Metrics for estimating vapour pressure deviation from ideality in binary mixtures.

SAR QSAR Environ Res

Arnot Research and Consulting, Inc. (ARC), Toronto, ON, Canada.

Published: November 2023

AI Article Synopsis

  • A novel approach is proposed to evaluate interactions between two compounds in a binary mixture, focusing on deviations from ideal behavior as predicted by Raoult's law.
  • The study correlates chemical similarity metrics with Root-Mean Square Error (RMSE) of Raoult's law predictions, identifying the strongest correlation with a quantitative structure-activity relationship (QSAR) utilizing differences in Abraham parameters.
  • The findings indicate that Δlog K is the most significant descriptor of deviation from Raoult's law, which is crucial for estimating vapor pressures relevant to inhalation exposure assessments.

Article Abstract

A novel method is introduced for estimating the degree of interactions occurring between two different compounds in a binary mixture resulting in deviations from ideality as predicted by Raoult's law. Metrics of chemical similarity between binary mixture components were used as descriptors and correlated with the Root-Mean Square Error (RMSE) associated with Raoult's law calculations of total vapour pressure prediction, including Abraham descriptors, sigma moments, and several chemical properties. The best correlation was for a quantitative structure-activity relationship (QSAR) equation using differences in Abraham parameters as descriptors ( = 0.7585), followed by a QSAR using differences in COSMO-RS sigma moment descriptors ( = 0.7461), and third by a QSAR using differences in the chemical properties of log K, melting point, and molecular weight as descriptors ( = 0.6878). Of these chemical properties, Δlog K had the strongest correlation with deviation from Raoult's law (RMSE) and this property alone resulted in an of 0.6630. These correlations are useful for assessing the expected deviation in Raoult's law estimations of vapour pressures, a key property for estimating inhalation exposure.

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Source
http://dx.doi.org/10.1080/1062936X.2023.2280634DOI Listing

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