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stk_paper.pdf (4.63 MB)

Stk: An Extendable Python Framework for Automated Molecular and Supramolecular Structure Assembly and Discovery

preprint
submitted on 08.03.2021, 12:50 and posted on 09.03.2021, 12:10 by Lukas Turcani, Andrew Tarzia, Filip Szczypiński, Kim Jelfs
Computational software workflows are emerging as all-in-one solutions to speed up the discovery of new materials.
Many computational approaches require the generation of realistic structural models for property prediction and candidate screening. However, molecular and supramolecular materials represent classes of materials with many potential applications for which there is no go-to database of existing structures or general protocol for generating structures. Here, we report a new version of the supramolecular toolkit, stk, an open-source, extendable and modular Python framework for general structure generation of (supra)molecular structures. Our construction approach follows a bottom-up process and minimises the input required from the user, making stk user-friendly and applicable to many material classes. This version of stk includes metal-containing structures and rotaxanes as well as general implementation and interface improvements. Additionally, this version includes built-in tools for exploring chemical space with an evolutionary algorithm and tools for database generation and visualisation. The latest version of stk is freely available at github.com/lukasturcani/stk

Funding

The Royal Society

Leverhulme Trust Research Project Grant

ERC CoMMaD 758370

History

Email Address of Submitting Author

k.jelfs@imperial.ac.uk

Institution

Imperial College London

Country

United Kingdom

ORCID For Submitting Author

0000-0001-7683-7630

Declaration of Conflict of Interest

No conflict of interest

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