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Weighted-density functionals for cavity formation and dispersion energies in continuum solvation models
Ravishankar Sundararaman1, Deniz Gunceler1, T A Arias1
1Department of Physics, Cornell University, Ithaca, New York 14853, USA.
This study introduces a new, minimally-empirical solvation model for predicting chemical reactions in solution. The model offers accurate solvation energy predictions with reduced parametrization, simplifying calculations for diverse chemical systems.
Area of Science:
- Physical Chemistry
- Computational Chemistry
- Theoretical Chemistry
Background:
- Continuum solvation models are crucial for first principles calculations of chemical reactions in solution.
- Current models necessitate extensive parametrization for each solvent and solute system, limiting their applicability.
- Empirical terms in existing models hinder accuracy and broad usability.
Purpose of the Study:
- To develop a minimally-empirical solvation model by replacing empirical terms with physically derived components.
- To enhance the efficiency and accuracy of predicting solvation energies for chemical reactions.
- To reduce the reliance on extensive experimental data for model parametrization.
Main Methods:
- Derived solvent radii from ab initio calculations of nonlocal dielectric response.
- Developed a parameter-free weighted-density approximation for cavity formation free energy.
- Utilized a pair-potential approximation for dispersion energy calculations.
- Introduced a single solvent-independent parameter (electron density threshold, nc) and a single solvent-dependent parameter (dispersion scale factor, s6).
Main Results:
- The model accurately reproduced solvation energies for organic molecules in water, chloroform, and carbon tetrachloride with low RMS errors (1.1, 0.6, and 0.5 kcal/mol, respectively).
- Fitting the solvent-dependent parameter (s6) to a single non-polar molecule's solvation energy minimally impacted accuracy.
- Demonstrated that parametrization for new solvents requires minimal effort and no extensive experimental databases.
Conclusions:
- The developed minimally-empirical solvation model offers a significant improvement over existing methods.
- The model's reduced parametrization requirements make it highly adaptable to various solvents and solute systems.
- This approach facilitates more efficient and accurate first principles calculations of chemical processes in solution.
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