Thermally conductive resins are needed for fuel cell bipolar plates. Varying amounts of three different carbons (carbon black, synthetic graphite particles, and carbon fiber) were added to Vectra A950RX Liquid Crystal Polymer. The resulting single filler composites were tested for thermal conductivity. In addition, the effects of single fillers and combinations of two different carbon fillers were studied via a factorial design. Synthetic graphite caused the largest statistically significant increase in composite through plane and in plane thermal conductivity. Composites containing synthetic graphite/carbon black and synthetic graphite/carbon fiber caused a statistically significant increase in through plane and in plane thermal conductivity.
Thermally conductive resins are needed for bipolar plates in fuel cells. Currently, the materials used for these bipolar plates often contain a single type of graphite in a thermosetting resin. In this study, varying amounts of two different types of polyacrylonitrile based carbon fibers, Fortafil 243 and Panex 30, were added to a thermoplastic matrix (Vectra A950RX Liquid Crystal Polymer). The resulting single filler composites were tested for thermal conductivity and a simple exponential thermal conductivity model was developed for the square root of the product of the inplane and through-plane thermal conductivity ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi k in k thru p . The experiments showed that the through-plane thermal conductivity was similar for composites up to 40 vol % fiber. However, at higher loadings, the Panex 30 samples exhibited higher thermal conductivity. The experiments also showed that the in-plane thermal conductivity of composites containing Panex 30 was higher than those containing Fortafil 243 for all volume fractions studied. Finally, the model agreed very well with experimental data covering a large range of filler volume fraction (from 0 to 55 vol % for both single filler systems). The model can be used with existing through-plane thermal conductivity models to predict in-plane thermal conductivity.
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