Multivariate optimization techniques in analytical chemistry-an overview

被引:104
作者
Ferreira, Sergio L. C. [1 ,2 ]
Lemos, Valfredo A. [2 ,3 ]
de Carvalho, Vanessa S. [1 ,2 ]
da Silva, Erik G. P. [2 ,4 ]
Queiroz, Antonio F. S. [5 ]
Felix, Caio S. A. [1 ,2 ]
da Silva, Daniel L. F. [1 ,2 ]
Dourado, Gilson B. [5 ]
Oliveira, Rafael V. [1 ,6 ]
机构
[1] Univ Fed Bahia, Grp Pesquisa Quim & Quimiometria, BR-40170270 Salvador, BA, Brazil
[2] Univ Fed Bahia, INCT, Energia & Ambiente, BR-40170290 Salvador, BA, Brazil
[3] Univ Estadual Sudoeste Bahia, BR-45206510 Jequie, Brazil
[4] Univ Estadual Santa Cruz, Dept Ciencias Exatas & Tecnol, BR-45662900 Ilheus, Brazil
[5] Univ Fed Bahia, Inst Geociencias, BR-40170290 Salvador, BA, Brazil
[6] Inst Fed Educ Ciencia & Tecnol Bahia, BR-44900000 Irece, Brazil
关键词
Factorial designs; Box Behnken design; Central composite design; Doehlert matrix; Multiple response functions; Robustness; BOX-BEHNKEN DESIGN; LIQUID-LIQUID MICROEXTRACTION; ATOMIC-ABSORPTION-SPECTROMETRY; SOLID-PHASE EXTRACTION; MULTIPLE-RESPONSE OPTIMIZATION; CONSTRAINED MIXTURE DESIGN; ARTIFICIAL NEURAL-NETWORK; MULTIRESPONSE OPTIMIZATION; DESIRABILITY FUNCTION; ICP OES;
D O I
10.1016/j.microc.2018.04.002
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
This review presents fundamentals and a critical evaluation of the multivariate optimization techniques employed by the analytical chemistry. Characteristics of the surface response methodologies (SRM) are shown and compared. Additionally, a bibliographic survey was performed in the web of science database using as keywords names of the chemometric tools utilized for experimental designs. Papers classified in the analytical chemistry area demonstrated that the two-level full factorial design had often been used for preliminary assessment of factors. For determination of critical conditions using quadratic models, the central composite design (CCD) is the technique most utilized by the analytical chemists. Remarks about standardized effects and the Pareto chart, description of the several multiple response functions employed in experimental designs, efficiencies of the SRM's and robustness tests are also discussed. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:176 / 182
页数:7
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