Journal
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
Volume 8, Issue 5, Pages 1828-1840Publisher
AMER CHEMICAL SOC
DOI: 10.1021/ct200842c
Keywords
-
Funding
- NSF [0328162, 0852657, 0915718]
- Direct For Computer & Info Scie & Enginr
- Division of Computing and Communication Foundations [0915718] Funding Source: National Science Foundation
- Directorate For Engineering
- Div Of Civil, Mechanical, & Manufact Inn [0328162] Funding Source: National Science Foundation
- Div Of Chem, Bioeng, Env, & Transp Sys
- Directorate For Engineering [0852657] Funding Source: National Science Foundation
Ask authors/readers for more resources
We propose a coarse-grained potential model to predict the concentration and potential profiles of confined water. In this model, we represent one water molecule with one coarse-grained bead, such that the interactions between the coarse-grained beads are given by isotropic two-body potentials. Due to the inherent inhomogeneity of the confined water microstructure, we find that a single spatially uniform coarse-grained water water potential may not be sufficient to accurately predict the structure of water near the surface. To accurately capture surface effects on the water structure, we add a coarse-grained correction potential between wall atoms and water coarse-grained beads. We use an empirical potential-based quasi-continuum theory (EQT) (J. Chem. Phys. 2007, 127, 174701) to derive and evaluate optimal parameters for the coarse-grained potential model. We evaluate the ability of our model to predict the structure of confined water for two different types of surfaces a silicon slit channel and a graphite slit channel and show that the results predicted by EQT are in good agreement with all-atom molecular dynamics results across multiple length scales. We also demonstrate that the coarse-grained potential parameters optimized using EQT work well even in the coarse-grained molecular dynamics simulations.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available