Multivariate Curve Resolution (MCR). Solving the mixture analysis problem

Abstract

This article is a tutorial that focuses on the main aspects to be considered when applying Multivariate Curve Resolution to analyze multicomponent systems, particularly when the Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) algorithm is used.

Pixel-Level Data Analysis Methods for Comprehensive Two-Dimensional Chromatography

“…It can also be applied to unfolded pixel-level LC Â LC-DAD or GC Â GC-TOFMS chromatograms wherein 1 t R and 2 t R are properly augmented in the same dimension or multiple sample chromatograms have been properly augmented to yield a bilinear 2D data matrix [66][67][68][69][70].…”

Experimento Didático De Quimiometria Para O Mapeamento De Pellets Farmacêuticos Utilizando Espectroscopia De Imagem Na Região Do Infravermelho Próximo E Resolução Multivariada De Curvas Com Mínimos Quadrados Alternantes: Um Tutorial, Parte Iv

“…A forma de calcular a porcentagem da variância explicada é descrita na Equação 5 e o ideal é que 100% da informação original seja expressa pelo modelo, sendo portanto desejado um valor para R 2 próximo a esse. 37,38 (…”

Optimization of Experimental Parameters in Analysis of Pharmaceutical Pellets by Near Infrared-Chemical Imaging (NIR-CI) and Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS)

“…One of the implications of choosing a good initial estimate is to avoid a possible local minimum, which could lead to a solution that is not representative of the system. 45,46 There are two possibilities of constructing an initial estimation matrix and one of them is with some previously known information, as pure substances signals obtained experimentally, under the same conditions in which the sample signal will be obtained. In this specific case, matrices containing 144 spectra were generated for each pure substance considered (sucrose, starch, silicon dioxide and ketoprofen).…”