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Published on: May 2, 2016
Testing recent charge-on-spring type polarizable water models. I. Melting temperature and ice properties
Péter T Kiss1, Péter Bertsyk, András Baranyai
1Institute of Chemistry, Eötvös University, 1518 Budapest 112, P.O. Box 32, Hungary.
Eight molecular water models using the charge-on-spring (COS) method were tested for freezing points. The BKd3 model showed the best freezing point estimation, indicating that accurately describing the temperature-density curve improves accuracy.
Area of Science:
- Computational chemistry
- Materials science
- Physical chemistry
Background:
- Accurate molecular models of water are crucial for understanding its properties.
- Polarization effects are significant in water models.
- Existing models often struggle to accurately predict phase transition properties like freezing points.
Purpose of the Study:
- To evaluate the freezing point accuracy of eight molecular water models employing the charge-on-spring (COS) method.
- To compare the performance of different polarization and repulsion schemes in these models.
- To identify which model features best correlate with accurate freezing point prediction.
Main Methods:
- Utilized thermodynamic integration (TI) and the Gibbs-Helmholtz equation to calculate free energy differences between liquid water and hexagonal ice (Ih).
- Employed TIP4P and SPC/E models as reference systems for TI calculations.
- Calculated freezing points for COS/G2, COS/G3, COS/B2, SWM4-DP, SWM4-NDP, BKd1, BKd2, and BKd3 models.
Main Results:
- All tested molecular models significantly underestimated the experimental freezing point of hexagonal ice (Ih).
- Calculated freezing points ranged from below 100 K (COS/B2) to 233 K (BKd3).
- The BKd3 model, which includes a variable size to approximate the temperature-density curve, yielded the best freezing point prediction among the studied models.
Conclusions:
- Current molecular water models, even those using the COS method, require improvement for accurate freezing point prediction.
- Accurately representing the temperature-density relationship of water is a key factor in improving freezing point predictions.
- Further development of water models is needed to capture the complex behavior of water and ice phases.
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