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Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

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AtomDB: A Python Library and Database for Atomic and Promolecular Properties.

Gabriela Sánchez Díaz¹, Michelle Richer^1,2, Marco Martínez González¹

¹Department of Chemistry & Chemical Biology, McMaster University, 1280 Main St. West, Hamilton, Hamilton, Ontario L8S 4M1, Canada.

The Journal of Physical Chemistry. A

|February 28, 2025

Summary

This summary is machine-generated.

AtomDB is a new Python library for atomic and promolecular properties. It provides a computational toolset with an extended periodic table database for diverse atomic species.

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Area of Science:

Computational Chemistry
Atomic Physics
Software Development

Background:

Accessing and manipulating atomic and promolecular data is crucial for scientific research.
Existing tools may lack comprehensive data or ease of use for diverse atomic species.

Purpose of the Study:

To introduce AtomDB, a free and open-source Python library.
To provide a robust computational toolset for atomic and promolecular properties.
To facilitate research involving atomic species with various charges and multiplicities.

Main Methods:

Development of a Python library utilizing an extended periodic table database.
Implementation of facilities for computing local and scalar promolecular properties.
Adherence to modern software development best practices, including documentation and testing.

Main Results:

AtomDB offers access to and manipulation of neutral and charged atomic species data.
The library computes local and scalar promolecular properties, considering extensivity and intensity.
It is designed for ease of use, extensibility, and maintainability.

Conclusions:

AtomDB provides a valuable, user-friendly computational resource for atomic and promolecular studies.
The library's design promotes reliability and ease of integration into research workflows.
This release note marks the official availability of the AtomDB library.