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Cited by 4,436

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A reactive potential for hydrocarbons with intermolecular interactions

Stuart, Steven J., Tutein, Alan B., Harrison, Judith A.·2000·The Journal of Chemical Physics

Abstract

A potential function is presented that can be used to model both chemical reactions and intermolecular interactions in condensed-phase hydrocarbon systems such as liquids, graphite, and polymers. This potential is derived from a well-known dissociable hydrocarbon force field, the reactive empirical bond-order potential. The extensions include an adaptive treatment of the nonbonded and dihedral-angle interactions, which still allows for covalent bonding interactions. Torsional potentials are introduced via a novel interaction potential that does not require a fixed hybridization state. The resulting model is intended as a first step towards a transferable, empirical potential capable of simulating chemical reactions in a variety of environments. The current implementation has been validated against structural and energetic properties of both gaseous and liquid hydrocarbons, and is expected to prove useful in simulations of hydrocarbon liquids, thin films, and other saturated hydrocarbon systems.

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Metadata

Authors
Stuart, S. J., Tutein, A. B., & Harrison, J. A.
Venue
The Journal of Chemical Physics
Published
2000-04-08
Volume
112
Issue
14
Pages
6472-6486
ISSN
  • 0021-9606 (ISSN-L)
  • 1089-7690
OpenAlex
W2019481672
Cited by
4,436
References
1
FWCI
9.17
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A reactive potential for hydrocarbons with intermolecular interactions. https://app.cochat.ai/papers/10.1063/1.481208
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Stuart, S. J., Tutein, A. B., & Harrison, J. A. (2000). A reactive potential for hydrocarbons with intermolecular interactions. The Journal of Chemical Physics. https://doi.org/10.1063/1.481208

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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.