Automated Bonding Analysis with Crystal Orbital Hamilton Populations
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Updated: Sep 6, 2025

Fully Autonomous Characterization and Data Collection from Crystals of Biological Macromolecules
Published on: March 22, 2019
Janine George1,2,3, Guido Petretto3, Aakash Naik1,2
1Federal Institute for Materials Research and Testing, Department Materials Chemistry, Unter den Eichen 87, 12205, Berlin, Germany.
Abstract:
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 for quantifying 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 a machine-readable format. To illustrate those capabilities, we have selected simple test compounds (NaCl, GaN), the oxynitrides BaTaO2 N, CaTaO2 N, and SrTaO2 N, and the thermoelectric material Yb14 Mn1 Sb11 . We show correlations between bond strengths and stabilities in the oxynitrides and the influence of the Mn-Sb bonds on the magnetism in Yb14 Mn1 Sb11 . Our contribution enables high-throughput bonding analysis and will facilitate the use of bonding information for machine learning studies.
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