Quantitative structure-retention relationships applied to chromatographic retention of ecotoxicity of anilines and phenols
Publish place: Asian Journal of Green Chmistry، Vol: 3، Issue: 2
Publish Year: 1396
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_AJGC-3-2_006
تاریخ نمایه سازی: 22 اردیبهشت 1397
Abstract:
Aniline, phenol, and their derivatives are widely used in industrial chemicals that consequently have a high potential for environmental pollution. Genetic algorithm and partial least square (GA-PLS), kernel partial least square (GA-KPLS) and Levenberg-Marquardt artificial neural network (L-M ANN) techniques were used to investigate the correlation between chromatographic retention (log k) and descriptors for modelling the toxicity to fathead minnows of anilines and phenols. Descriptors of GA-PLS model were selected as inputs in L- M ANN model. The described model does not require experimental parameters and potentially provides useful prediction for log k of new compounds. Finally a model with a low prediction error and a good correlation coefficient was obtained by L-M ANN. The stability and prediction ability of L-M ANN model was validated using external test set techniques.
Keywords:
Ecotoxicity , Environmental hazard , Phenols , Anilines , Quantitative stature retention relationship
Authors
Mehrdad Shahpar
Director of Ilam Petrochemical Company
Sharmin Esmaeilpoor
Department of Chemistry, Payame Noor University,Tehran, Iran