文献类型：期刊文献

英文题名：Modelling and optimization of the pore structure of carbon aerogels using an artificial neural network5

作者：Yang, Zhen[1];Qiao, Wen-Ming[1];Liang, Xiao-Yi[1]

机构：[1]East China Univ Sci & Technol, Key Lab Special Funct Polymer Mat & Their Related, Minist Educ, State Key Lab Chem Engn, Shanghai 200237, Peoples R China

年份：2017

卷号：32

期号：1

起止页码：77

外文期刊名：NEW CARBON MATERIALS

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000396641400011)】；

基金：National Natural Science Foundation of China (21177038).

语种：英文

外文关键词：Carbon aerogels; Pore structure; Neural network; Training algorithms; Modelling

摘要：An intelligent simulation method for predicting and optimizing the pore structure of carbon aerogels is proposed by using an artificial neural network (ANN) algorithm. The ANN model has been optimized based on an improved genetic algorithm from six typical training algorithms. The volumes and diameters of pores in the simulated samples are predicted by the optimized ANN model, which shows correlation coefficients R-2 of 0. 992 and 0. 981 and foot-mean-square prediction errors (RMSPE) of 0.077 and 0.054 between the predicted and experimental values for the volumes and diameters of pores, respectively. The proposed model is expected to have practical applications in the pore structure control of carbon aerogels.