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Cited by 498

The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.

Solute molecular dynamics in a mesoscale solvent

Malevanets, Anatoly, Kapral, Raymond·2000·The Journal of Chemical Physics

Abstract

A hybrid molecular dynamics (MD) algorithm which combines a full MD description of solute–solute and solute–solvent interactions with a mesoscale treatment of solvent-solvent interactions is developed. The solvent dynamics is modeled on a mesoscale level by coarse graining the system into cells and updating the velocities of the solvent molecules by multiparticle collisions within each cell. The solvent dynamics is such that the correct hydrodynamic equations are obtained in the macroscopic limit and a Boltzmann distribution of velocities is established in equilibrium. Discrete-time versions of the hydrodynamic equations and Green–Kubo autocorrelation functions are derived. Between the discrete-time solvent–solvent collisions the system evolves by the classical equations of motion. The hybrid MD scheme is illustrated by an application to the Brownian motion of a nanocolloidal particle in the mesoscale solvent and concentrated nanocolloidal suspensions.

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Metadata

Authors
Malevanets, A., & Kapral, R.
Venue
The Journal of Chemical Physics
Published
2000-04-22
Volume
112
Issue
16
Pages
7260-7269
ISSN
  • 0021-9606 (ISSN-L)
  • 1089-7690
OpenAlex
W2020858488
Cited by
498
References
13
FWCI
5.10
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Solute molecular dynamics in a mesoscale solvent. https://app.cochat.ai/papers/10.1063/1.481289
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Malevanets, A., & Kapral, R. (2000). Solute molecular dynamics in a mesoscale solvent. The Journal of Chemical Physics. https://doi.org/10.1063/1.481289

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.