Hi everyone!

I'd like to share ORCA PED Analyzer, an open-source tool I developed to simplify the analysis and assignment of vibrational calculations performed with ORCA.

The program performs Potential Energy Distribution (PED) analysis of harmonic normal modes and generates automatic vibrational assignments based on calculated atomic motion and internal-coordinate energy decomposition, rather than empirical frequency windows.

🔬 Main features

• PED analysis and automatic vibrational-mode assignment
• Detection and reporting of mixed modes
• Optional VPT2/GVPT2 integration
• Analysis of fundamentals, overtones and combination bands
• Harmonic and anharmonic IR intensities, when available
• Generation of broadened IR spectra
• CSV export
• Avogadro CJSON export for visualization of normal modes
• Both GUI and command-line interfaces
• Pre-built applications for Linux, Windows and macOS

🔗 Software

GitHub:
https://github.com/SebRoLENS/orca-ped-analyzer

The software is open source (MIT) and archived on Zenodo with a DOI.

⚠️ A note about the development

I am an experimental physical chemist, not a computational chemist or a professional software developer. However, I regularly use computational chemistry software as part of my research, and ORCA PED Analyzer was originally developed to address some of my own needs in vibrational analysis.

The development of the software made extensive use of AI-assisted programming.

I have tested it on real ORCA calculations and, based on my own use and validation so far, I believe the software has the potential to be a useful tool.

At the same time, given my primarily experimental background, I would particularly benefit from the opinion of people with deeper expertise in computational chemistry and vibrational analysis.

Independent testing, criticism and methodological feedback would therefore be extremely valuable.

If you try it and notice:

• incorrect behaviour
• questionable assignments
• methodological limitations
• edge cases
• or simply have suggestions for improving the analysis

I'd be very interested to hear your feedback.

Feedback, criticism, validation cases and contributions are very welcome!