PyOrbb —Automated Analyses of Orbital‐Interaction Mechanisms
ABSTRACT We present PyOrbb, an open‐source, user‐friendly Python‐based program that automates the analysis and visualization of orbital interaction mechanisms between molecular fragments or reactants, based on quantum‐chemical computations with the Amsterdam Density Functional (ADF) program. PyOrbb extracts the essential mixing patterns, presents them in an interactively adjustable orbital interaction diagram, and summarizes all relevant quantitative data in a convenient Excel spreadsheet for further analysis. The tool enables efficient interpretation of chemical bonding across a broad range of systems, including examples from organic, inorganic, and supramolecular chemistry. The application runs on macOS and Windows operating systems. PyOrbb is shown to accurately and rapidly visualize relevant bonding mechanisms from the often‐overwhelming output of density functional computations.
Authors
- Xiaobo Sun (ORCID: https://orcid.org/0000-0003-2483-8476)
- F. Matthias Bickelhaupt (ORCID: https://orcid.org/0000-0003-4655-7747)
- Célia Fonseca Guerra (ORCID: https://orcid.org/0000-0002-2973-5321)
- Jordi Poater (ORCID: https://orcid.org/0000-0002-0814-5074)
- Steven E. Beutick (ORCID: https://orcid.org/0000-0001-6672-881X)
- Laurens De Groot
- Trevor A. Hamlin (ORCID: https://orcid.org/0000-0002-5128-1004)
- Yuman Hordijk (ORCID: https://orcid.org/0000-0002-0777-4274)
- Tori Gijzen (ORCID: https://orcid.org/0009-0006-9879-9659)
Institutions
- Institució Catalana de Recerca i Estudis Avançats (ES)
- Radboud University Nijmegen (NL)
- University of Johannesburg (ZA)
- Universitat de Barcelona (ES)
- Vrije Universiteit Amsterdam (NL)
Publication Details
- Journal
- Journal of Computational Chemistry
- Published
- 2026-09-30
- DOI
- https://doi.org/10.1002/jcc.70512
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00