Automated Bonding Analysis with Crystal Orbital Hamilton Populations

Area of Science:

• Materials Science
• Computational Chemistry
• Solid-State Chemistry

Background:

• Accurate bonding analysis is crucial for understanding material properties.
• Traditional methods for analyzing crystal orbital Hamilton populations (COHP) can be time-consuming and complex.
• Automating these analyses can accelerate materials discovery and characterization.

Purpose of the Study:

• To present an automated workflow for bonding analysis in crystal structures.
• To integrate Python tools with the LOBSTER program for efficient COHP analysis.
• To provide automatic assessments of bonding situations, coordination environments, and charges.

Main Methods:

• Development of a Python-based workflow for automated crystal structure analysis.
• Utilizing the LOBSTER program for calculating Crystal Orbital Hamilton Populations (COHP).
• Implementation of automatic plotting and text output generation for bonding analysis results.

Main Results:

• Successful implementation of an automated workflow for COHP analysis.
• Automatic generation of bonding assessments, including plots and textual summaries.
• Accurate evaluation of coordination environments and atomic charges within crystal structures.

Conclusions:

• The developed automated workflow significantly simplifies and accelerates bonding analysis.
• This approach enhances the interpretability of crystal structure bonding through COHP.
• The tool facilitates faster materials research by automating complex computational tasks.