Our group aims to empower chemists with state-of-the-art quantum-chemical analysis tools. The latest project is PyOrbb, used for the automated analysis of complex molecular orbital interactions. PyOrbb makes expert orbital analysis available to all chemists, regardless of their theoretical background, ensuring that knowledge knows no bounds!
Welcome to the PyOrbb project repository. This project is currently led by members of the TheoCheM group at the Vrije Universiteit Amsterdam (Tori Gijzen, Yuman Hordijk, and Trevor Hamlin). We aim to empower computational and non-computational chemists to perform advanced orbital analyses. By presentation of computational data in
This README file serves as a central hub providing project-related information. Feel free to navigate directly to specific sections below or simply scroll down to learn more.
We are striving to optimise our application to facilitate anyone’s journey into the realm of advanced orbital analysis. So if you see any points where we can improve, don’t hesitate to contact us or open an issue in this repository!
The PyOrbb project aims to assist in advanced orbital analysis for computational chemistry calculations. PyOrbb will generate important orbital interaction schemes and related orbital figures automatically, as well as summarise important information such as SFO coefficients, populations, orbital levels and more. These properties are commonly used in computational chemical research analyses.
People often run into the following challenges:
- Hard to get a clear overview of relevant data.
- Data acquisition is often done manually, which can be a chaotic and laborious task.
- The information overload in the output of quantum chemical programs can be intimidating.
The aim of the PyOrbb project is:
- Enhance access to advanced orbital analyses
- To provide an efficient way to isolate all the relevant data
- Create a clear graphical representation of the relevant data that is relevant
Previously, our group has published the PyFrag 2019 program for the automation of fragment approaches and their quantitative analyses along a reaction coordinate. This allowed users to perform the Activation Strain Model (AMS) and the canonical energy decomposition analysis (EDA) for a whole reaction profile with one single input.
Currently, the installation can be done by cloning this repository and having all necessary dependencies. Your Python version should be >=Python3.8 and <=Python3.10
The following is for people who would like to install the repository themselves. For example, to edit and/or contribute code to the project.
Then, clone this repository:
git clone git@github.com:TheoChem-VU/PyOrbb.git
Then move into the new directory and install the package:
cd PyOrbb
python -m pip install --upgrade build pip
python -m build
python -m pip install -e .
To get new updates, simply run:
git pull
PyOrbb is a Python API for reading and working with orbital data from ADF calculations.
The main output at the moment is an Excel document with useful data relating to the orbitals and interactions between orbitals.
To create this Excel document use the pyorbb excel command. Please see pyorbb excel -h for more information.
[AMS rkf file] [should be included once this is known] [Figure horizontal si better than vertical]
[insert example outputs]
At the moment, contribution to this project is limited to our research group. In the foreseeable future, we want to open up to a greater community. This group will include users who a not necessarily familiar with computational analysis of molecular systems or fragment approaches. At the point of the first public rollout, we want to have such groups involved in the process of enhancing this repository.
A preliminary version of PyOrbb was rolled out by Xiaobo Sun assisted by Laurens Groot, who was a PostDoc in the TheoCheM group at the Vrije Universiteit Amsterdam.
Currently, the project has been adopted by a team of active TheoCheM group members consisting of Yuman Hordijk (@YumanHordijk), Tori Gijzen (@ToriGijzen), and dr. Trevor A. Hamlin (@TrevorAHamlin).
Additionally, we are being consulted by Nadine Spychala (@NadineSpychala) from the University of Sussex as a part of cohort 8 in the Open Life Sciences Scheme (https://openlifesci.org/openseeds/ols-8/projects-participants.html, @openlifesci).
If you want to report a problem or suggest an enhancement we'd encourage for you to open an issue in the GitHub repository. Otherwise you can reach us by email (https://www.theochem.nl/contact) or Twitter (@VU_TheoCheM)
You Might be interested in"
- The TheoCheM group
- The Vrije Universiteit Amsterdam
- The PyFrag 2019 program
- Our Python library TC-utility
- For a thorough overview of the theoretical background we recommend the following articles:
- P. Vermeeren, S.C.C. van der Lubbe, C. Fonseca Guerra, F.M. Bickelhaupt, T.A. Hamlin, Nature Protoc. 2020, 15, 649-667. (https://doi.org/10.1038/s41596-019-0265-0)
- T. A. Hamlin, P. Vermeeren, C. Fonseca Guerra, F. M. Bickelhaupt. In: Complementary Bonding Analyses; S. Grabowski, Ed.; De Gruyter: Berlin, 2021, pp 199-212. (https://doi.org/10.1515/9783110660074-008)