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Quantitative prediction of substituted products based on quantum‐chemical parameters and neural network method
Author(s) -
XueYe Wang,
Huang Song
Publication year - 2000
Publication title -
chinese journal of chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.28
H-Index - 41
eISSN - 1614-7065
pISSN - 1001-604X
DOI - 10.1002/cjoc.20000180412
Subject(s) - chemistry , ab initio , quantum , electrophile , quantum chemical , computational chemistry , nitration , artificial neural network , quantum chemistry , population , atomic orbital , electron , quantum mechanics , organic chemistry , reaction mechanism , molecule , artificial intelligence , catalysis , physics , demography , sociology , computer science
The criterion of orientating group of electrophilic aromatic nitration was discussed by means of pattern recognition method with quantum‐chemical parameters as features, and the product ratios of the reactions were quantitatively calculated using artificial neural network (ANN) method with the same parameters as inputs, based on the ab initio calculation of quantum chemistry, The quantum‐chemical parameters involved orbital energy, orbital electron population, atomic total electron density and atomic net charge. The predicted values are in agreement with experimental results and the predicted error of the ANN with quantum‐chemical parameters for the reaction is the smallest among the all methods.