Study of Complexation in Methanol/Water Mixtures by Infrared and Raman Spectroscopy and Multivariate Curve Resolution—Alternating Least-Squares Analysis

Abstract

The structure of the mobile phase in liquid chromatography plays an important role in the determination of retention behavior on reversed-phase stationary materials. One of the most commonly employed mobile phases is a mixture of methanol and water. In this work, infrared and Raman spectroscopic methods were used to investigate the structure of species formed in methanol/water mixtures. Chemometric methods using multivariate curve resolution by alternating least-squares analysis were used to resolve the overlapped spectra and to determine concentration profiles as a function of composition. The results showed that the structure of these mixtures could be described by a mixture model consisting of four species, namely, methanol, water, and two complexes, methanol/water (1:1) and methanol/water (1:4). The spectral frequencies and concentration profiles found from the Raman and infrared measurements were consistent with one another and with theoretical calculations.

Hydrogen bonding in aqueous ethanol solutions studied by Raman spectroscopy

“…The results [19] showed that the structure of water-methanol mixtures could be described by a mixture model consisting of four species-methanol, water, and two complexes: methanol/water (1:1) and methanol/water (1:4).…”

“…Multivariate curve resolution-alternating least squares (MCR-ALS) analysis [18] is a chemometric method, and recently, it has been used to study molecular association in alcohol solutions [19]. The results [19] showed that the structure of water-methanol mixtures could be described by a mixture model consisting of four species-methanol, water, and two complexes: methanol/water (1:1) and methanol/water (1:4).…”

Evaluation of conversion during the synthesis of aluminum (III) methacrylate-based copolymers using Raman spectroscopy and multivariate curve resolution

“…Basically, MCR-ALS is characterized by a bilinear decomposition of an original data matrix (D) into two matrices [31][32][33][34][35][36][37][38][39][40][41][42][43]: i) a matrix corresponding to the concentration profiles (C) and; ii) a second matrix related to the pure spectra profiles (S). MCR model can be expressed as D = CS T + ε, where the matrix D (dimensions m different individual spectra by n intensities measured at each spectral points) is approximated by the product of the matrix C (dimensions k components in the different by m rows of the data matrix) and matrix S T (transpose of matrix pure spectral profiles of dimensions k components by n columns of the original data matrix); and ε is the matrix of residuals (dimensions m different individual spectra by n intensities) containing the information not explained by the model.…”

“…MCR-ALS has been applied to Raman spectroscopy monitoring and some examples of representative studies are available in the open literature [35,36,39,42,48]. Among them, the following works deserve more emphasis.…”

“…Among them, the following works deserve more emphasis. Holden and coworkers [35] have investigated the structure of species formed in methanol/water mixtures with help of MCR-ALS, employed to resolve the overlapped spectra and to determine concentration profiles of the species. According to the results, the structure of methanol/water mixtures can be successfully predicted by using a mixture model consisting of four species.…”