The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/7a53ad3c-73b2-401a-b9a4-e4def0aa71e3

Pidko, Evgeny; Ivan Chernyshov (2024): Source, documentation, tests: MACE: Automated Assessment of Stereochemistry of Transition Metal Complexes and its Applications in Computational Catalysis. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/7a53ad3c-73b2-401a-b9a4-e4def0aa71e3.v1

Software

• Physical Chemistry (incl. Structural)
• Theoretical and Computational Chemistry
• Inorganic Chemistry
• Chemical Sciences

automation, chemoinformatics, computational chemistry, coordination chemistry, homogeneous catalysis, pincer ligands, python3, rdkit, transition metal complexes

GPL-3.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Evgeny Pidko , Ivan Chernyshov

MACE is an open source toolkit for the automated screening and discovery of metal complexes. The main features of the MACE package are to discover all possible configurations for square-planar and octahedral metal complexes, and generate atomic 3D coordinates suitable for quantum-chemical computations. This dataset contains source code, documentation, CLI examples, and test cases for MACE workflow reported in  "MACE: Automated Assessment of Stereochemistry of Transition Metal Complexes and its Applications in Computational Catalysis", J. Chem. Theory Comput.

• 2024-02-19 first online, published, posted

4TU.ResearchData

MACE: Automated Assessment of Stereochemistry of Transition Metal Complexes and its Applications in Computational Catalysis

• https://doi.org/10.1021/acs.jctc.3c01313

• Nederlandse Organisatie voor Wetenschappelijk Onderzoek

TU Delft, Faculty of Applied Sciences, Department of Chemical Engineering