Issue 11, 2022

Quantum chemical calculation of the vapor pressure of volatile and semi volatile organic compounds

Abstract

The vapor pressure is a specific and temperature-dependent parameter that describes the volatility of a substance and thus its driving force for evaporation or sublimation into the gas phase. Depending on the magnitude of the vapor pressure, there are different methods for experimental determination. However, these are usually associated with a corresponding amount of effort and become less accurate as the vapor pressure decreases. For purposes of vapor pressure prediction, algorithms were developed that are usually based on quantitative structure–activity relationships (QSAR). The quantum mechanical (QM) approach followed here applies an alternative, much less empirical strategy, where the change in Gibbs free energy for the transition from the condensed to the gas phase is obtained from conformer ensembles computed for each phase separately. The results of this automatic, so-called CRENSO workflow are compared with experimentally determined vapor pressures for a large set of environmentally relevant compounds. In addition, comparisons are made with the single structure-based COSMO-RS QM approach, linear-free-energy relationships (LFER) as well as results from the SPARC program. We show that our CRENSO workflow is superior to conventional prediction models and provides reliable vapor pressures for liquids and sub-cooled liquids over a wide pressure range.

Graphical abstract: Quantum chemical calculation of the vapor pressure of volatile and semi volatile organic compounds

Supplementary files

Article information

Article type
Paper
Submitted
26 Чер 2022
Accepted
01 Жов 2022
First published
03 Жов 2022
This article is Open Access
Creative Commons BY license

Environ. Sci.: Processes Impacts, 2022,24, 2153-2166

Quantum chemical calculation of the vapor pressure of volatile and semi volatile organic compounds

M. Stahn, S. Grimme, T. Salthammer, U. Hohm and W. Palm, Environ. Sci.: Processes Impacts, 2022, 24, 2153 DOI: 10.1039/D2EM00271J

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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