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The Journal of Chemical Physics
Article . 2017 . Peer-reviewed
License: CC BY
Data sources: Crossref
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The Journal of Chemical Physics
Article
License: CC BY
Data sources: UnpayWall
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Apollo
Article . 2017
License: CC BY
Data sources: Datacite
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Computational methodology for solubility prediction: Application to the sparingly soluble solutes

Authors: Lunna Li; Tim Totton; Daan Frenkel;

Computational methodology for solubility prediction: Application to the sparingly soluble solutes

Abstract

The solubility of a crystalline substance in the solution can be estimated from its absolute solid free energy and excess solvation free energy. Here, we present a numerical method, which enables convenient solubility estimation of general molecular crystals at arbitrary thermodynamic conditions where solid and solution can coexist. The methodology is based on standard alchemical free energy methods, such as thermodynamic integration and free energy perturbation, and consists of two parts: (1) systematic extension of the Einstein crystal method to calculate the absolute solid free energies of molecular crystals at arbitrary temperatures and pressures and (2) a flexible cavity method that can yield accurate estimates of the excess solvation free energies. As an illustration, via classical Molecular Dynamic simulations, we show that our approach can predict the solubility of OPLS-AA-based (Optimized Potentials for Liquid Simulations All Atomic) naphthalene in SPC (Simple Point Charge) water in good agreement with experimental data at various temperatures and pressures. Because the procedure is simple and general and only makes use of readily available open-source software, the methodology should provide a powerful tool for universal solubility prediction.

Country
United Kingdom
Related Organizations
Keywords

3407 Theoretical and Computational Chemistry, Networking and Information Technology R&D (NITRD), 34 Chemical Sciences, Networking and Information Technology R&D (NITRD), Bioengineering

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
102
Top 1%
Top 10%
Top 1%
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