xTB
Extended Tight Binding
Computing Applications (HPC) LGPL-3.0 (Free)
About
A semi-empirical quantum chemical program suite developed by the Grimme group. It performs fast and accurate calculations of structures, energies, and properties using the GFN-xTB family of methods for large molecular systems.
Key Features
- Methods: GFN0-xTB, GFN1-xTB, GFN2-xTB
- Speed: 1000x faster than DFT
- Applications: conformers, reactions, MD
- Properties: energies, gradients, Hessians
Citation
Bannwarth, C. et al. GFN2-xTB – An Accurate and Broadly Parametrized Self-Consistent Tight-Binding Quantum Chemical Method. J. Chem. Theory Comput. 15, 1652-1671 (2019). DOI:10.1021/acs.jctc.8b01176
Frequently Asked Questions
What is xTB?
xTB is a computing applications (hpc) application available in the Paramus App Store. A semi-empirical quantum chemical program suite developed by the Grimme group. It performs fast and accurate calculations of structures, energies, and properties using the GFN-xTB family of methods for large molecular systems.
Is xTB free to use?
Yes. xTB is distributed under the LGPL-3.0 (Free) license and is available at no cost through the Paramus App Store.
How do I install xTB?
xTB is installed through Paramus Chemistry OS, an on-premise Windows platform for computational chemistry. Open the Paramus App Store in your local installation and select xTB for one-click deployment.
What are the key features of xTB?
Key features of xTB include: Methods: GFN0-xTB, GFN1-xTB, GFN2-xTB; Speed: 1000x faster than DFT; Applications: conformers, reactions, MD; Properties: energies, gradients, Hessians.
What type of application is xTB?
xTB belongs to the “Computing Applications (HPC)” category in the Paramus App Store. It runs on Paramus Chemistry OS and can also be accessed through Paramus Cloud for supported workflows.
What platform does xTB run on?
xTB runs on Paramus Chemistry OS, a Windows-based on-premise platform that provides local compute power for demanding simulations. It requires a Paramus OS installation with appropriate hardware resources.
Can xTB be automated or integrated with AI workflows?
Yes. xTB is available as part of the Paramus ecosystem which supports MCP (Model Context Protocol) tools for AI-driven automation. This enables integration with large language models and automated research pipelines.
How should I cite xTB in publications?
The recommended citation for xTB is: Bannwarth, C. et al. GFN2-xTB – An Accurate and Broadly Parametrized Self-Consistent Tight-Binding Quantum Chemical Method. J. Chem. Theory Comput. 15, 1652-1671 (2019). DOI:10.1021/acs.jctc.8b01176