# CHEMSMART: Chemistry Simulation and Modeling Automation Toolkit for High-Efficiency Computational Chemistry Workflows

**Authors:** Xinglong Zhang, Huiwen Tan, Jingyi Liu, Zihan Li, Lewen Wang, Benjamin W. J. Chen

arXiv: 2508.20042 · 2025-08-28

## TL;DR

CHEMSMART is an open-source Python toolkit that automates and streamlines quantum chemistry workflows, improving efficiency and reproducibility in computational chemistry research.

## Contribution

It introduces a modular, integrated framework for automating various stages of quantum chemistry calculations, enhancing interoperability and user-friendliness.

## Key findings

- Automates job preparation, execution, and analysis in quantum chemistry workflows.
- Supports multiple computational tasks like geometry optimization and transition state searches.
- Enhances reproducibility and efficiency in computational chemistry research.

## Abstract

CHEMSMART (Chemistry Simulation and Modeling Automation Toolkit) is an open-source, Python-based framework designed to streamline quantum chemistry workflows for homogeneous catalysis and molecular modeling. By integrating job preparation, submission, execution, results analysis, and visualization, CHEMSMART addresses the inefficiencies of manual workflow management in computational chemistry by ensuring seamless interoperability with quantum chemistry packages and cheminformatics platforms. Its modular architecture supports automated job submission and execution tasks for geometry optimization, transition state searches, thermochemical analysis, and non-covalent interaction plotting, while auxiliary scripts facilitate file conversion, data organization, and electronic structure analysis. Future developments aim to expand compatibility with additional software, incorporate QM/MM and classical MD, and align with FAIR data principles for enhanced reproducibility and data reuse. Available on GitHub, CHEMSMART empowers researchers with a robust, user-friendly platform for efficient and reproducible computational chemistry.

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Source: https://tomesphere.com/paper/2508.20042