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A Novel Quality Criteria for Optimization of Chromatographic Multicomponent Separations
Author(s) -
Yang Jyisy,
Chen YiFen
Publication year - 1999
Publication title -
journal of the chinese chemical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.329
H-Index - 45
eISSN - 2192-6549
pISSN - 0009-4536
DOI - 10.1002/jccs.199900014
Subject(s) - weighting , chemistry , sigmoid function , resolution (logic) , chromatography , separation (statistics) , selection (genetic algorithm) , chromatographic separation , filter (signal processing) , function (biology) , statistics , computer science , high performance liquid chromatography , artificial intelligence , mathematics , medicine , evolutionary biology , biology , artificial neural network , computer vision , radiology
This study presents a Chromatographic Optimization Function (COF) to optimize chromatographic separation conditions. The COF proposed herein provides several advantages over conventional COFs, including the ability to eliminate the ambiguous selection of the weighting factors and easily obtain the acceptable or maximum resolution in the shortest separation time. The parameters used to construct this COF are in the form of sigmoidal functions to reduce the weight of the response for less acceptable conditions and to filter out undesired situations. In addition, resolution between peaks, length of separation time, and number of peaks separated are used as parameters for constructing the proposed COF. Closely examining the performance of the COF for both simulated and experimental chromatographic separations reveals an adequate correlation with human judgment and, also, creates no problems in selecting weighting factors.