Effects of heat treatment on the thermal properties of highly nanoporous graphene aerogels using the infrared microscopy technique

International Journal of Heat and Mass Transfer 76 (2014) 122–127

Contents lists available at ScienceDirect

International Journal of Heat and Mass Transfer

journal homepage: www.elsevier .com/locate / i jhmt

Effects of heat treatment on the thermal properties of highly nanoporousgraphene aerogels using the infrared microscopy technique

http://dx.doi.org/10.1016/j.ijheatmasstransfer.2014.04.0230017-9310/� 2014 Elsevier Ltd. All rights reserved.

⇑ Corresponding author. Tel.: +65 65161567.E-mail address: [email protected] (H.M. Duong).

Zeng Fan a,b, Amy Marconnet c, Son T. Nguyen a, Christina Y.H. Lim a, Hai M. Duong a,⇑a Department of Mechanical Engineering, National University of Singapore, Singaporeb Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, USAc School of Mechanical Engineering, Purdue University, USA

a r t i c l e i n f o a b s t r a c t

Article history:Received 21 November 2013Received in revised form 10 April 2014Accepted 12 April 2014

Keywords:Thermal conductionGraphene aerogelsThermal interface materials

Graphene aerogels (GAs), fabricated from graphene oxide (GO) suspensions using a mild chemical reduc-tion method, are promising for many applications. Here we report the thermal conductivities of GAs hav-ing various graphene volume fractions from 0.67% to 2.5%, with and without annealing treatment,measured using a comparative infrared microscopy technique. The thermal conductivities of the GAsare measured to be 0.12–0.36 W/(m K). This is the first systematical study of the thermal properties ofGAs and the results elucidate the factors limiting their thermal conductivities. The developed thermalmeasurement technique can be applied to other porous material systems.

� 2014 Elsevier Ltd. All rights reserved.

1. Introduction

Thermal management is crucial issue in the electronic indus-tries, owing to the continued miniaturization and rapid increasein the power of microelectronics, optoelectronics and photonicdevices [1,2]. Recently, graphene, with its light weight and remark-able thermal conductivities (�5300 W/(m K) [3]), has beenregarded to be an ideal candidate as nanofillers for next generationthermal interface materials (TIMs). Much effort has been made todevelop graphene-based composites by adding randomly orientedgraphene nanosheets into a polymer matrix [4–7]. However, theenhancement in thermal conductivity for graphene-based compos-ites is still very limited due to several factors including localagglomeration, defects within the graphene nanosheets, and inter-action between the graphene nanosheets and polymer matrix [8–10]. In addition, although the properties of pristine graphene areunique and desired for many applications, the time-consumingexfoliation process and low yield manufacturing make utilizationof graphene-based materials challenging in practice [11,12]. Thus,chemically-derived graphene from graphite is promising alterna-tive approach to produce graphene in large quantities [13–15].Assembling chemically-derived graphene nanosheets into three-dimensional (3D) architectures [16–23] creates an interconnectednetwork of graphene sheets with a scalable low-cost productionmethod [23], which is a promising for thermal management

applications at the industrial scale. In contrast to the non-uni-formly dispersed graphene observed in composites, graphene aero-gels (GAs) with continuous scaffolds and mesoporous structures(porosity > 90%) may reduce the internal thermal resistance andenhance the thermal efficiency of TIMs. However, studies of thethermal transport in GAs remain very limited. Zhong et al. [23]reported the thermal conductivity of a GA sample with a relativelylow surface area (�43 m2/g) to be 2.18 W/(m K) using the laserflash technique.

Several measurement techniques have been developed to char-acterize the thermal conductivities of nanostructured TIMs [24]including the laser flash technique [5,23,25,26], steady-state mea-surement techniques [27,28], transient techniques [29,30], andinfrared microscopy techniques [31–33]. Infrared microscopy hasseveral advantages over other methods as it leverages the non-con-tact, two-dimensional temperature mapping eliminating the needfor intrusive temperature sensors and is a direct measurement ofthermal conductivity (e.g. it does not require knowledge of thesample specific heat and density). Infrared microscopy techniqueshave been utilized to measure the effective thermal conductivitiesof a bulk material [31] and thermal resistances of commercial TIMs[33] with a reported approximated uncertainty of 10%. Particularlyfor thermal conductivity measurements, the heat flux can beextracted even more accurately with the employment of referencematerials based on a comparative method similar to the ASTME1225 standard.

In this work, a comparative infrared (IR) microscopy is devel-oped for thermal measurement of highly porous materials. We

Z. Fan et al. / International Journal of Heat and Mass Transfer 76 (2014) 122–127 123

apply this technique to determine the thermal conductivities of theGAs fabricated from graphene oxide (GO) aqueous suspension. Thethermal conductivity is measured as a function of graphene oxideconcentration and thermal annealing. This work reports the firstbenchmark data of the thermal properties of the GAs, and seeksto identify the factors limiting their thermal conductivities.

Fig. 1. (a) Schematic of the thermal conductivity measurement structure using thecomparative infrared thermography technique. (b) Temperature distribution andlinear best fit curves for the 3-layered stack consisting of a GA sample sandwichedbetween two amorphous quartz layers, scale: 133 lm/pixel. (c) Heat flux as afunction of the temperature gradient in the sample region at several power levels.

2. Materials and methods

2.1. Materials

Graphite powder, sodium nitrate (NaNO3), potassium perman-ganate (KMnO4), concentrated sulfuric acid (H2SO4), hydrogen per-oxide (30% H2O2), hydrochloric acid (HCl) are purchased fromSigma–Aldrich Company Ltd. L-ascorbic acid (LAA) and ethanolare obtained from Alfa Aesar and Merck respectively. All the chem-icals are used as received without further purification.

2.2. Synthesis of graphene aerogels (GAs)

Graphene aerogels (GAs) with a controlled morphology are syn-thesized from graphene oxide (GO) aqueous suspension by a chem-ical reduction method as described in our previous work [34,35]. Inbrief, GO is first prepared by oxidation of graphite powder usingH2SO4, NaNO3 and KMnO4 according to a modified Hummers’method [36–38], followed by exfoliation. Subsequently, GAs aresynthesized by chemical reduction of GO aqueous suspensions(with concentrations of 1, 2, 6 and 12 mg/ml) with LAA at 95 �Cfor 5 h and dried with supercritical CO2. In order to investigatethe impact of thermal annealing on the thermal conductivities ofthe GAs, the as-prepared GAs are annealed at 450 �C for 5 h underan Argon (Ar) environment.

2.3. Morphology characterization and thermal measurement of theGAs

The morphology of the GAs is characterized using a field emis-sion scanning electron microscopy (FESEM, Model S-4300 Hitachi,Japan). Additionally, X-ray diffraction (XRD, 6000 Shimadzu, Japan)shows the effects of GO concentration and thermal annealing onthe structure of the GAs. Bulk densities are quantified by measur-ing the GA weight and size.

The thermal conductivity of the GAs is measured using animproved comparative infrared microscopy technique [31]. Priorto the measurement, a GA sample is sandwiched between two ref-erence layers to build a 3-layered stack using silver paste to ensuregood contact between the sample and reference layers, which issubsequently affixed to a heat sink plate at the bottom and a resis-tive heater on the top. Amorphous quartz with a thermal conduc-tivity of kAmorphous quartz = 1.3 W/(m K) is selected as the referencematerial in this paper to ensure a comparable thermal resistancebetween the tested sample and reference materials as well as goodthermal conduction through the entire sample stack.

The dimension of the reference layers is 10 mm (L) � 10 mm(W) � 1 mm (H) and the in-plane dimension of the GA samples isalso 10 mm (L) � 10 mm (W). All the surfaces of the GAs are pol-ished and the thickness of the GAs is controlled to be1.2 ± 0.2 mm. The temperature resolution of the IR camera is0.08 K and for all the measurements, the temperature throughthe whole stack is lower than 80 �C.

A one-dimensional heat flux is generated through the stack bythe resistive heater and a VariCAM high resolution thermographicsystem captures the temperature distribution across the wholestack. All surfaces facing IR camera are coated with graphite toachieve a uniform, high (near unity) emissivity. The experimental

set-up is illustrated in Fig. 1(a). From the measured two-dimen-sional temperature maps for the amorphous quartz–GA-amor-phous quartz stack, one-dimensional temperature profiles areobtained by averaging the temperature in the direction perpendic-ular to the heat flux. Fig. 1(b) shows a typical temperature profile,where the temperature gradients in the reference amorphousquartz region dT

dx

� �Amorphous quartz

� �and sample region dT

dx

� �GA

� �are

calculated through fitting the temperature profile with the least-square method.

Heat transport within the sample stack can be described byFourier’s law. Given the same cross section and constant heat fluxin the stack, the one-dimensional steady-state heat conductionequation is expressed as:

q00 ¼ �kAmorphous quartz �dTdx

� �Amorphous quartz

¼ �kGA �dTdx

� �GA; ð1Þ

where q00 is the heat flux through the sample stack and is calculatedfrom the value of kAmorphous quartz and the average of the temperaturegradients in the two amorphous quartz regions. Accordingly, thethermal conductivity of the GA (kGA) is determined from Eq. (1)and the measured temperature gradient in the GA. To minimizethe effect of the thermal boundary resistance (TBR), the pixels atthe boundary of each layer in the stack are eliminated from thecalculation.

124 Z. Fan et al. / International Journal of Heat and Mass Transfer 76 (2014) 122–127

To yield robust results, the heat flux (q00) vs. the temperaturegradient in the sample region dT

dx

� �GA

� �is plotted at several power

levels and the measured graphene aerogel thermal conductivity(kGA) is extracted from the slope of the least-squares best fit to thiscurve, as shown in Fig. 1(c).

3. Results and discussion

3.1. Thermal conductivities of GAs with different concentrations

During the reduction of hydrophilic GO to hydrophobic graph-ene, the partial overlap of flexible graphene nanosheets due top–p interaction results in the formation of the 3D graphene hydro-gels [18,39]. After supercritical drying, the interconnected porousnetwork is preserved in the GAs, as shown by the FESEM imagesin Fig. 2. The concentration of GO aqueous suspension, as well asthe annealing treatment, impacts the morphologies and thermalconductivities of the GAs. Table 1 summarizes the synthesis condi-tions, density, volume fraction and thermal conductivities for eachGA sample.

The total thermal conductivity of the GAs consists of both elec-trical and lattice contributions [8]. However, the electronic contri-bution part ðkGA;eÞ is small, as calculated from Wiedemann–Franzlaw [40] (kGA;e ¼ LT=qGA, where L, T and q are the Lorentz number,temperature and electrical resistivity respectively), which are esti-mated to be less than 3% of the total thermal conductivity acrossthe whole measured temperature range. Therefore, the latticevibrations (phonons) are proposed to be the dominant heat trans-fer mechanism in the GAs [3–5,8,41].

Our previous investigations [34,35] showed that the GA synthe-sized from higher GO concentration exhibits higher electrical con-ductivity, due to the better electron mobility through the contactsbetween graphene sheets. Similar trends are also observed for thethermal properties of the GAs, as shown in Fig. 3. The thermal con-ductivity of GA4 (0.36 ± 0.015 W/(m K)), which was fabricatedfrom the highest concentration GO suspension, is significantlyhigher than those for GA1–3 (0.12 ± 0.006, 0.18 ± 0.013, and0.24 ± 0.007 W/(m K)), which were fabricated from lower concen-tration GO suspensions. This significant increase of thermal con-ductivity with the initial GO concentration could be attributed toa more connected network of graphene sheets in the GAs synthe-sized from higher GO concentration (see Fig. 2(a)–(d)). Specifically,the higher density of graphene nanosheets and the increased over-lap between sheets is expected to provide lower resistivity path-ways for phonons transport through the sample [4].

Considering the extremely high thermal conductivity of graph-ene (up to 5300 W/(m K)), all the measured values of the GAs areextremely low. The GAs have extremely high porosities (>97.5%)

Fig. 2. SEM images of the GAs synthesized under different conditions: (a)–(h) represent Gannealing, images (e)–(h) show denser networks than those in images (a)–(d) at the sam

and all the pores inside are filled by air, which has very low ther-mal conductivity (0.026 W/(m K) [42]). The low density of graph-ene is expected to be the dominant factor which results in thelow effective thermal conductivity of the GAs in the bulk form[43]. However, the measured thermal conductivity is below thatpredicted by the porosity and the conductivity of the individualgraphene sheets. Thus additional factors must contribute to thereduced thermal conductivity.

First, the quality of graphene nanosheets significantly impactsthe thermal conductivity of the GAs [44]. All the GAs here are syn-thesized by the chemical reduction method, in which a number ofdefects are introduced during the strong oxidation process and arenot completely repaired during the chemical or thermal reductionprocesses [11,45,46]. Note that the highest thermal conductivity ofreduced graphene oxide (rGO) is measured to be only 6.8 ± 0.08 W/(m K) [45], which falls well below 5300 W/(m K) of the defect-freegraphene.

Second, the size of chemically-derived graphene nanosheets iscomparable to the phonon mean free path (�775 nm at room tem-perature) [1]. Specifically, the individual nanosheets are reportedto range in size from 200 nm to 2 lm [45,47]. In the experiment,a large fraction of the graphene nanosheets within the GAs wouldbe far smaller than this mean free path, and thus their thermal con-ductivities are also significantly limited by the increased scatteringat the nanosheet boundaries [47].

Third, the GAs consists of numerous randomly distributedgraphene nanosheets in contact with each other. Heat must trans-fer between many nanosheets as it conducts across the aerogel andthe thermal resistance between the individual graphene nano-sheets is likely quite high. This interface resistance may limit thethermal conduction through the aerogel and increases its effectivethermal resistances. However, since the graphene nanosheetsbridge the whole GA bulk, the 3D networks still achieves moreeffective heat transport than dispersed rGO in composites [8,23].

Furthermore, the measurement technique may involve errorsdue the limited resolution of IR camera, the convection due to highsurface areas of the GAs as well as the variation in thermal conduc-tivities of the GAs and reference materials with temperature. Allthe errors should be taken into consideration and minimized dur-ing the experiments.

3.2. Effects of thermal annealing treatment on thermal conductivitiesof GAs

After thermal annealing, the thermal conductivities of GA5–7were enhanced (kGA = 0.18 ± 0.006, 0.23 ± 0.023 and 0.31 ± 0.023 W/(m K), respectively) compared to GA1–3 without annealing. Thethermal conductivity of GA8 (0.28 ± 0.016 W/(m K)) is slightly

A1–8 respectively. All images show the interconnected 3D network structures. Withe GO concentration.

Table 1Synthesis conditions, density, volume fraction and thermal conductivity of the GAs.

Samples GOconcentration(mg/ml)

Thermalannealing

Density(mg/cm3)

Volumefraction(%)

ThermalconductivitykGA (W/(m K))

GA1 1 Without 14.1 0.67 0.12 ± 0.006GA2 2 Without 28.1 1.34 0.18 ± 0.013GA3 6 Without 42.8 2.04 0.24 ± 0.007GA4 12 Without 52.4 2.50 0.36 ± 0.015

GA5 1 With 16.4 0.78 0.18 ± 0.006GA6 2 With 28.2 1.34 0.23 ± 0.023GA7 6 With 40.0 1.90 0.31 ± 0.023GA8 12 With 49.0 2.33 0.28 ± 0.016

Fig. 3. Effects of GO concentrations and thermal annealing on thermal conductiv-ities of the GAs.

Fig. 4. XRD patterns of the GA4–5, 7 and 8. Broad peaks indicate the non-crystalaerogel structure. Compared to GA7, the peak of GA8 shifts right and indicates thesmaller interspacing between graphene nanosheets.

Fig. 5. The thermal conductivity of the GAs as a function of graphene volumefraction. Best fits from rule of mixtures (dashed line) and EMT (orange dots) areshown. For the rule of mixtures, the slope of the least-squares best fits to theexperimental data is the (kG–kair). For EMT, the values calculated assume akG = 30.2 W/(m K), a value which was obtained by manually fitting the data. (Forinterpretation of the references to color in this figure legend, the reader is referredto the web version of this article.)

Z. Fan et al. / International Journal of Heat and Mass Transfer 76 (2014) 122–127 125

lower than that of the sample without annealing (GA4) and is alsolower than GA7 which was annealed, but had a lower GOconcentration.

Post growth annealing treatments of carbon nanotubes (CNTs)or graphene, removes the residual functional groups and repairssome defects [20,48]. The improved thermal conductivities ofGA5–7 can be attributed to the significant elimination of saturatedsp3 bonds bearing functional groups (which cause enhanced pho-non scattering and hinder the thermal transport [44,45]) and for-mation of sp2-hybridized carbon atoms. In contrast, thedecreased thermal conductivity of the GA8 may be due to the con-densation of graphene nanosheets during thermal annealing, as isindicated by the right-shift of XRD spectrum for GA8 in Fig. 4. Pho-non scattering between multi-layered graphene sheets leads to asignificant decline of the instinct thermal conductivity.

3.3. Prediction of thermal boundary resistance and thermalconductivities of graphene nanosheets within GAs

The rule of mixtures [49] and effective medium theory (EMT)[50] have been applied to predict the range of the thermal conduc-tivity of the rGO nanosheets, as shown in Fig. 5. The GAs are con-sidered as a two-phase system consisting of rGO and air withthermal conductivities kG and kair (kair = 0.026 W/(m K) [42]). A firstestimate of the thermal conductivity of graphene aerogels can becalculated through the rule of mixtures:

kGA ¼ f kG þ ð1� f Þkair; ð2Þ

where f is the volume fraction of graphene. This model predicts thethermal conductivity of the rGO to be kG to be 12.2 W/(m K),neglecting the effects of the thermal boundary resistance betweennanosheets. Both the rule of mixtures and the EMT approximationsdo not consider the details of the microstructure of the GAs (poresize, shape, etc.) or convective heat transfer within pores, but both

provide an estimate of the thermal conductivity of the grapheneportion of the aerogel.

A more detailed effective medium theory (EMT) based modelcan also be used to estimate the thermal conductivity throughthe relationship:

kGA ¼ kG3kair þ 2f ðkG � kairÞ

ð3� f ÞkG þ kairf þ RBkairkGfH

" #; ð3Þ

where RB is the TBR between rGO and air (RB = 10�5 Km2/W [51,52])and H is the total thickness of rGO and is taken to be 3 nm in thiscalculation. The thickness of a rGO monolayer is reported to be0.6–0.9 nm [53,54], and here the GAs are assumed to consist of 5-layer rGO nanosheets on average. This model assumes that thegraphene nanosheets are randomly dispersed and not intercon-nected. It should be noted that although RB is incorporated in theEMT model, it does not represent the contact between nanosheets,but rather the resistance between the nanosheets and air. The ther-mal conductivity of the rGO of kG = 30.2 W/(m K) is extracted fromthis EMT model [5,55] and is considered an upper bound to thethermal conductivity. Thus, we report that the thermal conductivityof chemically-derived graphene in our work is in the range of

126 Z. Fan et al. / International Journal of Heat and Mass Transfer 76 (2014) 122–127

12.2–30.2 W/(m K), which is a factor of 1.8–4.4 higher than thevalue reported elsewhere [45].

4. Conclusions

In conclusion, the GAs are synthesized by a chemical reductionmethod to investigate the thermal conduction mechanisms. Acomparative infrared technique is developed to measure the ther-mal conductivities of porous materials. This work reports the firstbenchmark results of the thermal conductivities of the GAs as afunction of GO concentrations and also investigates the effects ofthermal annealing. In this work, the thermal conductivity of theGAs is measured to be 0.12–0.36 W/(m K), which is much lowerthan that of pristine graphene. These low values are likely due tothe high porosity of the GAs, low quality, small size of the chemi-cally derived graphene, and the large thermal boundary resistanceat graphene–graphene and graphene–air contacts. In general, thethermal conductivity of the GAs can be controlled by optimizingthe GO concentration and other synthesis conditions (i.e. synthesistemperature and time). Post thermal annealing increases the ther-mal conductivities for the GAs synthesized with GO suspension oflow graphene concentration. In addition, by fitting the data withrule of mixtures and effective medium theory, the thermal conduc-tivity of rGO is estimated to be 12.2–30.2 W/(m K). Due to theirunique mesoporous network structure, GAs have great potentialto be developed into graphene-based composites by taking advan-tage of capillary forces to infiltrate the porous network.

Conflict of interest

None declared.

Acknowledgements

The authors deeply acknowledge the Start up Grant R-265-000-361-133, SERC 2011 Public Sector Research Funding (PSF) Grant R-265-000-424-305 and China Scholarship Council for the fundingsupport. We also thank Asst. Prof. Chua Kian Jon, Dr. Zhao Xingand Mr. Sun Bo for their support on thermal conductivitymeasurements.

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