Metrics for estimating vapour pressure deviation from ideality in binary mixtures

• Published in: SAR and QSAR in environmental research 2023-11, Vol.34 (11), p.943-961
• Main Authors: Celsie, A.K.D., Parnis, J.M., Brown, T.N.
• Format: Article
• Language: English
• Subjects: Binary mixtures; Chemical fingerprinting; Chemical properties; Correlation; Deviation; Inhalation; Melting point; Melting points; Molecular weight; Respiration; Root-mean-square errors; Structure-activity relationships; Vapor pressure
• ISSN: 1062-936X; 1029-046X
• DOI: 10.1080/1062936X.2023.2280634

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 (r2 = 0.7585), followed by a QSAR using differences in COSMO-RS sigma moment descriptors (r2 = 0.7461), and third by a QSAR using differences in the chemical properties of log KAW, melting point, and molecular weight as descriptors (r2 = 0.6878). Of these chemical properties, Δlog KAW had the strongest correlation with deviation from Raoult’s law (RMSE) and this property alone resulted in an r2 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.