Insight into the Density-Dependence of Pair Potentials for Predictive Coarse-Grained Models
收藏DataCite Commons2024-02-15 更新2024-07-13 收录
下载链接:
https://www.datacommons.psu.edu/commonswizard/MetadataDisplay.aspx?Dataset=6404
下载链接
链接失效反馈官方服务:
资源简介:
We investigate the temperature- and density-dependence of effective pair potentials for 1-site coarse-grained (CG) models of two industrial solvents, 1,4-dioxane and tetrahydrofuran. We observe that the calculated pair potentials are much more sensitive to density than to temperature. The generalized-Yvon-Born−Green framework reveals that this striking density-dependence reflects corresponding variations in the many-body correlations that determine the environment-mediated indirect contribution to the pair mean force. Moreover, we demonstrate, perhaps surprisingly, that this density-dependence is not important for accurately modeling the intermolecular structure. Accordingly, we adopt a density-independent interaction potential and transfer the density-dependence of the calculated pair potentials into a configuration-independent volume potential. Furthermore, we develop a single global potential that accurately models the intermolecular structure and pressure−volume equation of state across a very wide range of liquid state points. Consequently, this work provides fundamental insight into the density-dependence of effective pair potentials and also provides a significant step toward developing predictive CG models for efficiently modeling industrial solvents.
提供机构:
Penn State Data Commons
创建时间:
2024-02-15



