Litcius/Paper detail

Automated Bonding Analysis with Crystal Orbital Hamilton Populations

Janine George, Guido Petretto, Aakash Ashok Naik, Marco Esters, Adam Jackson, Ryky Nelson, Richard Dronskowski, Gian‐Marco Rignanese, Geoffroy Hautier

2022ChemPlusChem58 citationsDOIOpen Access PDF

Abstract

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 BaTaO 2 N, CaTaO 2 N, and SrTaO 2 N, and the thermoelectric material Yb 14 Mn 1 Sb 11 . We show correlations between bond strengths and stabilities in the oxynitrides and the influence of the Mn−Sb bonds on the magnetism in Yb 14 Mn 1 Sb 11 . Our contribution enables high‐throughput bonding analysis and will facilitate the use of bonding information for machine learning studies.

Topics & Concepts

Python (programming language)Chemical bondContext (archaeology)Crystal structure predictionPopulationComputer scienceMaterials scienceCrystal structureCrystallographyNanotechnologyComputational scienceChemistryProgramming languageBiologySociologyPaleontologyOrganic chemistryDemographyMachine Learning in Materials ScienceInorganic Chemistry and MaterialsX-ray Diffraction in Crystallography