4.7 Article

Ultra-Coarse-Grained Models Allow for an Accurate and Transferable Treatment of Interfacial Systems

期刊

JOURNAL OF CHEMICAL THEORY AND COMPUTATION
卷 14, 期 4, 页码 2180-2197

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.jctc.7b01173

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资金

  1. National Science Foundation (NSF Grant) [CHE-1465248]
  2. Kwanjeong Educational Foundation
  3. Direct For Mathematical & Physical Scien
  4. Division Of Chemistry [1465248] Funding Source: National Science Foundation

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Interfacial systems are fundamentally important in many processes. However, constructing coarse-grained (CG) models for such systems is a significant challenge due to their inhomogeneous nature. This problem is made worse due to the generally nontransferable nature of the interactions in CG models across different phases. In this paper, we address these challenges by systematically constructing ultra-coarse-grained (UCG) models for interfaces, in which the CG sites are allowed to have internal states. We find that a multiscale coarse-grained (MS-CG) representation of a single CG site model fails to identify the directionality of a molecule and is unable to reproduce the correct phase coexistence for aspherical molecules. In contrast with conventional MS-CG models, the UCG methodology allows chemical and environmental changes to be captured by modulating the interactions between internal states. In this work, we design the internal states to depend on local particle density to distinguish different phases in liquid/vapor or liquid/liquid interfaces. These UCG models are able to capture phase coexistence and recapitulate structures, notably at state points in which the MS-CG method yields poor results. Interestingly, effective pairwise forces and potentials from the UCG models are almost identical to those of the bulk liquids that correspond to each phase, indicating that the UCG approach can provide transferable interactions. This approach is expected to be applicable to other systems that exhibit phase coexistence and also to complex macromolecular systems by modulating interactions based on local density or other order parameters to unravel the complex nature underlying heterogeneous system boundaries.

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