Chemometrics in electroanalytical chemistry

被引：44

作者：

Esteban, M. ^{[1
]}

Arino, C. ^{[1
]}

Diaz-Cruz, J. M. ^{[1
]}

机构：

[1] Univ Barcelona, Fac Quim, Dept Quim Anal, E-08028 Barcelona, Spain

来源：

CRITICAL REVIEWS IN ANALYTICAL CHEMISTRY | 2006年 / 36卷 / 3-4期

关键词：

artificial neural networks; chemometrics; deconvolution; multicomponent systems; multivariate analysis; partial least squares; soft-modelling; voltammetry;

D O I：

10.1080/10408340600969981

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

The use of chemometrics in electroanalytical chemistry is not as popular as in spectroscopy, although recently, application of these methods for mathematical resolution of overlapping signals, calibration and model identification have been increasing. Self-modelling curve resolution and multivariate analysis have been shown to be very powerful for in the analysis of electroanalytical data, especially for multianalyte calibration and modelling in multicomponent dynamic systems. In this paper, an overview on the application of chemometrics to electroanalytical data is presented, with special attention to the contributions of the last decade.

引用

页码：295 / 313

页数：19

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