详细信息
High-precision thermal conductivity predictions of nano-porous carbon aerogel composites at various temperatures ( SCI-EXPANDED收录 EI收录)
文献类型:期刊文献
英文题名:High-precision thermal conductivity predictions of nano-porous carbon aerogel composites at various temperatures
作者:Wang, Peng[1];Zhou, Xiaoyi[1];Zhang, Yayun[1,2];Xing, Yue[3];Liang, Xiubing[3];Niu, Bo[1,2];Long, Donghui[1,2]
机构:[1]East China Univ Sci & Technol, State Key Lab Chem Engn, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Key Lab Specially Funct Mat & Related Technol, Shanghai 200237, Peoples R China;[3]Natl Innovat Inst Def Technol, Beijing 100071, Peoples R China
年份:2025
卷号:60
外文期刊名:THERMAL SCIENCE AND ENGINEERING PROGRESS
收录:;EI(收录号:20250817925574);WOS:【SCI-EXPANDED(收录号:WOS:001432422500001)】;
基金:This work was supported by the National Natural Science Foundation of China (Nos. 52472095 and U2341291) .
语种:英文
外文关键词:Carbon aerogel composites; Thermal conductivity; Lattice Boltzmann method; Inverse problem method
摘要: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.
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