journal article·2004-06

The role of structure on the thermal properties of graphitic foams

J. W. Klett, A. D. McMillan, N. C. Gallego, C. A. Walls

Journal of Materials Science· Volume 39· Issue 11
Publisher page

Abstract

A high conductivity graphite foam developed at Oak Ridge National Laboratory (ORNL) owes its unique thermal properties to the highly aligned graphitic structure along the cell walls. The material exhibits a peak in thermal conductivity at temperatures similar to that of highly ordered natural graphite, indicating the foam has an extremely graphitic nature. This paper explores the graphitic structure of the foam and attempts to correlate the morphology of the ligaments with the bulk thermal properties, up to 182 W/m·K. First, the manufacturing process of the foam and the resulting material properties are reported. Then, several models for representing the bulk materials properties are reviewed. Examination by optical image analysis, scanning electron microscopy (SEM) and transmission electron microscopy (TEM) was used to examine the structure of the graphite foam. In addition, crystallographic structure determined by X-ray diffraction is reported. A simple two parameter model of the morphology was developed and then used to predict the overall thermal properties of the foam based on the assumed highly ordered ligament structure. This new model correlated (within 5%) thermal conductivity to density of several foams, provided the average ligament conductivity could be accurately represented. From the new model and the material characterization data, it was determined that the average ligament thermal conductivity of the foam is >1650 W/m·K at room temperature, and increases to more than 2300 W/m·K at liquid nitrogen temperatures.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Heat and Mass Transfer in Porous Media · Thermal properties of materials · Phase Change Materials Research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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