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Multivariate optimization techniques in analytical chemistry-an overview

机译:分析化学中的多变量优化技术 - 概述

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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.
机译:本综述提出了对分析化学采用的多变量优化技术的基础和关键评价。 显示并比较了表面响应方法(SRM)的特征。 此外,使用用于实验设计的化学计量工具的关键字名称,在科学数据库网络中进行书目调查。 分析化学区分类的论文证明,两级全部因子设计通常用于对因素的初步评估。 为了使用二次模型确定临界条件,中央复合设计(CCD)是分析化学家最利用的技术。 备注关于标准化效果和帕累托图表,还讨论了实验设计中采用的几种多重反应函数的描述,SRM和鲁棒性测试的效率。 (c)2018 Elsevier B.v.保留所有权利。

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