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Detectability of concentration‐dependent factors by application of PCA. An indicator curve for the determination of important principal components and a post‐correction for transformation of principal components to factors
Author(s) -
Németh Zsolt István,
Rákosa Rita
Publication year - 2018
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.2998
Subject(s) - principal component analysis , absorbance , chemistry , ethanol , biological system , analytical chemistry (journal) , transformation (genetics) , absorption (acoustics) , spectral line , binary number , chromatography , mathematics , statistics , optics , physics , organic chemistry , biochemistry , gene , biology , arithmetic , astronomy
A semi empirical model of light absorption for binary liquid mixtures, which includes linear, parabolic, and periodic terms of concentration‐dependent factors, has been developed and applied for investigating the revealability of the factors. Concentration‐dependent near infrared spectra of ethanol‐water mixtures and a two‐component model were decomposed by principal component analysis. Generated from the principal component analysis results and called the m ean c oefficient of d etermination, an indicator is introduced for separating the important or systematic principal components with deterministic information (factor PCs) from stochastic principal components originating from spectral noise (error PCs). Moreover, a post‐correction method is proposed to pull the concentration‐dependent factor effects out of the systematic principal components. The first PC of ethanol‐water NIR mixture spectra defines the contributions of clusters of both water and ethanol molecules in the solution to resultant absorbance signals. The second PC includes partial absorptions from ethanol‐water dimers and ethanol‐water‐ethanol trimers. The third PC is assumed to reflect concentration‐dependent restructuring of mixture structure.