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Modelling ligand exchange in metal complexes with machine learning potentials

Documentation:
The deposited data sets accompany the publication Modelling ligand exchange in metal complexes with machine learning potentials and are necessary to reproduce the published results. It consists of: 1. MACE models for modeling Mg$^{2+}$ in water and Pd$^{2+}$ in acetonitrile, 2. Training data labelled by reference energies and forces, 3. Starting structures to run umbrella sampling simulations, 4. Plumed input files used in the umbrella sampling.

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Institution:
University of Oxford
Division:
MPLS
Department:
Chemistry
Role:
Creator
ORCID:
0000-0002-6293-5616
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Institution:
Center for Theoretical Chemistry, Ruhr University Bochum
Role:
Creator
More by this author/creator
Institution:
University of Oxford
Division:
MPLS
Department:
Chemistry
Role:
Creator
More by this author/creator
Institution:
Center for Theoretical Chemistry, Ruhr University Bochum
Role:
Creator
More by this author/creator
Institution:
University of Oxford
Division:
MPLS
Department:
Chemistry
Role:
Creator


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Funder identifier:
https://ror.org/00yjd3n13
Grant:
210737


Publisher:
University of Oxford
Publication date:
2024
DOI:


Language:
English
Keywords:
Pubs id:
2013139
Local pid:
pubs:2013139
Deposit date:
2024-07-08

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