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COMPASS: An ab Initio Force-Field Optimized for Condensed-Phase ApplicationsOverview with Details on Alkane and Benzene Compounds
Abstract
A general all-atom force field for atomistic simulation of common organic molecules, inorganic small molecules, and polymers was developed using state-of-the-art ab initio and empirical parametrization techniques. The valence parameters and atomic partial charges were derived by fitting to ab initio data, and the van der Waals (vdW) parameters were derived by conducting MD simulations of molecular liquids and fitting the simulated cohesive energies and equilibrium densities to experimental data. The combined parametrization procedure significantly improves the quality of a general force field. Validation studies based on large number of isolated molecules, molecular liquids and molecular crystals, representing 28 molecular classes, show that the present force field enables accurate and simultaneous prediction of structural, conformational, vibrational, and thermophysical properties for a broad range of molecules in isolation and in condensed phases. Detailed results of the parametrization and validation for alkane and benzene compounds are presented.
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Computer Simulation of Liquids
Allen, M. P., & Tildesley, D. J. (2017) · doi:10.1093/oso/9780198803195.001.0001 · Cited by 20,945
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Metadata
- Authors
- Sun, H.
- Venue
- The Journal of Physical Chemistry B
- Publisher
- American Chemical Society (ACS)
- Published
- 1998-08-29
- Volume
- 102
- Issue
- 38
- Pages
- 7338-7364
- ISSN
- 1520-5207 (ISSN-L)
- 1520-6106
- OpenAlex
- W2091654157
- Cited by
- 6,001
- References
- 1
- FWCI
- 13.78
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.