High-precision thermal conductivity predictions of nano-porous carbon aerogel composites at various temperatures

The high-temperature thermal conductivity (7eff) of carbon aerogel composites is a crucial parameter for their applications in thermal insulation fields. Herein, we develop a method that combining the inverse problem method and the Lattice Boltzmann method (LBM) to invert the high-temperature intrinsic thermal conductivity (7int) of carbon matrix, and then predict the composites 7eff at various temperatures using LBM. The 7int of carbon matrix is difficult to acquire owing to the material structural evolution that occurs during the carbonization process. For the first time, we calculate the 7int to range from 0.45 W/m/K to 21 W/m/K within the temperature range of 873 K to 1173 K through backpropagation. The composites 7eff is then predicted based on the solid phase 7int, pore structure and radiation effects, which exhibits a maximum deviation of only 0.5 % with the experimental values. Furthermore, the effects on the composites 7eff of property parameters such as carbon aerogel density and fiber density, as well as the environmental factor of pressure are evaluated, enabling the prediction of composites 7eff variations with different compositions and environmental conditions. The research findings present a more efficient method for predicting the high-temperature thermal conductivities of carbon aerogel composites, providing the theoretical guidance for improving their thermal insulation performance.