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Investigation on Exciton Relaxation Kinetics of ZnCuInS/ZnSe/ZnS Quantum Dots by Time-Resolved Spectroscopy Techniques
Xi-hua Du*,Wen-chang Zhuang,Xiao-qin Shi,Chang-jun Feng
Author NameAffiliationE-mail
Xi-hua Du* School of Chemistry and Chemical Engineering, Xuzhou Institute of Technology, Xuzhou 221111, China dxh@xzit.edu.cn 
Wen-chang Zhuang School of Chemistry and Chemical Engineering, Xuzhou Institute of Technology, Xuzhou 221111, China  
Xiao-qin Shi School of Chemistry and Chemical Engineering, Xuzhou Institute of Technology, Xuzhou 221111, China  
Chang-jun Feng School of Chemistry and Chemical Engineering, Xuzhou Institute of Technology, Xuzhou 221111, China  
Abstract:
Based on the location of bromine substituents and conjugation matrix, a new substituent po-sition index 0X 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 S?,ΔfH? and ΔfG? 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.
Key words:  Polybrominated diphenylamine, Neural networks, Molecular shape index, Elec-tronegativity distance vector, Substituent position index, Thermodynamic properties
FundProject:
神经网络法研究多溴代二苯胺热力学性质
堵锡华*,庄文昌,史小琴,冯长君
摘要:
基于溴取代位置及邻接矩阵,定义新的取代基指数0X,并计算了二苯胺和209个多溴代二苯胺的分子形状指数Km和电性距离矢量Mm,经最佳变量子集回归建立了210种该有机污染物热力学性质与0X、K3、M29、M36指数的定量结构-性质相关性(QSPR)模型. 将这4个结构参数作为BP神经网络的输入层结点,分别采用4:21:1、4:24:1、4:24:1的网络结构,利用BP算法获得了三个令人满意的QSPR模型,其总相关系数R分别为0.9999、0.9997和0.9995,标准误差分别为1.036、1.469和1.510,利用该模型得到的S?、ΔfH?和ΔfG?的预测值,与文献值的相对平均误差分别为0.11%、0.34%和0.24%,两者吻合度非常理想,说明该模型具有很好的稳定性、相关度和预测能力,结果表明多溴代二苯胺的热力学性质与0X、K3、M29和M36有很好的非线性关系,证明利用新定义的取代基指数建立的ANN模型对多溴代二苯胺性质的预测是合理的、适用的.
关键词:  多溴代二苯胺,神经网络,分子形状指数,电性距离矢量,取代基指数,热力学性质
DOI:10.1063/1674-0068/28/cjcp1406109
分类号: