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Cited by 364

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Diffusion in Lennard-Jones fluids using dual control volume grand canonical molecular dynamics simulation (DCV-GCMD)

Heffelfinger, Grant S., Swol, Frank van·1994·The Journal of Chemical Physics

Abstract

A new approach to calculating diffusivities, both transport as well as equilibrium, is presented. The dual control volume grand canonical molecular dynamics (or DCV-GCMD) method employs two local control volumes for chemical potential control via particle creation/destruction as in grand canonical Monte Carlo (GCMC) simulations. The control volumes are inserted in a standard NVT molecular dynamics simulation yielding a simulation with stochastic chemical potential control that may be thought of as a hybrid GCMC-MD approach. The geometrical control of the chemical potential enables a steady state chemical potential gradient to be established in the system. By measuring the density profile and flux, Fick’s law is used to determine the diffusivity. An example calculation is presented for a simple Lennard-Jones system.

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Metadata

Authors
Heffelfinger, G. S., & Swol, F. V.
Venue
The Journal of Chemical Physics
Published
1994-05-15
Volume
100
Issue
10
Pages
7548-7552
ISSN
  • 0021-9606 (ISSN-L)
  • 1089-7690
OpenAlex
W2021929941
Cited by
364
References
7
FWCI
4.20
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Diffusion in Lennard-Jones fluids using dual control volume grand canonical molecular dynamics simulation (DCV-GCMD). https://app.cochat.ai/papers/10.1063/1.466849
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Heffelfinger, G. S., & Swol, F. V. (1994). Diffusion in Lennard-Jones fluids using dual control volume grand canonical molecular dynamics simulation (DCV-GCMD). The Journal of Chemical Physics. https://doi.org/10.1063/1.466849

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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.