Self-association of six mono-hydroxyl aliphatic alcohols in CCl4 has been investigated with the use of infrared (IR) spectroscopy and methods for curve resolution. The alcohols were 1-octanol, 1-propanol, 2,4-dimethyl-3-pentanol, 2-methyl-2-propanol, 3-ethyl-3-pentanol, and 3-methyl-2-pentanol. Curve resolution of the OH stretching region assumes that distinct associates due to hydrogen bonding can be regarded as chemical species. The resolution aimed at determining the number, the structure, and the sizes of the associates in different concentration ranges. Analyses of the spectra, in limited concentration ranges, resulted in models containing up to three different species: monomers, open-chain multimers, and cyclic multimers. The size of the multimers was found to increase with increasing alcohol concentration. The resolved concentration profiles enable prediction of molar concentrations of the different alcohol species at all solute concentrations and estimation of the equilibrium constants involved. The molar extinction coefficients for all species at all wavenumbers can also be estimated.
In order to improve the storage and CPU time in the numerical analysis of large two-dimensional (hyphenated, second-order) infrared spectra, a data-preprocessing technique (compression) is presented which is based on B-splines. B-splines have been chosen as the compression method since they are wellsuited to model smooth curves. There are two primary goals of compression: a reduction of file size and a reduction of computation when analyzing the compressed representation. The compressed representation of the spectra is used as a substitute for the original representation. For the particular example used here, approximately 0.16 bit per data element was required for the compressed representation in contrast with 16 bits per data element in the uncompressed representation. The compressed representation was further analysed using principal component analysis and compared with a similar analysis on the original data set. The results shows that the principal compotent model of the compressed representation is directly comparable with the principal component model of the original data.
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