Response surface methodology (RSM) as a tool for optimization in analytical chemistry

被引：4868

作者：

Bezerra, Marcos Almeida ^{[1
,2
]}

Santelli, Ricardo Erthal ^{[2
]}

Oliveira, Eliane Padua ^{[2
]}

Villar, Leonardo Silveira ^{[2
]}

Escaleira, Luciane Amlia ^{[2
]}

机构：

[1] Univ Estadual Sudoeste Bahia, Lab Quim Analit, Rua Jose Moreira Sobrinho S-N, BR-45206190 Jequie, BA, Brazil

[2] Univ Fed Fluminense, Dept Geoquim, BR-24020150 Niteroi, RJ, Brazil

来源：

TALANTA | 2008年 / 76卷 / 05期

关键词：

response surface methodology; three-level factorial design; Box-Behnken design; central composite design; Doehlert design; desirability function; artificial neural network modeling;

D O I：

10.1016/j.talanta.2008.05.019

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

A review about the application of response surface methodology (RSM) in the optimization of analytical methods is presented. The theoretical principles of RSM and steps for its application are described to introduce readers to this multivariate statistical technique. Symmetrical experimental designs (three-level factorial, Box-Behnken, central composite, and Doehlert designs) are compared in terms of characteristics and efficiency. Furthermore, recent references of their uses in analytical chemistry are presented. Multiple response optimization applying desirability functions in RSM and the use of artificial neural networks for modeling are also discussed. (C) 2008 Published by Elsevier B.V.

引用

页码：965 / 977

页数：13

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