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: Indicator MCD and post-correction transformation of PCA results

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 mean coefficient of determination, 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.