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A Polymer Composite with Improved Thermal Conductivity by Constructing Hierarchically Ordered Three-Dimensional Interconnected Network of BN Jiantao Hu, Yun Huang, Yimin Yao, Guiran Pan, Jiajia Sun, Xiaoliang Zeng, Rong Sun, Jian-Bin Xu, Bo Song, and Ching-Ping Wong ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.7b02410 • Publication Date (Web): 31 Mar 2017 Downloaded from http://pubs.acs.org on April 4, 2017

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ACS Applied Materials & Interfaces

1

A Polymer Composite with Improved Thermal

2

Conductivity

3

Hierarchically Ordered

4

Interconnected Network of BN

5

Jiantao Hu, †,║ Yun Huang, †,║ Yimin Yao, †,‡ Guiran Pan, †,§ Jiajia Sun, †,║ Xiaoliang

6

Zeng, *, †,‡ Rong Sun, *, † Jian-Bin Xu, ⊥ Bo Song, # Ching-Ping Wong †, ⊥, #

7 8 9 10 11 12 13 14 15 16 17 18 19

†

by

Constructing Three-Dimensional

Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences,

Shenzhen 518055, China. ║

Department of Nano Science and Technology Institute, University of Science and

Technology of China, Suzhou 215123, China. ‡

Shenzhen College of Advanced Technology, University of Chinese Academy of

Sciences, Shenzhen 518055, China. §

Department of Chemical Engineering, China University of Petroleum, Beijing

102249, China. ⊥

Department of Electronics Engineering, The Chinese University of Hong Kong,

Hong Kong 999077, China. #

School of Materials Science and Engineering, Georgia Institute of Technology,

Atlanta, Georgia 30332, United States. *

Address corresponding to: [email protected] and [email protected]

20

1

ACS Paragon Plus Environment


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1

ABSTRACT

2

In this work, we report a fabrication of epoxy resin/ordered three-dimensional

3

boron nitride (3D-BN) network composites through combining ice-templating self-

4

assembly and infiltration methods. The polymer composites possess much higher

5

thermal conductivity up to 4.42 W m−1K−1 at relatively low loading 34 vol% than that

6

of random distribution composites (1.81 W m−1K−1 for epoxy/random 3D-BN

7

composites, 1.16 W m−1K−1 for epoxy/random BN composites), and exhibit high glass

8

transition temperature (178.9 °C–229.2 °C) and dimensional stability (22.7 ppm/K).

9

We attribute the increased thermal conductivity to the unique oriented 3D-BN

10

thermally conducive network, in which the much higher thermal conductivity along

11

in-plane direction of BN microplatelets plays role at its best. This study paves the way

12

for thermally conductive polymer composites used as thermal interface materials for

13

next generation electronic packaging and 3D integration circuits.

14 15

Keywords: polymer composites, thermal conductivity, ordered network, thermal interface resistance, boron nitride

16

2


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1. INTRODUCTION

2

Heat removal issue has increasingly been critical to the performance, lifetime,

3

and reliability of electrical devices, which become more integrated, functional and

4

miniaturized1. It is widely agreed that exploring novel polymer composites with

5

improved thermal conductivity used as thermal interface materials is effective to solve

6

this problem2. However, most polymers normally suffer from undesired thermal

7

conductivity of about 0.2 W m−1K−1 because of the random rotation and vibration of

8

molecular chains when transferring phonons3,11.The addition of highly thermally

9

conductive fillers such as carbon materials4-6, ceramic materials7-9 and metallic

10

particles10-11 is effective to improve the thermal conductivity of polymers. However, a

11

majority of polymer-based composites have coarsely-designed structure, leading to an

12

undesired increase of thermal conductivity, due to the high thermal interface

13

resistance (RC)12-13. Surface modification for the filler is an efficient method to

14

enhance the interaction between the fillers and polymer matrix14-18. Disappointedly,

15

the enhancement of thermal conductivity seems so modest for largely weakened by

16

the existence of RC19 and sometimes limited by the poor thermal conductivity of

17

modification agents. Therefore, some intrinsic factors, for example, filler shape and

18

orientation in composites, are supposed to be considered when we design novel

19

polymer-based composites with improved thermal conductivity.

20

Among different thermally conductive fillers, platelet-like fillers have attracted

21

special attention20, due to their high-aspect-ratio and low percolation thresholds,

22

which is easy to form thermally conductive network at low loading. For instance,

23

graphene, is the most investigated platelet-like filler during the past ten years.

24

However, the platelet-like fillers have anisotropic thermal conductivity—much higher

25

thermal conductivity along the in-plane direction but fairly lower thermal conductivity

3



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along the through-plane direction. To fully utilize the inherent property, orienting the

2

fillers in the heat flow direction is widely adopted to achieve a high thermal

3

conductivity of polymer composites. For example, Lin21 et al aligned hexagonal boron

4

nitride by external magnetic field to obtain high thermal conductivity of polymer

5

along the alignment direction. However, the incorporated Fe3O4 brings negative

6

influence on total mass and thermal expansion match. Cho22 et al induced effective

7

heat conduction along the out-of-plane direction of polysiloxane/BN nanosheet under

8

a high direct current

9

complicated and cost much. Additionally, other methods including doctor-blading17,

10

injection molding23, electrospinning24, gravitational force25, etc are also performed to

11

form well orientation of fillers. However, most of them are coarsely hierarchical or

12

merely aligned in horizontal direction. Ice-templating self-assembly strategy, which

13

can form well-aligned orientation along the ice growth direction, has been proved to

14

be a promising and effective method to construct layer-by-layer assembling structure

15

in micro and nano scale26-28. Furthermore, 3D filler network contributes to effectively

16

decrease the RC because the total interfacial area decreases with the increase of filler

17

dimensions. Therefore, constructing well-oriented 3D interconnected filler network is

18

highly desirable for realizing high thermal conductivity enhancement in polymer-

19

based composites.

20

electric field, whereas, the experimental process was

In our previous and X.Y. Huang et al.’s work

29-30

, well-aligned and

21

interconnected 3D boron nitride nanosheet (3D-BNNS) networks in polymer

22

composites were prepared via combining ice-templating assembly or high temperature

23

treatment strategy. A high thermal conductivity along the BNNS orientation direction

24

was successfully obtained. However, the ultrathin BNNS (~4 nm) incorporates too

25

much interfaces including epoxy-BNNS and BNNS-BNNS which severely increases

4


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the RC of the composites. In addition, BNNS hinders the incorporation of epoxy resin

2

because of enlarged capillary force, which limits the loading of BNNS and leads to a

3

saturated thermal conductivity (below 3.2 W m−1K−1). So it is still remaining a

4

challenge to exploit novel polymer composites with improved thermal conductivity

5

from basic material-designing and tailoring principles.

6

Herein, we chose relatively much thicker (thickness, 150–500 nm) BN

7

microplatelets to act as a highway to transport phonons in polymer composites and

8

achieve favorable thermal conducting properties simultaneously. The epoxy/ordered

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3D-BN network composites were prepared through combining a carefully controlled

10

ice-templating method and infiltration technology. An ordered 3D-BN aerogel

11

network was firstly fabricated after ice crystals removed. Liquid epoxy resin was then

12

infused into the network. The ordered 3D-BN network was well-preserved after

13

conditionally curing. The prepared composites possess a high thermal conductivity

14

(4.42 W m−1K−1), a low coefficient of thermal expansion (CTE, 22.7 ppm/K) and a

15

relatively high glass transition temperature (178.9 °C–229.2 °C). Moreover, the

16

influences of BN loading and size on the composite morphology and thermal

17

conductivity are further investigated through varying ball milling time, respectively.

18

The interface mechanisms of thermal conduction for ordered and random distribution

19

composites are also discussed by combining various thermally conductive theoretic

20

models.

21

2. EXPERIMENTAL SECTION

22

2.1 Materials

23

Commercial BN microplatelets with the size of 10 µm were purchased from

24

Denka (Japan). Sodium carboxymethylcellulose (SCMC, viscosity: 1000–1400 mpa.s)

25

was purchased from Aladdin. Liquid epoxy resin (model: ER-4221) was purchased 5



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from Dow Chemical Company. Hexahydrophthalic anhydride (HHPA, Sinopharm

2

Chemical Reagent Co., Ltd.) and imidazole were used as curing agent and catalyst,

3

respectively. The deionized water was available in Milli-Q system (Millipore,

4

Billerica, MA, USA).

5

2.2 Preparation of 3D-BN network

6

The BN-SCMC aqueous slurries were firstly prepared by dispersing various

7

loadings of BN into 1 wt% SCMC deionized water mixture, which was pre-prepared

8

as dispersion agent and organic binder. To obtain the uniformly dispersed BN-SCMC

9

mixture with different BN platelet size, the aqueous mixture was ball milled

10

(Planetary ball mill, ND7/0.4L, 600 rpm) for various periods (1h, 3h, 6h and 24h).

11

Thanks to the role of SCMC binder, the viscose slurries hinder the mutual lubrication

12

effect between BN platelets and zirconia balls, which helps to realize an effective ball

13

milling of the mixture. After ball milled, the slurries were then poured into a

14

polythene mold placed on one end of copper rod (cuboid copper, 25 mm diameter)

15

which was dipped in liquid nitrogen (−60 °C). Through a stable anisotropic freezing

16

conductor, a well-ordered BN network was formed by controlling ice crystal growth

17

direction. After freeze dried (Freeze dryer FD-1C-50, China) at low temperature

18

(−50 °C) and pressure (26 Pa) for 48 h, ordered 3D-BN aerogels with different BN

19

loadings were finally obtained.

20

2.3 Preparation of oriented epoxy/3D-BN network composites

21

A uniform dispersed epoxy resins (model: ER-4221), curing agent (HHPA) and

22

catalyst mixture (imidazole, epoxy: HHPA: imidazole = 100:100:1, wt/wt) was

23

obtained by using planetary mixer (Sinomih, VM200s150ML, China) at 200 r/min at

24

room temperature. The mixture was then infused into the 3D-BN scaffolds and

25

subsequently the compounds were put in the vacuum oven (DZF-6050) at −25 Pa for

6


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2 h to remove the remaining air. Benefitting from the capillary force and low pressure

2

environment, the liquid epoxy resin mixture was successfully infiltrated into the 3D-

3

BN scaffolds. Finally, the composites were obtained after cured in a continuous

4

process (120 °C for 1 h, 160 °C for another 2 h) in electrothermal blowing dryer

5

(DHG-9053A). The detailed fabricated process of epoxy/oriented 3D-BN network

6

composites is illustrated in Figure 1. For comparison, BN-SCMC mixtures with the

7

same BN loading froze in a refrigerator under same procedures and curing condition

8

were denoted as epoxy/random 3D-BN composites. BN platelets directly mixed with

9

epoxy resins without 3D structure were denoted as epoxy/random BN composites.

10 11

Figure 1. Schematic illustrations of the preparation process of epoxy/ordered 3D-BN

12

network composites.

13

2.4 Characterization

14

The scanning electron microscope (SEM) images of epoxy/3D-BN network

15

composites were taken by using a ﬁeld-emission SEM (Nova NanoSEM 450, FEI)

16

with 10 kV accelerating voltage. The thermal conductivity of the composites was

17

measured through laser ﬂash technique (LFA 467 NanoFlash, Netzsch) and calculated

18

from the following formula

19

K = ρCpσ

(1) 7



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where ρ is the density of the composites, Cp is the specific heat capacity which is

2

tested by differential scanning calorimetry (DCS TA instrument, Q2000), and σ is

3

thermal diffusivity. The CTE of the composites in the temperature range from 25 °C

4

to 300 °C was measured by using thermomechanical analysis (TMA) (Model TMA

5

402 F1 Hyperion, Netzsch) under a preloaded force of 0.02 N with a 5 °C min−1

6

heating rate. The equation to calculate the density ρ is as followed

7

ρ=

8

where m, d and h are the mass, diameter and thickness of the tablet-like composite,

9

respectively. To ensure the accuracy, the diameter and thickness of the prepared

10

samples were measured over 20 times in various positions to get an average value. An

11

error bar was added to the obtained thermal conductivity. The physical properties

12

including density, heat capacity and thermal diffusivity of epoxy/oriented 3D-BN

13

network composites with different BN volume fractions was listed in Table S1

14

(Supporting Information). Tg was determined by the dramatic turn point in the thermal

15

expansion curves. The sizes of the BN microplatelets which were ball milled in

16

different periods were confirmed by Mastersizer 3000 Laser Diffraction Particle Size

17

Analyzer. The energy dispersive spectroscopy was performed by using scanning

18

electron microscope equipped with an energy-dispersive spectroscopy (EDS) detector.

19

The XRD patterns were performed by X-ray power diffraction (Rigaku, D/max-

20

2500Pc) with Cu Kα radiation (λ = 1.5418 Å).

21

3. RESULTS AND DISCUSSION

m m = v π (d / 2)2 h

(2)

22

Figure 2a, 2c and 2e shows the SEM fracture micrographs of oriented 3D-BN

23

aerogel, epoxy/ordered 3D-BN network composite and epoxy/random 3D-BN

24

composite, respectively. Oriented 3D-BN aerogel and epoxy/oriented 3D-BN network

8


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composite possess a smooth and uniform surface. In contrast, epoxy/random 3D-BN

2

composite without aligned BN network presents a rough and chaotic texture-like

3

surface (Figure S1, Supporting information), which indicates the distances between

4

BN platelets are irregularly distributed because of the different ice growth kinetics

5

arising from the variously imposed temperature gradient. Both the fracture images of

6

oriented 3D-BN aerogel and epoxy/oriented 3D-BN network composite present an

7

excellent alignment along the ice crystal growth direction. Figure 2b, 2d, 2f

8

corresponds to respective enlarged image marked by rectangle area. The network of

9

interconnected BN branches connecting adjacent hierarchical BN platelet backbones

10

can be clearly figure out from Figure 2b and Figure 2d. Epoxy matrix was

11

successfully infiltrated into the BN network scaffolds without evident voids and gaps,

12

and it isolates and encapsulates the neighboring filler platelet aggregates. The micro-

13

appearance of epoxy/random 3D-BN composite and epoxy/ random BN (Figure S2,

14

Supporting information) are quite different from epoxy/oriented 3D-BN network

15

composite. BN microplatelets are hard to be recognized from the amorphous shape

16

without evident alignment.

9



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1 2

Figure 2. Microstructure characterizations of prepared composites. Figure 2a), c) and

3

e) are SEM fracture micrographs of oriented 3D-BN aerogel, epoxy/oriented 3D-BN

4

network composite and epoxy/random 3D-BN composite. Figure 2b), d), f)

5

corresponds to respective enlarged view outlined in the white rectangle area. The BN

6

loading is 22 vol%.

7

To further verify the alignment of BN in epoxy/oriented 3D-BN network

8

composites, X-ray diffraction patterns and energy dispersive spectrums were

9

performed as shown in Figure 3. Figure 3a shows the XRD patterns and their 10


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1

schematic illustrations of epoxy/oriented 3D-BN network composites, pure BN

2

platelets and epoxy/random 3D-BN composites, respectively. Two evident peaks

3

(26.8° and 41.6°) representing the (002) and (100) lattice plane are easily found out

4

and the intensity ratio I002/I100 value elucidates the orientation of BN along the z

5

direction (parallel to the ice growth direction)31-32. Note that the intensity of epoxy

6

halo (~ 500) is much lower than that of BN (~ 48000), which results in an almost flat

7

area in the halo range (~ 20°) (Figure S3, Supporting information). For pure BN

8

platelets, the ratio is 22.5 and reduces to 13.4 for epoxy/random 3D-BN composite,

9

whereas for epoxy/oriented 3D-BN network composite, this ratio turns to 1.6, which

10

indicates the increasing orientation degree of BN along ice growth direction. Beyond

11

all doubt, the absolutely random-distributed pure BN platelet powder possesses the

12

highest value, but epoxy/random 3D-BN composites possess the slightly reduced

13

value thanks to the 3D-BN architecture, and the lowest ratio of our epoxy/oriented

14

3D-BN network composites verify the existence of favorable alignment of BN as

15

illustrated in Figure 3b. The nitrogen and boron element electron distribution

16

mappings (Figure 3c, d) also confirm the well orientation of BN in epoxy/oriented

17

3D-BN network composites.

11



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1 2

Figure 3. Further orientation characterizations of epoxy/oriented 3D-BN network

3

composites. a) XRD patterns of epoxy/oriented 3D-BN network composite,

4

epoxy/random 3D-BN composite and pure BN platelets, respectively and their

5

schematic illustrations. b) Electron mapping of epoxy/oriented 3D-BN network

6

composite of 6.7 vol% BN loading. c), d), Nitrogen and boron element distribution

7

images.

8

Figure 4 shows the thermal properties of the prepared epoxy/oriented 3D-BN

9

network composites. Note that the measured thermal conductivity is along the ice

10

crystal growth direction. We mainly aim to use a facile method to achieve ideally

11

higher thermal conductivity at any desired direction by use of the anisotropic thermal

12

conduction ability of BN platelets. Figure 4a illustrates a continuously increasing

13

thermal conductivity as a function of BN loading for all prepared composites. The

12


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1

thermal conductivity of the epoxy/oriented 3D-BN network composites grows much

2

faster, when comparing with epoxy/random 3D-BN and epoxy/random BN

3

composites, benefiting from the well-aligned BN ⊥ - BN ⊥ stacking structure. It

4

effectively conveys the phonons through preponderant-thermally-conductive direction

5

without severely negative scattering. More direct connection between epoxy and BN

6

microplatelets

7

epoxy/random 3D-BN composites, the slightly higher thermal conductivity mainly

8

benefits from the 3D-BN network which decreases the total thermal interface area.

9

Besides, the BN ⊥ -BN// interfaces play a more significant role when transferring

10

phonons, which hinders the effective phonon transportation because of the anisotropic

11

thermal conduction ability of BN microplatelets as schematically illustrated in Figure

12

4c. Additionally, at low BN loading (6.7 vol%), the difference of thermal conductivity

13

between oriented composites and random comparison composites is small, which is

14

ascribed to the not-yet-formed network (Figure S4, Supporting information) where

15

similar epoxy-BN interface phonon transferring mechanism dominates. However, at

16

relatively higher BN loading (34.2 vol%), the thermal conductivity of epoxy/oriented

17

3D-BN network composites reaches 4.42 W m−1K-1 while only 1.81 W m−1K−1 for

18

epoxy/random 3D-BN composites and 1.16 W m−1K−1 for epoxy/random BN

19

composites, which emphasizes the importance of well-aligned 3D network of BN. To

20

further elucidate the improvement extent, a parameter η was introduced, which is

21

defined as

22

η=

23

where Kc and Km represents the thermal conductivity of the composites and pure

24

epoxy matrix, respectively. There exhibits a nonlinear increase of η versus BN loading

limits

the

thermal

dissipation

efficiency33.

Kc − Km ×100% Km

Meanwhile,

for

(3)

13



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in Figure 4b, which implies the existence of interaction between BN-BN at high BN

2

loading34. At 34.2 vol% BN loading, a dramatic growth of η up to 2226% takes place,

3

which might be ascribed to the formation of percolation network. Figure 4c is the heat

4

dissipation model of epoxy/oriented 3D-BN network composites, epoxy/random 3D-

5

BN and epoxy/random BN composites, which schematically illustrates the different

6

interface thermal conduction mechanisms. Compared with epoxy/random 3D-BN

7

composites, the enhanced thermal conductivity of epoxy/oriented 3D-BN network

8

composites is attributed to the elevated and elaborated BN⊥-BN⊥ stacking structure.

9

Phonons would scatter less severely when occurring the BN⊥-BN⊥ interface, for the

10

advantaged K⊥ of BN platelet is fully utilized as much as possible.

11

To quantitatively expose the underlying factors towards thermal conductive

12

properties, two physical models including effective medium theory (EMT)35-37 and

13

Foygel’s theory38-39 were introduced to fit the experimental thermal conductivity data

14

of epoxy/oriented 3D-BN network composites, epoxy/random 3D-BN composites and

15

epoxy/random BN, respectively. At low filler loading, filler is completely

16

encapsulated by epoxy resins, the RC between resin and filler dominates in polymer-

17

based composites. While at high loading, a stronger interaction between filler-filler

18

happens, thus the RC between filler-filler plays a more crucial role5,

19

transfer in a heterogeneous way through the anisotropic filler network composites and

20

would be badly scattered on the interfaces, especially on filler-resin interfaces because

21

of the large phonon spectrum mismatch, thus, leading to a large RC and a poor thermal

22

conductivity34,

23

encapsulated by resin, is used to calculate the RC originating from epoxy-BN interface

24

of epoxy/random BN composites as followed

40

. Phonons

41-42

. EMT model, which works well where filler is completely

14


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1

K = Km

3 + V f ( β1 + β 2 )

(4)

3 − V f β1

2[ d ( K BN − K m ) − 2 Rc K m K BN ] d ( K BN + K m ) + 2 Rc K m K BN

(5)

2

β1 =

3

where Km, KBN are the thermal conductivity of polymer resin (0.19 W m−1K−1), pure

4

BN platelets (200 W m−1K−1). Vf is the BN volume fraction and d is the thickness of

5

BN platelets (0.2 µm). The well-fitted EMT model (Figure S5, Supporting

6

information) yields a thermal interface resistance of 3.6 × 10-7 m2 K W−1 for

7

epoxy/random BN composites (Figure 4d). However, the EMT model is not suitable

8

for epoxy/oriented 3D-BN network composites and epoxy/random 3D-BN composites,

9

where a 3D-BN scaffold was pre-formed. Foygel nonlinear model is then used to

10

calculate the RC of BN-BN interface as followed

11

K − K m = K 0[

12

where K are the thermal conductivity of epoxy/oriented 3D-BN network composites

13

and epoxy/random 3D-BN composites. K0 is a preexponential factor ratio which is

14

related to BN platelets contribution, β is a conductivity exponent which depends on

15

aspect ratio of BN platelets. Vc is the critical percolation BN volume fraction. After

16

done the tangent on the experiment data curve, the value of Vc (0.12) for

17

epoxy/oriented 3D-BN network composites and Vc (0.20) for epoxy/random 3D-BN

18

composites were obtained. The values of K0 (7.77) and β (0.55) for epoxy/oriented

19

3D-BN network composites were then derived by fitting the experimental data. For

20

epoxy/random 3D-BN composites, the values turn to K0 (2.86) and β (0.33) (Figure

21

S6 and S7, Supporting information). Based on this, the contact resistance (R) between

22

adjacent BN platelets can be calculated from the following equation

V f − Vc 1 − Vc

(6)

]β

15



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1

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1

R =

2

where L (200 nm) is the size of BN platelets (ball milling time of 24 h). The RC of 2.1

3

x 105 K W−1 for epoxy/oriented 3D-BN network composites and 3.0 x 105 K W−1 for

4

epoxy/random 3D-BN composites were then obtained after substituting the values

5

into the formula. The relation between these two parameters meets Rc = R × S, where

6

S is the overlapping area between adjacent BN platelets. Wemhoff et al43 provides an

7

approximate solution to calculate it (Figure S8, Supporting Information). Finally, the

8

overlapping area is about 1.90 × 10−12 m2. Based on this value, the thermal interface

9

resistance of BN⊥-BN⊥ for epoxy/oriented 3D-BN network composites is 4.0 × 10−7

10

m2 K W−1 and the thermal interface resistance of BN⊥-BN∥ for epoxy/random 3D-BN

11

network composites is 5.6 × 10−7 m2 K W−1, which quantitatively illustrates the

12

underlying factor of interface contacting difference between epoxy/oriented 3D-BN

13

network composites and epoxy/random 3D-BN composites. Furthermore, it is worth

14

noting that, the thermal interface resistance of BN-BN is larger than that of epoxy-BN,

15

which originates from the rigidly contacting way between adjacent stiff BN platelets.

16

This is why we adopt ice templating strategy to align BN microplatelets to form

17

oriented BN⊥- BN⊥ stacking structure decreasing the total thermal interface resistance.

18

Although possessing a smaller thermal interface resistance of epoxy-BN, the thermal

19

conductivity of epoxy/random BN composites is sharply weakened by the epoxy resin.

20

In consequence, compared with epoxy/random BN and epoxy/random 3D-BN

21

composites, the well orientation of BN platelets in higher heat conduction direction

22

for oriented epoxy/3D-BN composites is the most significant factor responsible for

23

better thermal dissipation.

24

(7)

K 0 L(Vc )β

Thermal stability of thermal conductivity is another significant factor. In order to

16


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1

investigate the temperature dependence of prepared oriented composites, the thermal

2

conductivity of epoxy/oriented 3D-BN network composites (ball milling at 6 h, 31.8

3

vol% loading) were measured in a typical operating temperature range (30–100 °C),

4

as shown in Figure 4e. In the disordered materials such as epoxy resins, thermal

5

conductivity can grow with temperature as a result of better phonon transmission

6

through the interfaces and decreasing Kapitza resistance44 at higher temperature. Thus

7

at temperature range (~30–80 °C), thermal conductivity keeps increasing. Even

8

encountering the interfaces of filler-filler or resin-filler, kinetic energy equipped

9

phonons get easier to cross the barriers and an increased thermal conductivity is

10

obtained. With the temperature rising, a peak of thermal conductivity value appeared

11

(~80 °C), which agrees well with previous report45-47. In BN as well as other

12

crystalline materials, thermal conductivity decreases with increasing temperature

13

owing to stronger phonon Umklapp scatterings48 caused by aggravating phonon

14

collision. Phonon Umklapp scatterings outweigh the decreased Kapitza resistance,

15

leading to that the thermal conductivity is proportional to 1/T. In general, most of

16

electronics operate at boosted temperature, and the elevated thermal conductivity

17

(6.65 W m−1K−1) of epoxy/oriented 3D-BN network composites at boosted

18

temperatures can ensure efficient heat transfer.

17



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1 2

Figure 4. Thermal properties of epoxy/oriented 3D-BN network composites and its

3

comparison composites. a) Thermal conductivity of epoxy/oriented 3D-BN network

4

composites, epoxy/random 3D-BN and epoxy/random BN composites as a function of

18


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1

BN volume fraction. b) Thermal conductivity enhancement of epoxy/oriented 3D-BN

2

network composites in comparison to epoxy/random 3D-BN and epoxy/random BN

3

composites. The definition of thermal conductivity enhancement is η = (KC − Km)/Km,

4

where Kc and Km represents the thermal conductivity of the composites and pure

5

epoxy matrix, respectively. c) Respective heat dissipation model of prepared

6

composites. d) Fitting and simulation of experimental thermal conductivity values

7

based on EMT model. e) The relationship between temperature and thermal

8

conductivity of epoxy/oriented 3D-BN network composite. The concentration of BN

9

was 31.8 vol% with a ball milling time of 6 h.

10

The size and morphology of the filler have complex influences towards thermal

11

conductivity of polymer-based composites as reported previously2,

12

varying ball milling time, the effects of BN microplatelet size on cross-section

13

morphology and on thermal conductivity of the prepared composites were further

14

investigated. As shown in Figure 5a, the thermal conductivity of epoxy/oriented and

15

random 3D-BN composites increases with ball milling time simultaneously. Evidently,

16

the thermal conductivity of epoxy/oriented 3D-BN network composites grows much

17

faster than that of epoxy/random 3D-BN composites because of the existence of

18

oriented 3D-BN network. For instance, at ball milling of 24 h, thermal conductivity

19

reaches 4.42 W m−1K−1 for epoxy/oriented 3D-BN network composites, while it is

20

merely 1.81 W m-1K-1 for epoxy/random 3D-BN composites. The thermal

21

conductivity enhancement η (Figure S9, Supporting information) also varies in

22

different levels towards ball milling time. It is not difficult to figure out that, the η of

23

epoxy/oriented 3D-BN network composites is nearly three or four-fold higher than

24

that of epoxy/random 3D-BN composites in these various points. Furthermore, as

25

depicted in Figure 5b, the blue dots in the range of 8.79 to 1.94 µm (Figure S10,

19


34, 40

. Through


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

1

Supporting information) elucidate the size varying trend with the increasing ball

2

milling time. More ball milling time means more durable shear force is exerted on the

3

BN platelets through continuous rotation and collision of zirconia balls which slightly

4

alters the shape and size of BN platelets, i.e., modifies the micromorphology and

5

orientation of 3D-BN network, as shown in Figure 5c. In shorter ball milling time, e.g.

6

1 h or 3 h, shear force does not have enough time to mold BN microplatelets, resulting

7

in larger BN profile (~8.79 µm) and relatively chaotic fracture morphologies which is

8

responsible for much lower thermal conductivity. The effect of decreasing size of BN

9

platelets creates more interfaces between BN platelets and epoxy matrix, which might

10

cause more serious interfacial phonon scattering and an increased thermal interface

11

resistance49. In this work, the effect of better orientation outweighs the influence of

12

increased thermal conduction interfaces, which contributes to the improvement of

13

thermal conductivity. Larger BN platelet profile no doubt repulses ice crystals growth

14

expelling force and hinders the formation of oriented BN network. In addition, the

15

framework of larger BN platelets is not so intricate because abundant voids and gaps

16

are remained, which aggravates phonons scattering heavily. Conversely, longer ball

17

milling time contributes to a more uniform distribution of BN platelets, for example,

18

about 3.65 µm of BN size for 6 h and 1.94 µm for 24 h, corresponds to well-organized

19

cross-section architectures without evident defects. Heat flux can be easily and

20

effectively transferred through the oriented hierarchically BN network without severe

21

phonon-defect scattering and phonon-phonon scattering as schematically illustrated in

22

Figure 5c.

20


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1 2

Figure 5. Relationships between thermal conductivity, BN microplatelet size and

3

fracture morphologies versus ball milling time. a) Thermal conductivity of the

4

epoxy/oriented 3D-BN network composites and epoxy/random 3D-BN composites

5

versus ball milling time. b) BN platelet size distribution with various ball milling time.

6

c) Cross-section morphologies and corresponding schematic illustrations of

7

epoxy/oriented 3D-BN network composites versus different ball milling time. The

8

ball milling time is 1 h, 3 h, 6 h, 12 h and 24 h, respectively. The red arrows indicate

9

the heat dissipation direction. The BN loading is 34.2 vol%.

10

As we all know, poor dimension stability and low Tg would bring severe impacts

11

to the functionality of electronic devices18. To examine the dimension and thermal

12

reliability, the effect of BN loading on CTE and Tg are also discussed in Figure 6. As

13

illustrates in Figure 6a, both the oriented and random comparison samples show a 21



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

1

tendency to decrease with the extended BN loading. Epoxy/oriented 3D-BN network

2

composites present a lower CTE. For example, epoxy/oriented 3D-BN network

3

composites possess a CTE of 22.7 ppm/K, while 35 ppm/K for epoxy/random 3D-BN

4

composites and 40.1 ppm/K for epoxy/random BN composites at 34.2 vol% BN

5

loading (Figure S11, Supporting information). This is attributed to the well-aligned

6

3D BN structure stabilizing the whole framework of the composites. Tg, which is

7

related to polymer chain motion state changes, is another important factor that

8

determines the processability and usability of polymer composites. Figure 6b shows

9

the dependence of Tg on the BN loadings. It is interesting to note that, all the three

10

kinds of composites exhibit a significantly decreasing trend of Tg as a function of BN

11

loading, which is kindly diverse from previous reports50-51. It has been well

12

recognized that the incorporation of fillers can make the Tg of polymers increase,

13

decrease or remain constant, depending on the dispersion of fillers in the matrix and

14

the filler–matrix interaction (strong, weak or repulsive)52-53. The decreased trend of Tg

15

is ascribed to the degraded BN dispersion at higher loadings and the effect of

16

decreased distance of BN platelets. Such decreased interparticle spacing could induce

17

conformation changes of polymer chains surrounding BN microplatelets and

18

introduce additional free volume (mainly filled with air, as shown in Figure S3,

19

supporting information) inside composites, which increases the segmental mobility

20

and thus leads to reduction in Tg. In addition, the addition of BN partly prevents

21

epoxy resins from curing and cross-linking.54. However, the Tg values of random

22

comparison composites reduce faster than that of oriented composites, for the oriented

23

3D-BN network exerts a stronger confinement effect on the motion of epoxy

24

molecular chains, which means the formation of 3D-BN network contributes to

25

improve the polymer system stability.

22


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1 2

Figure 6. CTE and Tg values of prepared composites. a) CTE and b) Tg values of

3

epoxy/oriented 3D-BN network composites, epoxy/ random 3D-BN composites and

4

epoxy/random BN composites as a function of BN loading.

5

4. CONCLUSIONS

6

We have successfully fabricated epoxy/oriented 3D-BN network composites by

7

combining ice-templating self-assembly and infiltration technology. The obtained

8

composites possess a favorable thermal conductivity (4.42 W m−1K−1), lower thermal

9

expansion coefficient (22.7 ppm/K) and high glass transition temperature (178.9 °C–

10

229.2 °C). We attribute the improved thermal conductivity to the following two

11

factors: 1. the well-aligned BN platelets in higher heat conduction direction based on

12

the anisotropic thermal conduction ability in different directions; 2. engineered

13

interfacial thermal resistance by constructing interconnected 3D network of BN in

14

epoxy resin. The thermal interface resistance difference (4.0 × 10-7 m2 K W−1 of BN⊥-

15

BN⊥ interfaces for epoxy/oriented 3D-BN network composites and 5.6 × 10−7 m2 K

16

W−1 of BN ⊥ -BN ∥ interfaces for epoxy/random 3D-BN composites) quantitatively

17

emphasizes the importance of orientation of BN platelets. Besides, different ball

18

milling time corresponds to different BN platelet size, which exerts different influence 23



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Page 24 of 28

1

on the morphology and thermal conductivity of epoxy/oriented 3D-BN network

2

composites. This work provides a significant guideline for future designs of thermally

3

conductive polymer composites for applications in thermal interface materials, and

4

aerospace materials to meet the increasing needs of heat dissipation.

5

ASSOCIATED CONTENT

6

*Supporting Information

7

Additional data including Figure S1–S10, physical properties of epoxy/oriented 3D-

8

BN network composites (Table S1) and theoretic approach used in the approximate

9

calculation of the average overlap area between adjacent BN platelets is supplied as

10

Supporting Information that is free of charge on ACS Publications website.

11

AUTHOR INFORMATION

12

Corresponding Authors

13

*Address corresponding to: [email protected] and [email protected]

14

Notes

15

The authors declare no competing financial interest.

16

ACKNOWLEDGMENT

17

The authors would like to acknowledge the financial support from National Natural

18

Science Foundation of China (No. 51603226), Guangdong Provincial Key Laboratory

19

(2014B030301014),

20

(JCYJ20150831154213681).

21

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(47) Wang, F.; Zeng, X.; Yao, Y.; Sun, R.; Xu, J.; Wong, C. P. Silver Nanoparticle-Deposited Boron Nitride Nanosheets as Fillers for Polymeric Composites with High Thermal Conductivity. Sci. Rep. 2016, 6, 19394. (48) Balandin, A. A., Thermal Properties of Graphene and Nanostructured Carbon Materials. Nat. Mater. 2011, 10 (8), 569-581. (49) Yao, Y.; Zeng, X.; Pan, G.; Sun, J.; Hu, J.; Huang, Y.; Sun, R.; Xu, J. B.; Wong, C. P. Interfacial Engineering of Silicon Carbide Nanowire/Cellulose Microcrystal Paper toward High Thermal Conductivity. ACS Appl. Mater. Interfaces 2016, 8 (45), 31248-31255. (50) Jia, J.; Sun, X.; Lin, X.; Shen, X.; Mai, Y.-W.; Kim, J.-K. Exceptional Electrical Conductivity and Fracture Resistance of 3D Interconnected Graphene Foam/Epoxy Composites. ACS Nano 2014, 8 (6), 5774-5783. (51) Lian, G.; Tuan, C.-C.; Li, L.; Jiao, S.; Wang, Q.; Moon, K.-S.; Cui, D.; Wong, C.-P. Vertically Aligned and Interconnected Graphene Networks for High Thermal Conductivity of Epoxy Composites with Ultralow Loading. Chem. Mater. 2016, 28 (17), 6096-6104. (52) Bansal, A.; Yang, H. C.; Li, C. Z.; Cho, K. W.; Benicewicz, B. C.; Kumar, S. K.; Schadler, L. S. Quantitative Equivalence between Polymer Nanocomposites and Thin Polymer Films. Nat. Mater. 2005, 4 (9), 693-698. (53) Rittigstein, P.; Priestley, R. D.; Broadbelt, L. J.; Torkelson, J. M. Model Polymer Nanocomposites Provide an Understanding of Confinement Effects in Real Nanocomposites. Nat. Mater. 2007, 6 (4), 278-82. (54) An, L.; Pan, Y.; Shen, X.; Lu, H.; Yang, Y. Rod-like Attapulgite/Polyimide Nanocomposites with Simultaneously Improved Strength, Toughness, Thermal stability and Related Mechanisms. J. Mater. Chem. 2008, 18 (41), 4928.

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