Thermally conductive composite film filled with highly dispersed graphene nanoplatelets via solvent-free one-step fabrication

Composites Part B 110 (2017) 171e177

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Thermally conductive composite film filled with highly dispersed graphene nanoplatelets via solvent-free one-step fabrication Jaesang Yu, Ji Eun Cha, Seong Yun Kim* Multifunctional Structural Composite Research Center, Institute of Advanced Composite Materials, Korea Institute of Science and Technology (KIST), 92 Chudong-ro, Bongdong-eup, Wanju-gun, Jeonbuk, 55324, Republic of Korea

a r t i c l e i n f o

a b s t r a c t

Article history: Received 7 April 2016 Received in revised form 2 November 2016 Accepted 7 November 2016 Available online 9 November 2016

We proposed a solvent-free melting process for fabricating high-conductivity polymer composite films filled with highly dispersed GNP fillers. The excellent dispersion of GNP fillers in the composite films was observed using X-ray micro-computed tomography (micro-CT), a non-destructive three-dimensional (3D) analysis technique that helps to analyze the internal structures of composite films with precision. The excellent dispersion of GNP fillers also confirmed by the fact that experimentally determined electrical and thermal conductivity values of the composite films were well consistent with the theoretical calculations obtained with a Mori-Tanaka method. The composite films exhibited an electrical conductivity on the order of 101 S/m and the in-plane thermal conductivity of 7.1 W/m$K when they contained 20 wt% GNP fillers. © 2016 Elsevier Ltd. All rights reserved.

Keywords: Polymer-matrix composites (PMCs) Thermal properties Non-destructive testing Compression moulding

1. Introduction Since nanocarbons such as carbon nanotubes and graphene were found to have excellent thermal and electrical conductivity characteristics, a number of studies [1e5] have subsequently been conducted with regard to the development of nanocarbon-based high-conductivity materials. In particular, graphene is known for its outstanding thermal conductivity, with a value of 3000e6500 W/m$K [6,7], compared to carbon nanotubes, with a thermal conductivity of 1950e5000 W/m$K [1,8,9]. As a result, increasing attention is being paid to the development of thermally conductive composites using graphene [4,5]. Typically, thermally conductive composites have been fabricated by incorporating polymer resins with fillers of high thermal conductivity (e.g. carbon, ceramic or metal fillers) [10,11]. Recent studies [4,5] have been conducted on thermally conductive polymer composites filled with lightweight carbon fillers, especially with graphene nanoplatelet (GNP) fillers in bulk powder form, which are prepared by the reduction of graphene oxide that has been exfoliated by the thermal oxidation of graphite. The uniform dispersion of fillers is reported as one of the most important physical factors to be considered when fabricating high-

* Corresponding author. E-mail address: [email protected] (S.Y. Kim). http://dx.doi.org/10.1016/j.compositesb.2016.11.014 1359-8368/© 2016 Elsevier Ltd. All rights reserved.

conductivity composites filled with nanocarbon fillers, which tend to easily agglomerate due to van der Waals forces [1,4,12]. Using the most economically favorable melt-mixing process, it is difficult to achieve a uniform dispersion at a filler content high enough to sufficiently manifest the properties of the high-conductivity composites. In contrast, the solution-mixing-based process can achieve a uniform dispersion of fillers, but is not economical because it requires a long drying process time [12]. A recently proposed solvent-free in-situ polymerization-mixing process helps disperse fillers uniformly, like solution mixing, because low viscosity is produced under certain conditions [2,5,10,11,13e15]. Noh et al. [13] reported that a uniform dispersion of fillers in composites could be achieved by powder mixing and the in-situ polymerization of nanofillers and cyclic butylene terephthalate (CBT) oligoesters, without using any solvents. In addition, they reported the electrical [14,15] and thermal [2,5] properties of composites fabricated by the proposed process. In order to investigate the relationship between the internal structure and conductive properties of the composites filled with short fillers, it is necessary to evaluate the dispersion of the short fillers within the composites. To accomplish this, the fracture surface of composites filled with short fillers is generally observed using scanning electron microscopy. However, this method has somewhat limited, since it is not able to evaluate the entire internal structure and the dispersion of the fillers within the composites. Various non-destructive methods have been suggested in order to

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identify the internal structure of composites, such as ultrasonic testing, X-ray, eddy current, microwave, electrical resistivity measurement, acoustic emission, flash thermography, and shearography [16e20]. Among non-destructive methods with good resolution, X-ray computed tomography can be the most appropriate non-destructive method for evaluating the dispersion of composites filled with short fillers, because of its excellent ability of detection as summarized in Table S1 and Fig. S1 [21e31]. There are a variety of approaches and schemes reported for assessing and modeling the conductivities of composites at different scales of length, such as nano-, micro- and macroapplication scales. Among them, the Mori-Tanaka method (MTM) is a powerful tool for evaluating the effective properties of composite materials [32e35]. Recently, in order to model the electrical properties of composites containing carbon fillers, Kim et al. [15] have developed an analytical homogenization approach that allows for multiple heterogeneities within conductive coating layers, taking into account the electron tunneling effect. Further, they have proposed an MTM micromechanics theory that takes into account the waviness of CNT [2] and GNP [5] fillers to theoretically predict the thermal conductivity of composites containing nanocarbon fillers. As shown in Fig. 1, the present study proposes an application process for the one-step fabrication of high-conductivity polymer composite films, based on the previously proposed processes of powder mixing and in-situ polymerization. Micro-CT, a nondestructive 3D analysis technique, was used to assess the dispersion of GNP fillers in the composite films. In addition, the electrical and thermal conductivity values of the composite films were calculated by means of a micromechanics-based Mori-Tanaka model and compared with the experimental results. 2. Experimental 2.1. Materials High-conductivity GNP fillers (M25, XG Sciences, Lansing, MI, USA) was used as a filler. As shown in Fig. 2 (a) and (b), the GNP fillers were about 6e8 nm in thickness, 25 mm in diameter and 0.03e0.1 g/cc in bulk density and had a thermal conductivity of 3000 and 6 W/m$K in in-plane and through-plane directions, respectively. Cyclic butylene terephthalate (CBT, CBT 160, Cyclics Co., Schenectady, NY, USA) is a low-molecular-weight ring-shaped oligomer consisting of two to seven butyl monomers. CBT is

characterized by cleaving and melting in a temperature range of 130e150
C, and is known to have a low viscosity of 0.02 Pa s. CBT 160 is polymerized into polymerized CBT (pCBT) by contained catalysts when it is subjected to a heat of higher than 160
C [36]. 2.2. Fabrication of composites Since residual moisture is a major factor that impedes the polymerization of CBT resins, the fillers and resins were dried for 12 h at 110
C to remove moisture before fabrication of the composites. CBT can promote the enhanced dispersion of incorporated fillers because it has a low viscosity of about 0.02 Pa s during initial melting [13,14]. In order to achieve enhanced filler dispersion, we first finely powdered the CBT pellets and then mixed them with fillers in a target weight ratio as shown in Fig. 1. After that, the mixed materials were further mixed for 3 min at 2000 rpm using a mixer (ARE 310, Thinky Corp., Tokyo, Japan). The fine powder mixture was heated at 230
C for 20 min on a heating press (Dae Heung Science Co., Incheon, Korea) for the in-situ polymerization of the CBT resins. After the in-situ polymerization, the composite films were fabricated sequentially for 1 min under a pressure of 100 psi. The fabricated composite films were flexible as can be seen in Fig. 1. 2.3. Characterization 2.3.1. Morphology The thickness of the GNP fillers was observed using AFM (NX-10, Park systems Corp., Suwon, Korea). A 0.5 mg sample of the GNP was dispersed in 100 ml of ethanol using a horn-type ultrasonicator (VCX750, Sonics & Materials INC., CT, USA) for 2 h at 750 W power. The GNP sample was spin-coated for 60 s at 3000 rpm using a spin coater (spin process controller, MIDAS, Daejeon, Korea) on a silicon wafer. A field emission scanning electron microscope (FE-SEM, Nova NanoSEM 450, FEI Corp., OR, USA) was used to observe the lateral size and shape of the GNP fillers, and the fracture-surface morphology of fabricated composites. Prepared samples were surface-coated with platinum for 120 s in a vacuum using a sputter coating machine (Ion Sputter E-1030, Hitachi High Technologies, Tokyo, Japan). The coated composite samples were observed with a voltage of 10 kV applied under nitrogen vacuum conditions. 2.3.2. Tomography Micro-CT (Skyscan 1172, Bruker Co., USA) was used to identify the dispersion and network structures of the fillers in the

Fig. 1. Schematic of low cost and solvent-free one-step fabrication based on powder mixing and in-situ polymerization for thermally conductive composite film filled with highly disperse GNP fillers.

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Fig. 2. (a) AFM and (b) SEM images of GNP fillers, and micro-CT (c) 2D and (d) reconstruction images of the composite film.

composites. Measurements were made in a size of 2000  1332 pixels, and the X-ray source was measured under the conditions 51 kV voltage, 194 mA current and normal pressure.

2.3.3. Electrical conductivity Electrical conductivity of the fabricated composite films was measured by using the four-probe method according to ASTM D 257 (FPP-RS8, DASOL ENG, Cheongju, Korea) and an ultrahigh resistance meter (SM-8220, HIOKI E. E. Corporation, Nagano, Japan) under the applied voltage of 10 V.

2.3.4. Thermal conductivity The thermal conductivity of the composites was measured under normal temperature and pressure conditions using a conductivity-measuring instrument (TPS 2500 S, Hot Disk ab, Gothenburg, Sweden), according to the ISO 22007-2 standard. The sensor used in this study consisted of a double spiral of thin nickel wire and served as a continuous plane heat source. The sensor induced a temperature rise (DT) by supplying a constant amount of power (P) and, at the same time, measured the temperature change using a variation in sensor resistance. The thermal conductivity of the samples was determined using the Fourier equation for heat conduction based on the supplied power and induced temperature change.

2.3.5. Heat dissipation A thermographic camera (FLIR T420, Wilsonville, OR, USA) was used to evaluate temperature changes in fabricated composites. The heat dissipation image of a composite heated to 100
C was recorded 5 s after the material was placed on a room temperature plate.

3. Theoretical approach 3.1. Modified micromechanics for effective electrical conductivity The mean electric field gradient in the matrix is assumed to have been perturbed by the presence of other heterogeneities. The continuum averaged electric flux vector (J) and electric field gradient (Vf) are used in the MTM to predict the effective electrical conductivity tensor for the composite. The mathematical relationships used to determine the electrical conductivity in a conductor are similar in functional form to those used to develop the micromechanics models for thermal conductivity for steady state heat flux [32]. The electrical flow in a composite may be characterized in terms of the far-field applied electric flux vector (J), i.e.,

J ¼ s,Vf

(1)

where sis the effective second-rank electrical conductivity tensor and Vfis the electrical field gradient, which can be expressed in terms of the electrical potential, f. Similar to the classical Eshelby solution for linear elasticity [33e35], where the strain field inside each heterogeneity is constant, the resulting electric field gradient inside each heterogeneity is constant when calculating effective electrical conductivities. The MTM may be extended to the case for composites containing multiple distinct heterogeneities (fibers, spheres, platelets, voids, etc.) using the multi-inclusion and multi-phase composite models [35]. Yu et al. [32,37e40] used this approach for determining elastic moduli and thermal conductivities of a variety of nanocomposites. Suppose that the matrix contains m distinct types of ellipsoidal heterogeneities (p ¼ 1, 2,…, m) each consisting of np layers (ap ¼ 1, 2,…, np; p ¼ 1, 2,…, m). Each type of heterogeneity has distinct electrical properties, shape, and orientation distribution. The overall effective electrical conductivity tensor, s, for a composite containing m distinct types of heterogeneities (p ¼ 1, 2,…, m) each having an arbitrary number of layers (np) in a matrix

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(0) can be expressed as

AðPÞ ðap Þ ¼

8 2 39 1 = np < m    X X 5 s ¼sM , I þ 4 cðpÞa SðpÞ  I , AðpÞ ðap Þ  SðpÞ p : ; p¼1

ap ¼1

(2) Here

sM  sðpÞ ðap Þ

1

,sM

(3)

is the second-rank electrical field concentration tensor for the

ap ¼1

8 2 39 1 =1  np m < X X 4 5 , Iþ cðpÞa SðpÞ , AðpÞ ðap Þ  SðPÞ p : ; p¼1



ap th layer of the pth heterogeneity (ap ¼ 1, 2,…, np, p ¼ 1, 2,…, m). ð aÞ Further, sðpÞp is the second-rank electrical conductivity tensor for the ap th layer of the pth heterogeneity, c(p)apis the volume fraction of the ap th layer of the pth heterogeneity, and S(p) is the well-known second-rank Eshelby tensor common to the pth heterogeneity and all layers of the pth heterogeneity and I is the second-rank identity

Fig. 3. SEM images of composite film filled with (a) 1 wt%, (c) 5 wt%, (e) 10 wt%, (g) 15 wt% and (i) 20 wt% GNP fillers and micro-CT images of composite film filled with (b) 1 wt%, (d) 5 wt%, (f) 10 wt%, (h) 15 wt% and (j) 20 wt% GNP fillers.

J. Yu et al. / Composites Part B 110 (2017) 171e177

tensor. Here a “$” is used to denote the tensor single dot product. 3.2. Modified micromechanics for effective thermal conductivity The MTM [33e35] considers a single ellipsoidal heterogeneity embedded within an infinite homogeneous matrix domain subjected to a constant far-field heat flux, as applied to steady-state heat conduction problems. The MTM departs from the Eshelby method [41], which posits that the thermal gradient field is not perturbed by the existence of heterogeneities within a matrix. The MTM takes the opposite view and uses the continuum averaged heat flux vector (q) and temperature gradient (VT) to predict the effective thermal conductivity tensor for the composite [42,43]. The heat flow in a composite may be characterized in terms of the farfield applied heat flux vector (q), i.e.,

q ¼ K,VT

(4)

where K is the effective second-rank thermal conductivity tensor and VT is the continuum averaged temperature gradient. Like the classical Eshelby solution for linear elasticity [41], where the strain field inside each heterogeneity is constant, the resulting temperature gradient inside each heterogeneity is also constant when calculating effective thermal properties. The MTM may be extended to composites containing multiple distinct heterogeneities (i.e., fibers, spheres, platelets, voids, etc.) using the multi-inclusion and multi-phase composite models [35]. Yu et al. [32,37e40] used this approach to determine the elastic properties of a variety of nanocomposites. Suppose that the matrix contains m distinct types of ellipsoidal heterogeneities (p ¼ 1, 2,…, m), each consisting of np layers (ap ¼ 1, 2,…, np; p ¼ 1, 2,…, m). Each type of heterogeneity has distinct thermal properties, shapes, and orientation distributions. In this case, the effective thermal conductivity tensor, K, can be expressed as:

8 2 39 1 = np < m    X X a 4 5 K ¼Kð0Þ , I þ cðpÞa SðpÞ  I , AðpÞ ð p Þ  SðpÞ p : ; p¼1

ap ¼1

8 2 39 1 =1  np m < X X a 4 5 , Iþ cðpÞa SðpÞ , AðpÞ ð p Þ  SðPÞ p : ; p¼1

ap ¼1

(5)

175

of composites requires a non-destructive 3D analysis method. Micro-CT employing an X-ray source is a useful tool that can meet the requirement for accurate analysis. If 2D images shown in Fig. 2 (c) are taken consecutively in the direction of sample thickness and then reconstructed three-dimensionally, as shown in Fig. 2 (d), the internal structure of the sample in which GNP fillers are dispersed and oriented can be measured in a non-destructive manner. In this study, therefore, SEM and 3D micro-CT images were measured and compared to determine the dispersion of the fillers in the composites and to identify the 3D networks of thermally conductive fillers. A GNP/pCBT composite film was prepared by the proposed process, based on powder mixing and in situ polymerization. Fig. 3 shows the fracture-surface morphology and 3D micro-CT image of the composite film with respect to the weight fractions of GNP fillers in the composite. From the SEM image of the fracture surface of the composite film, it was difficult to determine the degree of GNP filler dispersion accurately, whereas in the X-ray micro-CT image, excellent filler dispersion was observed within the composite film, regardless of the weight fraction, until 20 wt% was reached. This comparison confirms that a non-destructive 3D analysis technique like X-ray micro-CT is required to assess the dispersion of GNP fillers in composite films. Fig. 4 shows the electrical conductivity of the composite film with respect to the weight fractions of GNP fillers (s ¼ 1.0E þ 5 S/ m). The electrical conductivity of the composite film was rapidly enhanced at low filler content and asymptotically converged at a filler content of above 5 wt% and the electrical percolation threshold of the composite film was observed to have a filler content of around 3 wt% both experimentally and theoretically. The measured electrical conductivity of the GNP composite film was consistent with the effective electrical conductivity predicted by the mean field micromechanical estimates based on the MoriTanaka model under assumed ideal conditions. From these observations, it can be concluded that the proposed method for fabricating composite films is a low-cost and solvent-free one-step process which can achieve a uniform dispersion of GNP fillers. Fig. 5 shows the actual measurements of thermal conductivity with respect to the weight fractions of GNP fillers. The in-plane thermal conductivity of the composite film showed a rapid increase as the content of GNP increased. For example, the thermal conductivity of composite film at a weight fraction of 20 wt% reached up to 7.10 W/m$K, a 857% increase compared to that of the

Where

AðPÞ ðap Þ ¼



Kð0Þ  KðpÞ ðap Þ

1

,Kð0Þ

(6)

is the second-rank temperature gradient concentration tensor for the ap th layer of the pth heterogeneity (ap ¼ 1, 2,…, np, p ¼ 1, 2,…, ðaÞ

m). Here KðpÞp is the second-rank thermal conductivity tensor for

the ap th layer of the pth heterogeneity, c(p)apis the volume fraction of the ath p layer of the pth heterogeneity, and S(p) is the second-rank Eshelby tensor common to the pth heterogeneity and all of its layers. 4. Results and discussion Using the electron microscope to examine the morphology of fracture surfaces, which is commonly adopted as a way of identifying the internal structures of composites, may also generate problems, such as changes in the internal structures during fracture surface sampling, and image distortion due to the two-dimensional (2D) image analysis. For accuracy, analysis of the internal structures

Fig. 4. Practically and theoretically obtained electrical conductivity of the composite films.

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found between the practically and theoretically obtained thermal conductivities. The heat dissipation properties of the fabricated composite films are presented in Fig. 6. Composites that had a high GNP content and thus exhibited excellent thermal conductivity were the most sensitive to temperature changes due to cooling. A fairly consistent trend was found between thermal conductivity and heat dissipation properties in relation to the composition of composite films. These findings confirm that optimizing the filler composition and the 3D thermally-conductive filler network is the most important physical factor in maximizing the heat dissipation properties of composites as well as their thermal conductivity.

5. Conclusion

Fig. 5. Practically and theoretically obtained thermal conductivity of the composite films.

We proposed a one-step solvent-free melting process for fabricating high-conductivity polymer composite films, which achieves high dispersion of the GNP fillers. From the results of a 3D non-destructive micro-CT analysis for internal structure of composite film, it confirmed that the proposed method for fabricating

Fig. 6. Infrared camera images of composite films during cooling after 5 s for transient temperature response and heat transport.

resin in use, 0.75 W/m$K. When carbon nanotubes, which are often compared with GNP fillers, are used as the composite carbon nanofillers, the composites are known to show a small increase in thermal conductivity regardless of the weight fraction [1,44e46]. The low thermal conductivity of composites filled with carbon nanotubes is caused by the interfacial resistance between the carbon nanotubes and polymer matrix, and the contact resistance between carbon nanotubes. Phonons are scattered by the interfacial resistance between carbon nanotubes and matrix in polymer composites, and the phonon transport between carbon nanotubes is adversely affected by the contact resistance [47e50]. Therefore, it can be concluded that, compared to carbon nanotubes, GNP is a relatively more excellent thermally-conductive nanofiller with respect to enhancing the thermal conductivity of polymer composites. The values of thermal conductivity calculated by the MoriTanaka method are shown in Fig. 5 with respect to the weight fractions of GNP fillers. The calculations slightly overestimated the measurements of thermal conductivity with respect to the weight fractions of composites. Considering the excellent dispersion of the fillers shown in the X-ray micro-CT image of Fig. 3, this overestimation can be explained by the imperfect interfacial interaction between the GNP fillers and matrix. The Mori-Tanaka method used in this study assumed that GNP fillers was fully dispersed in a matrix and would be fully bonded with the resin. The overestimation of thermal conductivity was attributable to the assumption that the contained GNP fillers would form an ideal heat transfer network in a composite, including the perfect dispersion and interfacial bonding. Nevertheless, a fairly consistent trend was

the composite films was a low-cost and solvent-free one-step process for achieving a uniform dispersion of GNP fillers. The electrical and thermal conductivity of the composite films were calculated theoretically with the Mori-Tanaka model, and the experimentally measured electrical and thermal conductivities were well consistent with the theoretical calculations. A fairly consistent trend was found between thermal conductivity and heat dissipation properties in relation to the composition of the composite films. The content and dispersion of GNP fillers in composite films were found to be the most important physical factors determining the conductive characteristics of the films. In light of the study findings, it is concluded that the proposed process, which allows nanofillers to be highly dispersed in composites without using solvents, will contribute to commercializing low-cost conductive composite films. Acknowledgements This study was supported by Korea Institute of Science and Technology (KIST) Institutional Program and the Technological innovation R&D program of SMBA [S2394169]. This study is also supported by the WPM (World Premier Materials) Program, Project No. 10037878, Ultralight Structural Nano Carbon Composites, funded by the Ministry of Trade, Industry and Energy (MOTIE, Korea). Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.compositesb.2016.11.014.

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