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Explicit consideration of spatial hydrogen bonding direction for activity coefficient prediction based on implicit
1Department of Chemical Engineering, National Taiwan University, Taipei 10617, Taiwan. stlin@ntu.edu.tw.
A new directional hydrogen bond model improves predictions of chemical activity coefficients in mixtures. This approach enhances accuracy for associating fluids, crucial for understanding thermodynamic properties and mixture non-ideality.
Area of Science:
- Thermodynamics
- Physical Chemistry
- Computational Chemistry
Background:
- Activity coefficients are vital for understanding mixture non-ideality and thermodynamic properties.
- The COSMO-SAC model predicts activity coefficients but struggles with associating fluids.
- Current models neglect the spatial orientation crucial for hydrogen bond formation.
Purpose of the Study:
- To develop a more accurate model for predicting activity coefficients in associating fluids.
- To incorporate spatial orientational constraints into hydrogen bond descriptions.
- To improve the reliability of thermodynamic property predictions for complex mixtures.
Main Methods:
- Proposed a new directional hydrogen bond (DHB) approach within the COSMO-SAC framework.
- Utilized Valence Shell Electron Pair Repulsion (VSEPR) theory to define orientation-dependent interactions.
- Limited hydrogen bond interactions to specific spatial regions based on lone pair electron projections.
Main Results:
- The new COSMO-SAC(DHB) model shows significantly improved accuracy for predicting activity coefficients.
- The model demonstrates enhanced reliability for various properties, including vapor-liquid equilibria (VLE) and water-octanol partition coefficients (Kow).
- Fewer universal parameters are required compared to previous models.
Conclusions:
- The COSMO-SAC(DHB) model offers a more accurate and reliable method for predicting thermodynamic properties of associating fluids.
- Incorporating directional hydrogen bonding significantly advances the prediction capabilities for mixture non-ideality.
- This approach provides a more robust tool for chemical process design and analysis.
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