.

• On the other hand, looking at figures 19 through 22, we notice that, as pressure

increases, there is a more pronounced breakdown of boron nitride particulates,

leading to loss of percolation and therefore diminishing the thermal conductivity

of the composite. Based on that observation, we conclude that the lower the

pressure, the better the percolation, and therefore the better the thermal

conductivity.

To strike a balance between these contradictory observations, we would have to pick one

of the two middle pressures – 1000 psi or 1500 psi. From a qualitative standpoint, it would

seem that the 1000 psi treatment is better since it produces fewer microvoids, while at the

same time preserving the integrity of the Boron Nitride sphere better than at 1,500 psi.

Therefore, it was decided from this point onward to apply a 1,000 psi compression

molding pressure to all thermal conductivity prototypes.

28

IV Phase Two: Coupling Agents

For a given filler concentration, there are three methods to increase the thermal

conductivity of the composite. They are (i) maximizing conductive paths, (ii) minimizing

thermal resistance in each conductive path [35], and (iii) decreasing the thermal contact

resistance at the filler–matrix interface. In this section, we will focus on the third method,

attempting so with the use of a coupling agent (also known as compatibilizer).

The value of the third method stems from the tendency for gaps or other flaws to occur at

the filler–matrix interface due to the insufficient affinity between filler and matrix. Such

interfacial flaws cause a high thermal resistance at the interface, thus reducing the

thermal conductivity of the composite [36, 37]. This thesis will attempt to use surface

treatment of the filler to improve the affinity between filler and matrix, thereby

significantly increasing the thermal conductivity of the composite. In particular, this

thesis will focus on using silane coupling agents for surface treatment. Silane acts as a

bridge to connect the ceramic filler and the polymer matrix together, because it has two

different chemical structures at the two ends of the molecule. One end is chemically

reactive with the polymer; the other end is chemically reactive with the surface of the

ceramic filler [37].

4.1 Background Research

Several studies have been conducted which used a variety of silane coupling agents. For

example, Yung and Yue [37] describe using a coupling agent – KBM-430 – to treat a

polymorph of hexagonal Boron Nitride not different from PTX60.

In surface-treating the Boron Nitride with the coupling agent, they first mixed the filler

and the coupling agent of 1 wt% of filler weight in a small amount of isopropyl alcohol at

80°C for 2 h. Next, they carried out vacuum drying to remove the solvent at 85°C for 24 h,

exposing the filler to ambient air for 4 h. Finally, they heat treated the filler at 100/120°C

for 4 h. The treated fillers were then stored in vacuum dryer.

29

Next, they embedded the

treated Boron Nitride in

an epoxy matrix and

conducted thermal

conductivity

measurements.

In their results, they

noted that increasing the

concentration of the

coupling agent increased the thermal conductivity up until 1%, which they found to be

the optimal concentration of coupling agent. Further increasing the coupling agent, they

found, led to a thick coating on the BN filler, which eventually become thermal barrier

causing the thermal conductivity to decrease. This is evident in figure 23 above, which

summarizes the results of their experiments.

The value of this study is that it provides a starting point for this section of the thesis. An

initial investigation found that KBM-430 may be difficult to procure, so a similar silane

agent, 3-aminopropyltriethoxysilane (SCA100), was obtained from Struktol.

Other coupling agents used by other researchers were also explored, such as Styrylethyl

trimethoxysilane (KH-560) [38] and [Methoxy(polyethyleneoxy) propyl]trimethoxysilane

[35] but they were both deemed unsuitable for this thesis as they could not sustain the

operating conditions under which the prototypes are produced. Therefore, the focus of

this section of the thesis will be solely on using SCA1100 as a surface treatment coupling

agent.

Finally, in addition to PPS, LDPE will be explored as a matrix polymer in future

experiments when using treated Boron Nitride. This is in accordance with research

Figure 23: Graph

showing the strong

correlation between

use of coupling

agents and thermal

conductivity. Note

that an increase in

the amount of

coupling agent does

not necessarily

imply an increase in

matrix-filler

adhesion. In fact, it

may have a

detrimental effect as

is the case here [37]

30

conducted by Harrison et al, which found a high affinity between silane-treated BN and

LDPE [10].

4.2 Methodology

The following steps are carried out in preparing a sample of Boron Nitride surface treated

with SCA1100 coupling agent:

1. A 50:50 mixture of water an ethanol is prepared in a beaker

2. The desired amount of coupling agent is added to the water-ethanol mixture using

a micropipette

3. The desired amount of Boron Nitride powder is added to the mixture of water,

ethanol and coupling agent

4. The mixture is stirred at the required temperature on a magnetic stir plate

5. The stirred mixture is filtered, leaving behind treated Boron Nitride powder (i.e.

Boron Nitride which has bonded to the coupling agent)

6. The Boron Nitride is dried on the hot plate overnight at 60°C

Treated Boron Nitride

50:50 water/ethanol solution Coupling Agent Boron Nitride

Stir on hot plate Filter out treated boron nitride

Treated Boron

Nitride

31

4.3 Thermal Gravimetric Analysis

Thermogravimetric Analysis (TGA) is a type of test which measures weight changes in a

material as a function of temperature (or time) under a controlled atmosphere. Its

principal uses include measurement of a material's thermal stability and composition.

For this thesis, TGA was carried out on treated and untreated samples of PTX60 and

PT110 in order to compare the effect of surface treatment on both polymorphs, as well as

to ensure that the coupling agent has adhered sufficiently to the Boron nitride particles.

4.3.1 Methodology

A TA Instruments Q-50 TG analyzer was used to conduct the TGA tests. The analyzer

itself consists of a high-precision balance with a platinum pan loaded with 10-20mg of a

powder of the composition to be tested. The sample is placed in a small electrically

heated oven with a thermocouple to accurately measure the temperature. The

atmosphere is then purged with Nitrogen in order prevent oxidation or other undesired

reactions.

Though the TGA machine can reach temperatures up to 1000°C, a temperature of 800°C

was deemed sufficient for the testing. A ‘ramp’ profile was picked, in which the furnace

heats the sample gradually at 20°C/minute until it reaches the 800°C mark.

After the data are logged, curve smoothing and other operations are then carried out by

the software in order to identify the points of inflection and produce an accurate graph of

percentage weight loss vs. temperature (or time).

32

4.3.2 Results

4.3.2.1 Calibration

As a proof-of-concept, LDPE was

analyzed for weight loss by

ramping the TGA up to 800°C.

Since LDPE’s degradation

temperature is only 120°C, one

would expect it to completely burn

off during the test, which was

confirmed as can be seen in figure

24 on the right. This test was

carried out to ensure the TGA is

properly calibrated.

4.3.2.2 PTX60 vs. PT110

Next, treated and untreated samples of PTX60 were analyzed in order to compare weight

loss results before and after surface treatment using 8 parts of SCA1100 coupling agent per

100 parts of PTX60.

Figure 24: TGA results for Pure LDPE

Figure 25: TGA results for Untreated PTX60 Figure 26: TGA results for PTX60 treated with SCA100

33

The same was carried out for PT110 samples before and after treatment with SCA1100

The fractional-loss results for treated and untreated BN upon heating to 800°C are shown

in chart 3 below. The amounts of volatile/decomposable material on the as-received,

acetone and HNO3 treated BN particles were negligible (~0.1% weight loss), indicating

that treatments involving acetone and acids did not result in a coating on the particle. On

the other hand, the amounts of weight loss were much higher (averaging out around -

0.82%) with treated PTX60 powder, indicating that the silane treatment resulted in a

coating on the particle, which decomposed during heating. This is exactly what we are

looking for in a coupling agent.

Figure 27: TGA results for Untreated PT110 Figure 28: : TGA results for PT110 treated with SCA100

-1.00%

-0.80%

-0.60%

-0.40%

-0.20%

0.00%

0.20%

PTX60 PT110 Untreated

Pe

rce

nta

ge

We

igh

t C

ha

ng

e

Chart 3: TGA results

34

The results for PT110, however, were slightly more ambiguous, with two of the samples

recording a weight gain and one recording a negligible loss. There are several reasons in

existing literature which may explain this unexpected weight gain. The first is that one of

the constituents in the sample may have oxidized during the experiment, leading to a

chemical reaction, which forms a compound that increases the weight of the sample [44].

This, however, is unlikely since the furnace is purged with nitrogen gas for the duration of

the run, which expels oxygen, thereby preventing any chemical reactions. Further, if

oxidation was an issue with the TGA, we would’ve observed the same weight gain when

testing the treated PTX60 samples.

Another possible explanation for the weight gain

is due to a phenomenon called baseline drift, in

which the TGA machine becomes decalibrated

over time due to changes in buoyancy of the purge

gas as its density decreases with increasing

temperature [45].

Regardless of the validity of this hypothesis is true, it was made clear from the TGA charts

that there is no perceptible weight loss in any of the treated PT110 samples, indicating

that SCA1100 failed to coat the PT110 platelets during the treatment process. This is likely

due to an incompatibility between the functional groups on the coupling agent and the

PT110 platelets.

Figure 29: Baseline Drift in TGA

35

By using SCA1100 solutions of three different concentrations, different amounts of coating

resulted. The three amounts were: 3 parts of SCA1100 per 100 parts of Boron Nitride (3 pph

for short), 8 pph (the recommended dosage per Struktol, the supplier of SCA1100), and 15

pph. These treatments were carried out for both PTX60 and PT110, and the results are

plotted in chart 4 below.

As can be seen, the higher the silane concentration in the solution, the greater the weight

loss, indicating an improved coating of the Boron Nitride. This was true for both PTX60

and PT110, though much more pronounced with the former.

These results imply that PTX60 has good reactivity with SCA1100 as it bonds well to it,

smoothing out its surface, thereby mitigating the interfacial thermal resistance that it

forms with PPS when the two are compression molded into a composite. These results,

however, do not imply that a higher amount of SCA1100 will ensure a higher thermal

conductivity in the a composite containing treated PTX60.

The next section addresses the issue of how to determine what the optimal amount of

coupling agent should be, amongst other factors.

-0.80%

-0.60%

-0.40%

-0.20%

0.00%

0.20%

0.40%

3 8 15

We

igh

t C

ah

ng

e

Amount of SCA1100 (parts of SCA1100 per hundred parts of Boron Nitride)

Chart 4 : TGA Results for PTX60 vs. PT110 vs. Amount of Silane Used

PTX60

PT110

36

4.4 Design of Experiments

Design of Experiments (DOE) is a systematic approach to investigating, understanding

and optimizing system or process. It comprises a series of structured tests in which

planned changes are made to the input variables – in this case, changes in process

conditions or amount of coupling agent, for example – of a process. The effects of these

changes on a pre-defined output – in this case, thermal conductivity – are then assessed

using statistical software such as MATLAB.

DOE is widely used in multivariate data analysis since it allows a judgement on the

significance to the output of input variables acting alone, as well input variables acting in

combination with one another.

Traditional ‘one-factor-at-a-time’ (OFAT) testing always carries the risk that the

experimenter may find one input variable to have a significant effect on the output while

failing to discover that changing another variable may alter the effect of the first (i.e.

some kind of dependency or interaction). This is because the temptation is to stop the

test when this first significant effect has been found. In order to reveal an interaction or

dependency, 'one change at a time' testing relies on the experimenter carrying the tests in

the appropriate direction. However, DOE plans for all possible dependencies in the first

place, and then prescribes exactly what data are needed to assess them i.e. whether input

variables change the response on their own, when combined, or not at all. In terms of

resource the exact length and size of the experiment are set by the design (i.e. before

testing begins).

Three types of DOE exist which may be used in our experiments: 1) Full Factorial DOE,

which accounts for all possible combinations of input variables, 2) Fractional Factorial

DOE, which exploits the sparsity-of-effects principle to expose information about the

most important features of the problem studied, while using a fraction of the effort of a

full factorial design in terms of experimental runs and resources, and 3) the Taguchi

Method, which is similar to the Fractional Factorial method, but relies on analysis of

variance (ANVOA) to define the list of experiments needed to be run.

37

For this thesis, it was determined that a Taguchi orthogonal-array DOE would be the

most efficient; two such arrays were to be constructed, one for samples with an LDPE

matrix, and the other for samples with a PPS matrix.

The first step in detailing these arrays was to list all control factors known (or suspected)

to have an effect on thermal conductivity of the resultant composite2:

1. Coupling Agent Treatment (stirring) Condition: Three stirring conditions

would be studied: 10 minutes at room temperature, 20 minutes at 60°C, and 20

minutes at 60°C

2. Amount of Coupling Agent: Per the recommendation of the supplier of SCA1100,

Struktol, three dosages of coupling agent would be attempted: 3 parts of SCA1100

per 100 parts of Boron Nitride (3 pph), 8 pph, and 15 pph.

3. Weight % of treated PTX60 in a thermal conductivity Sample: Six potential

levels would be considered: 5%, 10%, 25%, 33.3%, 50% and 74%. This allows us to

gauge the effect of coupling agents across a wide spectrum of different

compositions.

In summary, 3 control factors were identified: the first and second have three design

levels, and the third has six design levels. If we were to run a full factorial DOE against all

these factors, we would have to test 54 prototypes, which would be too expensive and too

time-consuming. Therefore, using MINITAB, we determine we arrive at the following

testing arrays: (1) An L9 DOE for samples consisting of a PPS matrix, and (b) An L12 DOE

for samples with an LDPE matrix. These arrays allow us to minimize the number of

experimental runs while still gaining information of how different control factors affect

the thermal conductivity independently and collectively.

A graphical summary of all the chosen experiments can be seen in figures 30 and 31 on the

next two pages.

2 The type of coupling agent was also identified as a control factor during the literature review phase, however, since no coupling agents were found that can withstand the process conditions currently used in prototyping samples, only SCA1100 is considered.

38

8 pph SCA 1100 +

PTX60

10 wt%

25 wt%

33 wt%

50 wt%

74 wt%

5 wt%

SCA 1100 + PTX60 at 60° for

10 minutes

3 pph SCA 1100 +

PTX60

15 pph SCA 1100

+ PTX60

33 wt%

33 wt%

Coupling agent

treatment condition

Amount of

Coupling Agent

wt% of agent-treated

PTX60 in a thermal

conductivity sample

SCA 1100 + PTX60 at 60° for 20

minutes

SCA 1100 mixed with PTX60 at

room temperature for 10 minutes

8 pph SCA 1100 +

PTX60

8 pph SCA 1100 +

PTX60

50%

33 wt%

33 wt%

50%

Type of Coupling Agent

3-aminopropyltriethoxysilane

(SCA1100)

Styrylethyl trimethoxysilane

[Methoxy(polyethyleneoxy)

propyl] trimethoxysilane

LDPE matrix

Figure 30: Summary of all compositions to be tested, using an LDPE matrix, as per a Taguchi L-27 DOE

39

Note the red cells in figure 30 on the previous page. These represent experimental

runs which have failed since they were carried out using LDPE in pellet form. The

samples produced using this method were extremely brittle as the LDPE pellets did

not melt during the compounding, but rather got embedded within the PPS.

Nevertheless, the information lost from the DOE due to the failure of these samples is

not severe This is because there is an additional array (fig 31) which carries out

similar tests, the results of which may, with caution, be extended to make conjectures

about samples with an LDPE matrix. This is explored in the next section.

Figure 31: Summary of all compositions to be tested, using a PPS matrix, as per a Taguchi L-27 DOE

40

1.7

1.9

2.1

2.3

2.5

2.7

2.9

Th

erm

al

Co

nd

uct

ivit

y (

W/m

.K)

4.5 Thermal Conductivity Results

Chart 5 above summarizes the

results of all experiments runs

at the same treatment condition of

10 minute stirring at 60°C for prototypes

with a PPS matrix. Immediately, we notice

that there is an almost linear relationship

between Boron Nitride content and thermal

conductivity, with the highest being 8.8 W/m.K

at 74 wt% Boron Nitride – very close to the desired

goal of 10 W/m.K. This figure is 13% higher that the

thermal conductivity obtained for untreated 74 wt%

Boron Nitride, indicating the coupling agent has

achieved its purpose of improving of the interface

between matrix and particles, thereby minimizing filler–matrix thermal contact

resistance. This improvement was also observed at the 33 wt% Boron Nitride

0

1

2

3

4

5

6

7

8

9

10

0% 10% 20% 30% 40% 50% 60% 70% 80%

Th

erm

al

Co

nd

uct

ivit

y (

W/m

.K)

wt% of PTX60 Boron Nitride

Chart 5: Thermal Conductivity Results: Treated vs. Untreated PTX60 in PPS matrix

Untreated PTX60

Treated with 8 pph SCA1100



41

composition, where the treated sample performed almost 40% better than its untreated

counterpart.

Next, we look at the effect of amount of coupling agent on thermal conductivity; this

comparison was carried out on 33 wt% Boron Nitride prototypes, and the results of these

tests are shown in the inset on chart 5.

Given that all three concentrations of SCA1100 yielded conductivities above that achieved

with untreated PTX60, we conclude that all silane treatments were effective in increasing

the thermal conductivity of the composite, though to varying degrees. As the amount of

silane coating on the particles increased, the thermal conductivity was enhanced more,

until the silane concentration reached 8 pph. Further increase of the silane concentration

to 15 pph caused the thermal conductivity to decrease. Hence, silane 8 pph treatment was

the most effective. This means that the coating resulting from the silane treatment must

be sufficiently thick in order for the treatment to be fully effective. The coating serves as

an interlayer at the filler–matrix interface, thereby improving the quality of the interface.

However, if the coating is too thick, the interlayer will become less effective or even a

thermal barrier, thereby decreasing the thermal conductivity.

42

Turning our attention to LDPE samples, we will now be able to understand the effect

of treatment conditions on thermal conductivity, as well as compare the effectiveness

of LDPE and PPS as matrices for our composites.

Looking at chart 6 above, we observe that the conditions under which PTX60 is

treated have a minimal effect on thermal conductivity regardless of composition.

That is to say, stirring PTX60 and SCA1100 at 60°C for 20 minutes does not achieve

any better a coating than does stirring them for 10 minutes at room temperature.

Therefore, to save time and energy, it is recommended for future research to carry

out the stirring at the latter condition.

We can also observe from chart 6 that PPS is a marginally better matrix than LDPE as

it manages to achieve, on average, an 8% higher thermal conductivity. This is likely

due to the fact that the functional groups on SCA1100 bond better to PPS than they do

with LDPE. Further, LDPE has less tendency to crystallize than PPS, therefore

diminishing the thermal conductivity of the matrix in the final composite.

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

60° for 10

mins

60° for 20

mins

22° for 10

mins

60° for 10

mins

60° for 10

mins

60° for 20

mins

22° for 10

mins

60° for 10

mins

LDPE PPS LDPE PPS

33% PTX60 50% PTX60

Th

erm

al

Co

nd

uct

ivit

y (

W/m

.K)

Chart 6: Thermal Conductivity Results: Different Treatment Conditions

43

Referring back to Design of Experiments, notice how, using a Taguchi DOE, we were

able to reduce the number of experiments by concluding from the LDPE results in

chart 6 that the treatment conditions are inconsequential, therefore forgoing the

need to test PPS samples at each process condition.

4.6 SEM Analysis

In order to study the effect of coupling agents on the morphology of the samples, four

prototypes were sectioned for SEM analysis, of which two comprised on a PPS matrix

embedded with:

1. 33 wt% PTX treated with 8 pph SCA1100


And the other two comprised an LDPE matrix embedded with



44

Figure 32 shows SEM micrographs of the cross-section of Boron Nitride-PPS composites

containing as-received BN particles (fig 32a) and silane-treated BN particles (fig 32b).

Figure 32a shows cracks, bare particles, and holes caused by particle pull-out due to the

poor interface between particles and matrix. Figure 32b shows fewer cracks, less bare

particles and less holes, indicating the improvement of the interface. This is in line with

the thermal conductivity results in section 4.5 which show that the treated Boron Nitride

samples performed substantially better than their untreated counterparts.

Figures 33 and 34 above show PPS composite samples embedded with treated 33% (fig

33) and 50% (fig 34) PTX60 Boron Nitride. In both cases, we observe that the Boron

Nitride particles have been coated with a layer of Silane. This improves the matrix-

Figure 32: SEM micrographs of a PPS matrix embedded with 33 wt% PTX60 (a) as-received, (b) treated

with SCA1100 at 60°C for 10 minutes. 500X magnification.

(a) (b)

Figure 33: 33 wt% surface-treated PTX60 in PPS matrix Figure 34: 50 wt% surface-treated PTX60 in PPS matrix

45

filler bonding and reduces the steep interfacial directional changes which were

previously resulting in severe phonon scattering leading to poor thermal

conductivity.

Figures 35 show LDPE composite samples embedded with treated 33% (fig 35) and

50% (fig 36) PTX60 Boron Nitride. In those cases, we observe the same coating layer

on the Boron Nitride particulates, but far less pronounced than in the PPS images,

indicating that the preparation of the treated Boron Nitride was not as effective as it

was in the previous cases. As such, it is recommended that these samples be retested

using a new batch of PTX60 treated with 8 pph SCA1100.

Finally, we note from figure 37, which shows

a low magnification image of an LDPE-PTX60

composite that the composites consisting of

an LDPE matrix produce an excellent finish

with very few microvoids, gaps or

imperfections as is the case with PPS matrix

samples (see figures 15 through 18).

Figure 35: 33 wt% surface-treated PTX60 in LDPE matrix Figure 36: 50 wt% surface-treated PTX60 in LDPE matrix

Figure 37: 33 wt% surface-treated PTX60 in LDPE

matrix. Low magnification

46

V Future Research Directions

It would seem that this research project has reached its limits, with the highest thermal

conductivity – still well short of predicted values – being obtained at the maximum 74

wt% Boron Nitride (with coupling agent). However, expanding on the results obtained in

this thesis, much work can be done in order to further close the gap between

experimental values and theoretical predictions. This section outlines three such

methods.

5.1 Multi-Modal hBN fillers

So far, the focus has been on using hexagonal Boron Nitride (hBN) embedded in

PPS in order to produce a composite with appreciable thermal conductivity. Another

form of Boron Nitride exists, however, which may be used in tandem with hBN to

improve upon the current results: Cubic boron nitride (cBN), a diamond-like allotrope of

Boron Nitride, exhibits excellent mechanical and thermal properties due to its

microstructure. It is synthesized by heating powdered hBN to 1500°C at a pressure in

excess of 60 kbars. This process transforms the atomic structure from hexagonal to cubic,

making the material hard and of high abrasivity.

hBN and cBN are often referred to as ‘modes’ of Boron Nitride. When compounded with a

resin and compression molded, they are equally good in terms of thermal conductivity

[25]. However, due to its hardness and abrasivity, cBN must be used with caution, and in

small amounts, as it may damage the compression molding.

In order to ensure the formation of a near-perfect conductive network throughout

the composite, maximum packing of the Boron Nitride in the matrix must be carried out.

To achieve a high packing density composites, several researchers have found the use of

large size particles with multimodal particle size distribution and low aspect ratio with

smooth surface texture to be very most effective [9][25][31]. The theory behind the

superiority of multi-modality relies on the idea of combined use of whiskers (hBN) and

47

particles(cBN) enhances the formation of a thermally conductive networks throughout

the composite[29]. The large particle size, on the other hand, is desired to minimize the

scattering of phonons due to the interfacial thermal barrier. Moreover, the use of large

particle size tends to form fewer thermally resistant junctions of the polymer layers than

the small particle size at the same filler content. Finally, the smooth surface texture

ensures that there is good adhesion between the BN and resin.

5.2 Ishida Method

Perhaps one of the best and most encouraging papers written on the topic of thermally-

conductive polymers is by Ishida and Rimdusit, who managed to obtain a thermal

conductivity of 32.5 W/m.K by embedding 88 wt%

hexagonal BN (grade HCJ48)3 in as-synthesized

bisphenol-A-methylamine type polybenzoxazine.

They note that “the remarkably high value was

obtained using the well-recognized concept of

thermal management in composite materials by

maximizing the formation of conductive networks

while minimizing the thermal barrier resistance

along the heat flow path. The concept was

accomplished by using

highly thermally conductive filler with a matrix

resin which has low melt viscosity and good adhesion to the filler. In addition, a large

particle size with multimodal particle size distribution was used. Boron nitride and

polybenzoxazine have properties that meet all these requirements and thus exhibit a very

high thermal conductivity value [...] Boron nitride-filled polybenzoxazine has many

outstanding properties which makes it suitable for an application as a molding compound

3 supplied by Advanced Ceramics, http://www.advceramics.com/

Figure 38: Ishida and Rimdusit's results for BN-saturated

polybenzoxazine

48

for the electronic packaging industry and other applications with high thermal

conductivity.” [9]

5.3 Multifunctional Fillers

As was pointed out in section 3.3, the

likely reason why there is a large gap

between the obtained and the

expected thermal conductivity values

is that, instead of agglomerating

together in a close-packed

arrangement to form a thermal

conductive network, the BN filler

particulates tend to cluster together in

a random arrangement, thus leaving

gaps in the conductive path.

These gaps may be bridged using carbon nanotubes (CNT), carbon fibres or graphene

[40] as diagrammed in figure 39. One study, conducted by Agarwal et al using various

compositions and orientations of carbon fiber and CNT fillers in a polycarbonate matrix

concluded that “composites containing hybrid mixtures of two fillers show higher

thermal conductivity due to increased contacts between the microfibers that are

promoted by the presence of the nanofibers, especially when microfibers are aligned.” [41]

Other potential fillers include nano-scaled graphene platelets (NGPs), which can be

obtained from American Elements [42] and carbon fibres, both of which exhibit excellent

thermomechanical properties.

Figure39:

Diagram

showing

thermal

conductive

pathways in

the matrix

49

VI Conclusion

A thermal conductivity of 8.8 W/m.K was obtained using composite consisting of 74 wt%

Boron Nitride embedded in a poly(p-phenylene sulphide) matrix. This remarkably high

value was obtained using the well-recognized concept of thermal management in

composite materials by maximizing the formation of conductive networks while

minimizing the thermal barrier resistance along the heat flow path. This was

accomplished by (1) using a resin which has a low melt viscosity and excellent affinity

with the filler to ensure that air gaps within the composite are minimized, (2) surface

treating the filler with a coupling agent, which improved the adhesion of Boron Nitride to

the matrix, thereby reducing phonon scattering at interfacial barriers and lattice defects

and bringing the percolation threshold within reach, (2) utilizing an optimized

compression molding pressure to preserve the thermomechanical integrity of Boron

Nitride, and (3) exploiting the spherical shape of PTX60-grade Boron Nitride to maximize

the packing of filler throughout the matrix, thereby increasing the likelihood of filler-filler

contact, and reducing the percolation threshold.

Though LDPE has shown far better affinity to Boron Nitride than PPS in SEM images, BN-

LDPE composites seem to have a high percolation threshold, and therefore would require

the use of a different coupling agent, or Boron Nitride contents in excess of 50 wt% in

order to achieve the desire goal of 10 W/m.K. However, a better-established method

would be the use of epoxy resins such as polybenzoxazine, combined with multi-modal

Boron Nitride filler, which, together, have shown potential to reach up to 32 W/m.K.

50

Acknowledgements: The author thanks Dr. Naguib for his continuous supervisory support and Dr. Leung for his superb mentoring, as well as Mr. Khan for his guidance and suggestions.

References

[1] Li et al, “Design and performance evaluation of microprocessor packaging capacitors using integrated capacitor-via-plane model”, IEEE Trasnscations on Advanced Packaging, Vol23, Issue: 3 pp 361-367, Aug 2000

[2] Sato et al, “Thermally conductive composite films of hexagonal boron nitride and polyimide with affinity-enhanced interfaces”, Journal of Materials Chemistry, vol.20,no.14, pp.2749-2752,2010

[3] Droval, G.; Feller, J. F.; Salagnac, P.; Glouannec, P. Polym. AdV. Technol. 2006, 17, 732–745

[4] Lee, W. S.; Yu, J. Diamond Relat. Mater. 2005, 14, 1647–1653

[5] Zhu etl al, “Study on the Properties of the Epoxy-Matrix Composites Filled with Thermally Conductive AlN and BN Ceramic Particles”, Journal of Applied Polymer Science Volume 118, Issue 5, pp 2754–2764, 5 December 2010

[6] Xu, “Increasing the thermal conductivity of boron nitride and aluminum nitride particle epoxy-matrix composites by particle surface treatments”, Composite Materials Research Laboratory, State University of New York at Buffalo, Buffalo, NY 14260-4400, USA

[7] Lee et al, “Thermally conductive and electrically insulating "EVA composite encapsulants for solar photovoltaic (PV) cell”, eXPRESS Polymer Letters, Vol.2, No.5 (2008) 357–363

[8] K. Sato, H. Horibe, and H. Horibe, “Thermally conductive composite films of hexagonal boron nitride and polyimide with affinity-enhanced interfaces,” Journal of Materials Chemistry, vol. 20, no. 14, pp. 2749–2752, 2010.

[9] Ishida et al, “Very high thermal conductivity obtained by boron nitride-filled polybenzoxazine”, Thermochimica Acta, vol 320, Issues 1-2, 2 pp 177-186, November 1998

[10] Harrison et al, “Polyethylene/Boron Nitride Composites for Space Radiation Shielding”, Journal of

Applied Polymer Science, Volume 109, Issue 4, pages 2529–2538, 15 August 2008

[11] Li et al, “Enhanced Thermal Conductivity of Polyimide Films via a Hybrid of Micro- and Nano Sized Boron Nitride” J. Phys. Chem. B, 2010, 114 (20), pp 6825–6829

[12] Gabellini and Maroaes, “Miscibility and morphology of poly p-phenylene sulphide–liquid crystal polymer blends”, Journal of Applied Polymer Science, volume 60, Issue 1, pages 21–27, 4 April 1996

[13] Author Unknown, JOURNAL OF MATERIALS SCIENCE 12 (1977), http://www.springerlink.com/content/r15008m241448215/fulltext.pdf

[14] http://www.dimensionsguide.com/processor-dimensions/

[15] Reebay et al, “Experimental Study of the convective heat transfer coefficient in electronic cooling”, Quantitative Infrared Thermography, University of Laval

[16] Xu, “Increasing the thermal conductivity of boron nitride and aluminum nitride particle epoxy-matrix composites by particle surface treatments”, Composite Materials Research Laboratory, State University of

New York at Buffalo, Buffalo, NY 14260-4400, USA

[17] Chung et al, “Role of Phonon Dispersion in Lattice Thermal Conductivity Modeling”, Transactions of

the ASME, Vol. 126, JUNE 2004

[18] L. D'Ilario and A. Martinelli, “Glass transition and the origin of poly(p-phenylene sulfide) secondary crystallization”, The European Physical Journal: Soft Materials and Biological Processes, vol 19, Number 1, 37-45, DOI: 10.1140/epje/e2006-00009-4

[19] Xu et al, “Synthesis and characterization of poly(p-phenylene sulfide sulfone/ketone) copolymer” POLYMER BULLETIN, Volume 54, Numbers 4-5, 251-261, DOI: 10.1007/s00289-005-0392-3

51

[20] Shen S, Henry A, Tong J, Zheng R, Gang Chen G. “Polyethylene nanofibres with very high thermal conductivities”, Nature Nanotechnology. 7 March 2010.

[21] Tian and Yang, “Phonon Transport and Thermal Conductivity Percolation in Random Nanoparticle Composites” CMES, vol.24, no.2, pp.123-141, 2008

[22] Martin et al. “Field-structured composites for efficient, directed heat transfer” Journal of Applied Physics, Volume: 106 Issue:8 Oct 2009

[23] Sato et al, “Thermally conductive composite films of hexagonal boron nitride and polyimide with affinity-enhanced interfaces”, JOURNAL OF MATERIALS CHEMISTRY,vol.20,no.14,pp.2749-2752,2010

[24] Neelakanta, Perambur S. Ph.D., C. Eng., "Handbook of Electromagnetic Materials, Monolithic and Composite Versions and their Applications", pp. 25-26.

[25] Droval et al, “Electrothermal Behavior of Conductive Polymer Composite Heating Elements Filled with Ceramic Particles”, Journal of Thermophysics and Heat Transfer 0887-8722 vol.22 no.4, Oct 2008

[26] Ali, “Ceramic-Polymer Composite Material and its Use in Microelectronics Packaging", US Patents Office, August 1998

[27] Raman and Meneghetti, “Boron nitride finds new applications in thermoplastic compounds”, Plastics, Additives and Compounding, Volume 10, Issue 3, May-June 2008, Pages 26-29, 31

[28] L.I. Demkina “A New System for Calculating The Coefficient of Thermal Expansion of Silicate Glasses”, Glass and Ceramics, Volume 17, Number 10, 503-510, DOI: 10.1007/BF00669607

[29] Raman and Meneghetti, “Boron nitride finds new applications in thermoplastic compounds”, Plastics,

Additives and Compounding, Volume 10, Issue 3, May-June 2008, Pages 26-29, 31

[30] Sato et al, “Thermally conductive composite films of hexagonal boron nitride and polyimide with affinity-enhanced interfaces”, Journal of Materials Chemistry, vol.20,no.14, pp.2749-2752,2010

[31] Yung et al, “Enhanced Thermal Conductivity of Boron Nitride Epoxy-Matrix Composite Through Multi-Modal Particle Size Mixing” Journal of Applied Polymer Science, vol 106, Issue 6, pages 3587–3591, 15 December 2007

[32] Burbank, “Twin Screw Compounding”, Rubber World, Jul 1997 http://www.thefreelibrary.com/Twin+screw+compounding-a019677610

[33] “Standard Test Method for Thermal Conductivity of Solids by Means of the Guarded-Comparative-Longitudinal Heat Flow Technique”, Developed by Subcommittee: E37.05, Book of Standards Volume: 14.02

[34] Jeffree, C. E.; Read, N. D. (1991). "Ambient- and Low-temperature scanning electron microscopy". In Hall, J. L.; Hawes, C. R.. Electron Microscopy of Plant Cells. London: Academic Press. pp. 313–413. ISBN 0123188806.

[35] R. Ruth, K. Y. Donaldson and D. P. H. Hasseiman, J. Amer. Ceram. Soc. 75, 2887 (1992).

[36] Jung et al, “Preparations and thermal properties of micro- and nano-BN dispersed HDPE composites”, Thermochimica Acta, Volume 499, Issues 1-2, 20 February 2010, Pages 8-14

[37] KC Yung and Yue, “Thermal Management for Boron Nitride Filled Metal Core Printed Circuit Board” Journal of Composite Materials, December 2008 vol. 42 no. 24 2615-2627

[38] Lee et al, “Thermally conductive and electrically insulating "EVA composite encapsulants for solar photovoltaic (PV) cell”, eXPRESS Polymer Letters, Vol.2, No.5 (2008) 357–363

[39] Yen Ng et al, “Thermal Conductivity of Boron Nitride-Filled Thermoplastics: Effect of Filler Characteristics and Composite Processing Conditions”, Polymer Composites, Volume 26, Issue 6, pages 778–790, December 2005

[40] “'Cool' graphene might be ideal for thermal management in nanoelectronics”, Nanowerk Spotlight

http://www.nanowerk.com/spotlight/spotid=4641.php

[41] Argwal et al, “Thermal Conductivity of Polymer Nanocomposites Made With Carbon Nanofibers”, Polymer Engineering & Science, Volume 48, Issue 12, pages 2474–2481, December 2008

[42] http://www.americanelements.com/cgnf.html

52

[43] Ramani NC, "Analysis of the Effect of Pressure on Compression Moulding of UHMWPE", J. Mat. Science: Mat. In Medicine, 9: 165-172, 1998 [44] Thermogravimetric Analysis Theory, Operation, Calibration and Data Interpretation, TA Instruments Presentation, Kadine Mohamed [45] Determining Volatiles in Polyethylene Terephthalate Using the Q5000 IR Thermogravimetric Analyzer, R. Bruce Cassel Ph.D . TA Instruments [46] Koledintseva et al, “Maxwell Garnett Model for Dielectric Mixtures Containing Conducting Particles at Optical Frequencies”, Progress In Electromagnetics Research, PIER 63, 223–242, 2006

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