文献类型：期刊文章

作　　者：堵锡华[1] 庄文昌[1] 史小琴[1] 冯长君[1]

机构地区：[1]徐州工程学院化学化工学院,徐州221111

出　　处：《Chinese Journal of Chemical Physics》

年　　份：2015

卷　　号：28

期　　号：1

起止页码：59-64

语　　种：中文

收录情况：AJ、CAS、CSCD、CSCD2015_2016、INSPEC、JST、RSC、SCI、SCI-EXPANDED(收录号：WOS:000351806100010)、SCIE、SCOPUS、WOS、ZGKJHX、普通刊

摘　　要：Based on the location of bromine substituents and conjugation matrix, a new substituent po- sition index ~X not only was defined, but also molecular shape indexes Km and electronega- tivity distance vectors Mm of diphenylamine and 209 kinds of polybrominated diphenylamine （PBDPA） molecules were calculated. Then the quantitative structure-property relationships （QSPR） among the thermodynamic properties of 210 organic pollutants and 0X, K3, M29, M36 were founded by Leaps-and-Bounds regression. Using the four structural parameters as input neurons of the artificial neural network, three satisfactory QSPR models with network structures of 4：21：1, 4：24：1, and 4：24：1 respectively, were achieved by the back-propagation algorithm. The total correlation coefficients R were 0.9999, 0.9997, and 0.9995 respectively and the standard errors S were 1.036, 1.469, and 1.510 respectively. The relative mean deviation between the predicted value and the experimental value of Sθ, AfHe and △fGθ- were 0.11%, 0.34% and 0.24% respectively, which indicated that the QSPR models had good stability and superior predictive ability. The results showed that there were good nonlinear correlations between the thermodynamic properties of PBDPAs and the four structural pa- rameters. Thus, it was concluded that the ANN models established by the new substituent position index were fully applicable to predict properties of PBDPAs.

关 键 词：Polybrominated diphenylamine  Neural networks  Molecular shape index  Elec-tronegativity distance vector  Substituent position index  Thermodynamic properties  

分 类 号：O]