ParAMS: Parameter Optimization for Atomistic and Molecular Simulations

TL;DR

ParAMS is a Python package that simplifies parameter optimization in computational chemistry, making workflows more accessible, transparent, and reproducible through modular design and versatile protocols.

Contribution

It introduces a flexible, modular Python tool for efficient parameter optimization in atomistic simulations, enhancing reproducibility and ease of use.

Findings

Successfully optimized DFTB repulsive potential for ZnO

Optimized ReaxFF force field for organic disulfides

Demonstrated versatility across different PES models

Abstract

This work introduces ParAMS -- a versatile Python package that aims to make parameterization workflows in computational chemistry and physics more accessible, transparent and reproducible. We demonstrate how ParAMS facilitates the parameter optimization for potential energy surface (PES) models, which can otherwise be a tedious specialist task. Because of the package's modular structure, various functionality can be easily combined to implement a diversity of parameter optimization protocols. For example, the choice of PES model and the parameter optimization algorithm can be selected independently. An illustration of ParAMS' strengths is provided in two case studies: i) a density functional-based tight binding (DFTB) repulsive potential for the inorganic ionic crystal ZnO, and ii) a ReaxFF force field for the simulation of organic disulfides.