Prediction of limiting activity coefficients by a modified separation of cohesive energy density model and UNIFAC

Abstract

A modified separation of cohesive energy density (MOSCED) model was developed to predict limiting activity coefficients (7"'s) using only pure component parameters. For 3357 y"s, an average error of 9.1 % was achieved with very few errors greater than 30%. The data included activity coefficients of both protic and aprotic (but nonaqueous) systems over wide temperature ranges. The results compared very well with the predictions of the leading predictive technique in the literature, the UNIFAC solution of groups approach (average error 20.5 %).

Multiparameter solubility model of fullerene C60

“…The major difference in this model is to consider hydrogen bonding to be an asymmetrical interaction, i.e., a molecule possesses an acceptor and a donor component. Their model was modified by Thomas and Eckert [28] and the hydrogen bonding components were named acidity and basicity parameters. These authors also included a different parameter to take into account the receptor difference between two components.…”

Characterization of Mixtures Part 1: Prediction of Infinite‐Dilution Activity Coefficients Using Neural Network‐Based QSPR Models

“…The literature reveals various methods and models useful for the prediction or calculation of infinite-dilution activity coefficients: for example, theoretical regular solution theory models [9 -11], models based upon an equation of state [12 -14]; models using only pure component parameters [15,16], and group contribution methods [17 -21]. A variety of empirical models have been developed for the solubility (or for the infinite-dilution activity coefficients) of solutes in water [22 -24].…”

Predicting infinite dilution activity coefficients of organic compounds in water by quantum-connectivity descriptors

“…Thus, many predictive models have been reported among which the MOSCED [5], ASOG [6] and UNIFAC [7] are known to be very powerful in terms of their accuracy of prediction. However, due to the strong non-ideality existing in aqueous solutions, these traditional predictive methods tend to be only moderately successful in predicting c ¥ of organic solutes in water.…”