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Updated: Mar 30, 2026
10:52
Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
Published on: April 12, 2019
13.5K
Multiscale Simulation of Liquid Water Using a Four-to-One Mapping for Coarse-Graining
Anu Nagarajan1, Christoph Junghans2, Silvina Matysiak1
1Fischell Department of Bioengineering, University of Maryland , College Park, Maryland 20742, United States.
Journal of Chemical Theory and Computation
|November 20, 2015
Summary
This study introduces a multiresolution simulation method, mapping four water molecules to one coarse-grained bead. This approach preserves water
Area of Science:
- Computational chemistry
- Molecular dynamics simulations
- Soft matter physics
Background:
- Accurate modeling of solvent environments is crucial for understanding chemical and physical processes.
- Bridging atomistic and coarse-grained simulations offers computational efficiency but requires careful validation.
Purpose of the Study:
- To develop and validate a multiresolution simulation scheme for solvent environments.
- To enable seamless transitions between atomistic and coarse-grained resolutions.
Main Methods:
- Implementing a multiresolution simulation scheme where four atomistic water molecules are represented by a single coarse-grained bead.
- Utilizing soft restraining potentials to facilitate resolution exchange.
- Performing all-atom simulations to assess the impact of restraining potentials on liquid water properties.
- Analyzing solvation shell structures around various solutes (hydrophobic, hydrophilic, ionic).
Main Results:
- Soft restraining potentials effectively bundle four water molecules without disrupting hydrogen bonding in liquid water.
- The structural integrity of the first solvation shell around diverse solutes is maintained.
- The proposed scheme allows for smooth transitions and free exchange between coarse-grained and all-atom resolutions.
Conclusions:
- The developed multiresolution simulation scheme accurately represents solvent behavior.
- This method provides a robust framework for adaptive resolution simulations, enhancing computational efficiency while preserving accuracy.
- The approach is suitable for studying solvation effects in complex systems.
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