Multivariate optimization techniques in analytical chemistry - an overview
| Autor: | Erik Galvão Paranhos da Silva, Sergio Luis Costa Ferreira, Rafael Vasconcelos Oliveira, Caio S.A. Felix, Gilson B. Dourado, Valfredo Azevedo Lemos, Antônio Fernando de Souza Queiroz, Daniel Levi França da Silva, Vanessa Sales de Carvalho |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Central composite design
Computer science Design of experiments 010401 analytical chemistry Analytical chemistry Analytical Chemistry (journal) 02 engineering and technology Factorial experiment 021001 nanoscience & nanotechnology Multivariate optimization 01 natural sciences 0104 chemical sciences Analytical Chemistry Pareto chart Quadratic equation Robustness (computer science) 0210 nano-technology Spectroscopy |
| Zdroj: | Microchemical Journal. 140:176-182 |
| ISSN: | 0026-265X |
| DOI: | 10.1016/j.microc.2018.04.002 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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