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Christoph Hille1, Stefan Ringe2, Martin Deimel1

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Summary

This study presents optimized parameters for the Self-Consistent Continuum Solvation (SCCS) model for 67 non-aqueous solvents, improving solvation effect simulations for chemical reactions and battery material design. The new parameters enhance accuracy and allow prediction for new solvents using dielectric permittivity.

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Area of Science:

  • Computational chemistry
  • Physical chemistry
  • Materials science

Background:

  • Continuum modeling techniques are crucial for simulating solvation effects in chemical reactions, offering efficiency over explicit solvent sampling.
  • Implicit solvation models require accurate parameterization, with prior focus on water models, but non-aqueous solvents are increasingly important, especially for battery materials.
  • The Self-Consistent Continuum Solvation (SCCS) model is an effective implicit solvation technique.

Purpose of the Study:

  • To develop a systematic parametrization protocol for the SCCS model for 67 non-aqueous solvents.
  • To create the Solv@TUM database of experimentally measured partition coefficients for model parametrization.
  • To assess the accuracy of the optimized SCCS model and introduce an improved variant (SCCS-P) for specific solute types.

Main Methods:

  • Systematic parametrization of the SCCS model using experimental partition coefficients from the Solv@TUM database (≈6000 data points).
  • Comparison of the optimized SCCS model's accuracy against established universal continuum solvation models (SMx).
  • Development of the SCCS-P model by modifying non-electrostatic terms for enhanced accuracy, particularly for aromatic solutes.
  • Investigation of predicting SCCS parameters for new solvents based on dielectric bulk permittivity.

Main Results:

  • Optimized SCCS parameters for 67 non-aqueous solvents were successfully obtained.
  • The optimized SCCS model demonstrates accuracy comparable to SMx methods but with a single fit parameter, reducing statistical noise.
  • The SCCS-P model shows improved accuracy, especially for aromatic solutes.
  • SCCS parameters can be reasonably predicted for untested solvents using their dielectric bulk permittivity.

Conclusions:

  • The developed SCCS parametrization protocol and the Solv@TUM database provide a valuable resource for accurate solvation effect simulations in non-aqueous media.
  • The optimized SCCS and SCCS-P models offer efficient and accurate alternatives for computational studies, particularly in areas like battery material design.
  • The ability to predict SCCS parameters based on dielectric permittivity simplifies the application of these models to a wider range of solvents.