stk : A Python toolkit for supramolecular assembly
File(s)Turcani_et_al-2018-Journal_of_Computational_Chemistry.pdf (2.64 MB)
Published version
Author(s)
Turcani, Lukas
Berardo, Enrico
Jelfs, KE
Type
Journal Article
Abstract
A tool for the automated assembly, molecular optimization and property calculation
of supramolecular materials is presented. stk is a modular, extensible and open-source
Python library that provides a simple Python API and integration with third party
computational codes. stk currently supports the construction of linear polymers, small
linear oligomers, organic cages in multiple topologies, and covalent organic frameworks
(COFs) in multiple framework topologies, but is designed to be easy to extend to new,
unrelated, supramolecules or new topologies. Extension to metal-organic frameworks
(MOFs), metallocycles or supramolecules, such as catenanes, would be straightforward.
Through integration with third party codes, stk offers the user the opportunity to explore
the potential energy landscape of the assembled supramolecule and then calculate
the supramolecule’s structural features and properties. stk provides support for highthroughput
screening of large batches of supramolecules at a time. The source code of
the program can be found at https://github.com/supramolecular-toolkit/stk.
of supramolecular materials is presented. stk is a modular, extensible and open-source
Python library that provides a simple Python API and integration with third party
computational codes. stk currently supports the construction of linear polymers, small
linear oligomers, organic cages in multiple topologies, and covalent organic frameworks
(COFs) in multiple framework topologies, but is designed to be easy to extend to new,
unrelated, supramolecules or new topologies. Extension to metal-organic frameworks
(MOFs), metallocycles or supramolecules, such as catenanes, would be straightforward.
Through integration with third party codes, stk offers the user the opportunity to explore
the potential energy landscape of the assembled supramolecule and then calculate
the supramolecule’s structural features and properties. stk provides support for highthroughput
screening of large batches of supramolecules at a time. The source code of
the program can be found at https://github.com/supramolecular-toolkit/stk.
Date Issued
2018-09-05
Date Acceptance
2018-05-20
Citation
Journal of Computational Chemistry, 2018, 39 (23), pp.1931-1942
ISSN
0192-8651
Publisher
Wiley
Start Page
1931
End Page
1942
Journal / Book Title
Journal of Computational Chemistry
Volume
39
Issue
23
Copyright Statement
© 2018 The Authors. Journal of Computational Chemistry published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons
Attribution License, which permits use, distribution and reproduction in any
medium, provided the original work is properly cited.
Attribution License, which permits use, distribution and reproduction in any
medium, provided the original work is properly cited.
Sponsor
The Royal Society
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (EPSRC)
Grant Number
UF120469
EP/M017257/1
EP/P005543/1
Subjects
Science & Technology
Physical Sciences
Chemistry, Multidisciplinary
Chemistry
python
high-throughput screening
supramolecular assembly
materials design
supramolecular chemistry
CONJUGATED POLYMERS
DESIGN
PROGRAM
CRYSTALLINE
BINDING
high-throughput screening
materials design
python
supramolecular assembly
supramolecular chemistry
0306 Physical Chemistry (incl. Structural)
0307 Theoretical and Computational Chemistry
Chemical Physics
Publication Status
Published
Date Publish Online
2018-09-24