Automated Bonding Analysis with Crystal Orbital Hamilton Populations

21 March 2022, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


Understanding crystalline structures based on their chemical bonding is growing in importance. In this context, chemical bonding can be studied with the Crystal Orbital Hamilton Population (COHP), allowing to quantify interatomic bond strength. Here we present a new set of tools to automate the calculation of COHP and analyze the results. We use the program packages VASP and LOBSTER and the Python packages atomate and pymatgen. The analysis produced by our tools includes plots, a textual description, and key data in machine-readable format. To illustrate those capabilities, we have selected simple test compounds (NaCl, GaN), the oxynitrides BaTaO2N, CaTaO2N, and SrTaO2N, and the thermoelectric material Yb14Mn1Sb11. We show correlations between bond strengths and stabilities in the oxynitrides, as well as the influence of the Mn-Sb bonds on the magnetism in Yb14Mn1Sb11. Our contribution enables high-throughput bonding analysis and will facilitate the use of bonding information for machine learning studies.


bonding analysis
chemical understanding


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