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ParAMS: Parameter Optimization for Atomistic and Molecular Simulations.

Leonid Komissarov1,2, Robert Rüger2, Matti Hellström2

  • 1Center for Molecular Modeling (CMM), Ghent University, Technologiepark-Zwijnaarde 46, B-9052 Ghent, Belgium.

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Summary
This summary is machine-generated.

ParAMS is a Python package simplifying computational chemistry parameter optimization for potential energy surface (PES) models. It enhances accessibility, transparency, and reproducibility in workflows.

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Area of Science:

  • Computational Chemistry and Physics
  • Materials Science
  • Cheminformatics

Background:

  • Parametrization of potential energy surface (PES) models is crucial for accurate simulations in chemistry and physics.
  • Current parametrization workflows can be complex, time-consuming, and require specialized expertise.
  • Lack of accessible and reproducible tools hinders broader adoption and advancement in the field.

Purpose of the Study:

  • To introduce ParAMS, a versatile Python package designed to streamline and democratize parametrization workflows.
  • To enhance the accessibility, transparency, and reproducibility of parameter optimization for PES models.
  • To provide a modular framework for combining different PES models and optimization algorithms.

Main Methods:

  • Development of a modular Python package, ParAMS, for automated parameter optimization.
  • Implementation of flexible protocols allowing independent selection of PES models and optimization algorithms.
  • Case studies involving density functional-based tight binding (DFTB) and ReaxFF force fields.

Main Results:

  • ParAMS successfully facilitates parameter optimization for diverse PES models.
  • Demonstrated efficiency in optimizing a DFTB repulsive potential for ZnO.
  • Showcased effectiveness in refining a ReaxFF force field for organic disulfide simulations.

Conclusions:

  • ParAMS significantly improves the accessibility and reproducibility of computational chemistry parametrization.
  • The package's modular design supports a wide range of optimization protocols.
  • ParAMS is a valuable tool for researchers seeking to optimize PES models efficiently and reliably.