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Application of Multiway Chemometric Techniques for Analysis of AC Voltammetric Data
Author(s) -
Jaworski Aleksander,
Wikiel Hanna,
Wikiel Kazimierz
Publication year - 2009
Publication title -
electroanalysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 128
eISSN - 1521-4109
pISSN - 1040-0397
DOI - 10.1002/elan.200804453
Subject(s) - partial least squares regression , multilinear map , robustness (evolution) , calibration , inverse , decomposition , chemometrics , least squares function approximation , computer science , analytical chemistry (journal) , biological system , chemistry , mathematics , statistics , chromatography , machine learning , organic chemistry , estimator , biochemistry , geometry , biology , pure mathematics , gene
Three multiway calibration techniques have been applied for determining of the suppressor concentration in industrial copper electrometallization baths used in semiconductor manufacturing. Parallel factor analysis (PARAFAC) for multiway array decomposition coupled with inverse least squares (ILS) regression (PARAFAC/ILS), direct trilinear decomposition (DTLD) coupled with ILS (DTLD/ILS), and multilinear partial least squares (N‐PLS) regression were employed to develop and test calibration models based on trilinear AC voltammetric data. All techniques employed comparatively produce reliable calibration model and provide quantitative information about its robustness.