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Research Papers: Conduction

Thermal Conductivity of Turbostratic Carbon Nanofiber Networks

[+] Author and Article Information
Matthew L. Bauer, Christopher B. Saltonstall, Patrick E. Hopkins, Pamela M. Norris

Department of Mechanical and
Aerospace Engineering,
University of Virginia,
Charlottesville, VA 22904-4746

Zayd C. Leseman

Department of Mechanical and Industrial Engineering,
University of New Mexico,
Albuquerque, NM 87131

Thomas E. Beechem

Sandia National Laboratories,
Albuquerque, NM 87185

Contributed by the Heat Transfer Division of ASME for publication in the JOURNAL OF HEAT TRANSFER. Manuscript received April 8, 2015; final manuscript received November 27, 2015; published online March 15, 2016. Assoc. Editor: Alan McGaughey.The United States Government retains, and by accepting the article for publication, the publisher acknowledges that the United States Government retains, a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for United States government purposes.

J. Heat Transfer 138(6), 061302 (Mar 15, 2016) (9 pages) Paper No: HT-15-1272; doi: 10.1115/1.4032610 History: Received April 08, 2015; Revised November 27, 2015

Composite material systems composed of a matrix of nanomaterials can achieve combinations of mechanical and thermophysical properties outside the range of traditional systems. The microstructure of the system dictates the rate, in which heat moves through the material. In this work, air/carbon nanofiber networks are studied to elucidate the system parameters influencing thermal transport. Thermal properties are measured with varying initial carbon fiber fill fraction, environment pressure, loading pressure, and heat treatment temperature (HTT) through a bidirectional modification of the 3ω technique. The nanostructure of the individual fibers is characterized with small angle X-ray scattering and Raman spectroscopy providing insight to individual fiber thermal conductivity. Measured thermal conductivity of the carbon nanofiber networks varied from 0.010 W/(m K) to 0.070 W/(m K). An understanding of the intrinsic properties of the individual fibers and the interactions of the two-phase composite is used to reconcile low measured thermal conductivities with predictive modeling. Accounting for fiber-to-fiber interactions and the nuanced changes in the composite as pressure is applied is necessary to successfully model thermal transport in system.

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Figures

Grahic Jump Location
Fig. 1

Average Raman spectra of each sample. Each spectrum was first normalized to the G peak intensity and then averaged. (a) The averaged spectra of the unannealed samples. (b) The averaged spectra of the annealed S1 series.

Grahic Jump Location
Fig. 2

Guinier plot of SAXS intensity decay. The lack of linear region over this q regime indicates an absence of monodisperse voids observed in other carbon fiber samples.

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Fig. 3

Scanning electron microscope image of a carbon fiber sample

Grahic Jump Location
Fig. 4

Raw data and modeled fit from sample S1 with an applied pressure of 220 kPa. The experimental uncertainty in each data point is slightly smaller than the data markers. The measured values match the inputs used in Fig. 5.

Grahic Jump Location
Fig. 5

Sensitivity of the 3ω experiment to composite samples'effective thermal conductivity and volumetric heat capacity as well as the contact resistance between the mount and sample. This plot was generated with ke = 0.024 W/(m K), Ce = 3 × 105 J/(m3 K), and Rp = 6 × 10−5 K m2/W, similar to the fourth data point in Fig. 6. The change in direction of the contact resistance sensitivity above 10,000 Hz only exists due to the presence of the SiOx layer closer to the heater. At greater applied pressures, the signal's sensitivity to the carbon fibers' thermal conductivity and heat capacity is increased. At low applied pressures, the experiment can lose sensitivity to these properties [15].

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Fig. 6

Best fit results of data taken on S1 (without heat treatment) with measured density of 90 kg/m3. Measurements were taken at six unique compressive pressures, with the sample thermal conductivity, sample volumetric heat capacity, and the sample to mount contact resistance simultaneously fit. This data are representative of data taken on each sample. The fitting error propagated from sources of uncertainty in the system is estimated at 9% for the sample's thermal conductivity, 6% for the volumetric heat capacity, and 4% for the contact resistance between the sample and the passivation layer.

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Fig. 7

Measured thermal conductivity values from sample S5 at both vacuum and atmospheric pressure. Carbon fill fraction is calculated from the best fit volumetric heat capacity using Eq. (2). Also, plotted is the SFM accounting for varying sample properties as pressure is applied.

Grahic Jump Location
Fig. 8

Normalized modeled response of 200 kg/m3 dense carbon nanofiber composite (S5) as pressure is applied. The total thermal conductivity response, ke, only increases due to the role of thermal conductance through fiber contacts. Alternatively, increasing carbon fiber fill fraction does not increase effective thermal transport while excluding additional fiber-to-fiber contacts. The contribution of gas conductivity decreases at greater pressures due to decreasing pore sizes. The bending over of fibers at greater applied pressures also causes a decrease in the thermal conductivity.

Grahic Jump Location
Fig. 9

Best fit 3ω thermal conductivity results for nonheat-treated samples S1, S2, S3, S4, and S5 (densities of 90, 110, 130, 160, and 200 kg/m3, respectively). All the data are acquired at room temperature and atmospheric pressure. The thermal conductivity predictions from the SFM (dashed lines) are also plotted for initial fill fractions ranging from 4% to 12% in steps of 2% (ϕ0). As pressure is applied, the fill fraction increases to a maximum value of ϕ=40%.

Grahic Jump Location
Fig. 10

Best fit data from the heat-treated sample series (S1). The measured thermal conductivity increases significantly from the as-grown sample compared to the heat-treated samples, with the sample which underwent a 1500 °C HTT showing an additional increase compared to the more moderately heated samples. The change in effective thermal conductivity with respect to carbon fiber fill fraction has increased with heat treatment. Over the data, the SFM is plotted with carbon fiber thermal conductivities of 40, 80, 120, and 160 W/(m K), respectively.

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