Abstract
A technique of molecular statistical calculations, developed and improved with the active participation of workers at the Institute of Physical Chemistry and Electrochemistry, allows the accurate estimation of the chromatographic retention of analytes. The resulting version of molecular statistical method (with regard to conformational non-rigidity) is used to predict the values of alkylbenzene retention under conditions of gas adsorption chromatography. The accuracy of estimating the retention indices is compared to results from current machine learning approaches of predicting retention (for gas-liquid chromatography). The effectiveness of separating structural hydrocarbon isomers on different columns is also compared.
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