Published April 21, 2026 | Version 1
Dataset Open

Dataset for the article: Revealing the Structural Origin of Spin--Orbit Coupling with SOPEL

  • 1. University of Chemistry and Technology Prague

Description

____________________Dataset for the article: Revealing the Structural Origin of Spin--Orbit Coupling with SOPEL____________________

Last updated: 2026-04-21
DOI: 10.5281/zenodo.19048438

______Contact______
* Petr Slavicek
* petr.slavicek@vscht.cz
* +420 220 44 3687
* ORCID: 0000-0002-5358-5538
* Dept. of Physical Chemistry. Faculty of Chemical Engineering, University of Chemistry and Technology, Prague
* Technicka 5, 166 28, Prague 6, Czech Republic

______Data manager or custodian______
* Josef Filgas
* josef.filgas@vscht.cz
* +420 220 44 5002
* ORCID: 0000-0003-4840-0671
* Dept. of Physical Chemistry. Faculty of Chemical Engineering, University of Chemistry and Technology, Prague
* Technicka 5, 166 28, Prague 6, Czech Republic

______Licence______
* Dataset the article: Revealing the Structural Origin of Spin--Orbit Coupling with SOPEL by Josef Filgas is licensed under CC BY 4.0
* licence information: https://creativecommons.org/licenses/by/4.0/
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______About the dataset______
Spin--orbit coupling is a key ingredient for many photochemical processes, yet it is commonly reported as an opaque scalar quantity with limited chemical interpretability. Here, we introduce the concept of SOPEL (Spin--Orbit Population ELement), an atom-resolved decomposition of spin--orbit coupling matrix elements (SOCMEs) that reveals their structural origin in molecules. We further present practical selection rules for nonzero couplings in the language of real atomic orbitals, providing an intuitive link between local orbital character and the spin--orbit coupling. Together, the concept converts the SOCMEs from a black-box electronic-structure output into a chemically interpretable quantity. By localizing the structural origin of spin--orbit coupling, SOPEL provides a practical framework not only for interpreting spin-forbidden processes in terms of structure and motion, but also for chemically guided molecular design. Applications to iodine-substituted BODIPY, formaldehyde, benzophenone, and triarylamine--terephthalonitrile show that the approach (i) identifies the atoms and fragments that generate spin--orbit coupling, (ii) characterizes spin--vibronic mechanisms, (iii) captures redistribution of the coupling origin across molecular frameworks, and (iv) explains why heavy-atom participation alone does not guarantee strong coupling.

______Methods of data collection______
* Ab initio calculations
All of the calculations were performed using the ORCA 6.0.1 or Gaussian09, rev. D.01 program packages. The general input files for each type of performed calculations are a part of the dataset.

______Methods of data processing______
The dataset contains only raw data (input files geometries, trajectories, and processing scripts with manuals), therefore no processing is described.

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______File name structure_____
* In the file named “Cartesian_coordinates.txt”, all of the xyz cartesian coordinates of the used geometries are printed and properly described.
* In the file named "recalculations-of-SOC.sh", the SOC recalculation bash script is written, enabling a systematic recalculation of the studied trajectory using ORCA.
* Files with "opt-freq" are input files for the ORCA and  G09 (for BODIPY) optimizations.
* Python scripts used for the analyses are:
    SOPEL-processing.py: processes ORCA recalculations of the trajectories, generated by the recalculations-of-SOC.sh script;
    AO-animation.py: animation of AO contributions to MOs, based on the output from the SOPEL-processing.py script;
    SOCC-SOPELs-animation.py: animation of SOPEL contributions, based on the output from the SOPEL-processing.py script;
    Spheres-animation.py: animation of SOPEL contributions only with the geometry;
    pictures.py: produces images of plots from the two scripts above, based on the output from the SOPEL-processing.py script;
    all-contractions.py: evaluation and print of the contractions for one ORCA calculation.
* Trajectories: contain "mode" in its name and the first word is the molecule    

______File formats______
* .txt: text file
* .sh: script for bash 
* .py: Python script

______SW necessary to open files______
* All the files in the dataset can be opened with any of the text file reading software, e.g., Notepad.

______Units and abbreviations______
* All the cartesian coordinates are given in the Angstrom units.

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______Dataset structure and List of files______
* Cartesian coordinates of all of the used structures:
    Cartesian_coordinates.txt

* Processing script for the trajectory recalculation:
    recalculations-of-SOC.sh

* Input files for the ORCA and Gaussian optimization:
    ORCA-opt-freq.txt
    G09-opt-freq.txt

* Python scripts:
    AO-animation.py
    SOCC-SOPELs-animation.py
    all-contractions.py
    SOPEL-processing.py
    pictures.py
    Spheres-animation.py    

* Trajectories:
    BODIPY-mode-100.txt
    formaldehyde-mode-5.txt
    benzophenone-mode-1.txt

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Additional details

Funding

Czech Science Foundation
Přenos tripletové energie: Cesta k aktivaci UV-chromoforů viditelným světlem GA24-11466S