Prediction of self-diffusion coefficients of chemically diverse pure liquids by all-atom molecular dynamics simulations
© 2022 The Authors. Journal of Computational Chemistry published by Wiley Periodicals LLC.
Veröffentlicht in: | Journal of computational chemistry. - 1984. - 43(2022), 28 vom: 30. Okt., Seite 1892-1900 |
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Weitere Verfasser: | , , |
Format: | Online-Aufsatz |
Sprache: | English |
Veröffentlicht: |
2022
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Zugriff auf das übergeordnete Werk: | Journal of computational chemistry |
Schlagworte: | Journal Article liquid state mean square displacement molecular dynamics simulation self-diffusion coefficient water model Pharmaceutical Preparations |
Zusammenfassung: | © 2022 The Authors. Journal of Computational Chemistry published by Wiley Periodicals LLC. Molecular self-diffusion coefficients underlie various kinetic properties of the liquids involved in chemistry, physics, and pharmaceutics. In this study, 547 self-diffusion coefficients are calculated based on all-atom molecular dynamics (MD) simulations of 152 diverse pure liquids at various temperatures employing the OPLS4 force field. The calculated coefficients are compared with experimental data (424 extracted from the literature and 123 newly measured by pulsed-field gradient nuclear magnetic resonance). The calculations well agree with the experimental values. The determination coefficient and root mean square error between the observed and calculated logarithmic self-diffusion coefficients of the 547 entries are 0.931 and 0.213, respectively, demonstrating that the MD calculation can be an excellent industrial tool for predicting, for example, molecular transportation in liquids such as the diffusion of active ingredients in biological and pharmaceutical liquids. The self-diffusion coefficients collected in this study are compiled into a database for broad researches including artificial intelligence calculations |
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Beschreibung: | Date Completed 23.09.2022 Date Revised 10.09.2024 published: Print-Electronic Citation Status MEDLINE |
ISSN: | 1096-987X |
DOI: | 10.1002/jcc.26975 |