Soft-sphere continuum solvation models for nonaqueous solvents.

Area of Science:

• Computational chemistry
• Physical chemistry
• Chemical physics

Background:

• Solvation effects are crucial for chemical systems in solution, influencing solubility, reactivity, and stability.
• Continuum solvation models, like self-consistent continuum solvation (SCCS) and soft-sphere continuum solvation (SSCS), efficiently capture these interactions in quantum chemistry and condensed matter simulations.
• These models rely on parameters derived from solvent properties or reference data.

Purpose of the Study:

• To systematically parameterize the SSCS model for a broad range of nonaqueous solvents.
• To validate the SSCS model's performance using experimental solvation-free energies and partition coefficients.
• To assess the transferability and predictive power of continuum solvation models for diverse solvent environments.

Main Methods:

• Systematic parameterization of the SSCS model for over 100 nonaqueous solvents.
• Validation using experimental solvation-free energies and partition coefficients from comprehensive databases.
• Calculation of average root mean square error (RMSE) to assess model accuracy.

Main Results:

• The SSCS model was successfully parameterized for over 100 nonaqueous solvents.
• The average RMSE across all solvents was 0.85 kcal/mol, falling below the threshold for chemical accuracy (1 kcal/mol).
• A single-parameter model demonstrated accurate reproduction of experimental solvation energies, similar to the SCCS model.

Conclusions:

• The parameterized SSCS model shows high accuracy and transferability across diverse nonaqueous solvent environments.
• The findings support the potential for a unified approach to predict solvation properties computationally.
• This work enhances the capability of computational studies for various chemical systems in solution.