Automated Bonding Analysis with Crystal Orbital Hamilton Populations

Area of Science:

• Materials Science
• Computational Chemistry
• Solid-State Physics

Background:

• Understanding crystalline structures relies on analyzing chemical bonding.
• Crystal Orbital Hamilton Population (COHP) quantifies interatomic bond strength.
• Automated analysis of COHP is crucial for efficient materials discovery.

Purpose of the Study:

• To present new tools for automating Crystal Orbital Hamilton Population (COHP) calculations and analysis.
• To enable quantitative assessment of interatomic bond strengths in diverse crystalline materials.
• To facilitate the integration of bonding information into machine learning models for materials science.

Main Methods:

• Utilized VASP and LOBSTER for electronic structure calculations.
• Employed atomate and pymatgen Python packages for workflow automation.
• Developed analysis tools generating plots, textual descriptions, and machine-readable data.

Main Results:

• Successfully automated COHP calculation and analysis for various compounds (NaCl, GaN, oxynitrides, Yb14Mn1Sb11).
• Demonstrated correlations between bond strengths and stability in oxynitrides.
• Illustrated the impact of Mn-Sb bonds on magnetism in Yb14Mn1Sb11.

Conclusions:

• The developed tools enable high-throughput bonding analysis.
• Automated COHP analysis facilitates the use of bonding information for materials design and machine learning.
• This work enhances the understanding of structure-property relationships in crystalline materials.