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Assessment and Optimization of Configurational-Bias Monte Carlo Particle Swap Strategies for Simulations of Water in the Gibbs Ensemble
Peng Bai,
J. Ilja Siepmann
Chemical Engineering and Materials Science
Chemistry (Twin Cities)
Research output
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Contribution to journal
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Article
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peer-review
25
Scopus citations
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Dive into the research topics of 'Assessment and Optimization of Configurational-Bias Monte Carlo Particle Swap Strategies for Simulations of Water in the Gibbs Ensemble'. Together they form a unique fingerprint.
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Keyphrases
Gibbs Ensemble
100%
Configurational Bias Monte Carlo
100%
Acceptance Probability
60%
Gibbs Ensemble Monte Carlo
40%
Monte Carlo Method
20%
Monte Carlo Algorithm
20%
TIP4P
20%
Multiple Parameters
20%
Rate-limiting Step
20%
High Directional
20%
Water Model
20%
Fluid Phase Equilibria
20%
Optimal Efficiency
20%
Reduction Temperature
20%
Swap Move
20%
Directional Interaction
20%
Chemistry
Gibbs Free Energy
100%
Configurational Bias Monte Carlo
100%
Statistical Ensemble
100%
Monte Carlo Method
40%
Fluid Phase Equilibrium
20%
Engineering
Gibbs Free Energy
100%
Directional
33%
Fluid Phase
33%
Reduced Temperature
33%
Limiting Step
33%
Chemical Engineering
Gibbs Free Energy
100%