ISIS Neutron and Muon Source Data Journal
This is a page describing data taken during an experiment at the ISIS Neutron and Muon Source. Information about the ISIS Neutron and Muon Source can be found at https://www.isis.stfc.ac.uk.
Benchmarking machine learnt interatomic potentials for analysis of neutron spectroscopy data
Abstract: We seek to benchmark the abilities of recent advances in machine learnt (ML) potentials, through comparison to inelastic neutron spectroscopy (INS) measurements. INS provides unparalleled sensitivity to the local atomic environment by probing vibrations. Our chosen system provides a unique challenge to ML methods as the interactions are strongly hydrogen bonding/dispersion related (something ab initio methods typically struggle with). We hope to also make use of new high pressure capabilities on TOSCA to examine a hypothesised phase change at high pressure.
Principal Investigator: Dr Keith Butler
Local Contact: Dr Jeff Armstrong
Experimenter: Dr Alin Elena
Experimenter: Mr Mueen Taj
DOI: 10.5286/ISIS.E.RB2510190
ISIS Experiment Number: RB2510190
| Part DOI | Instrument | Public release date | Download Link |
|---|---|---|---|
| 10.5286/ISIS.E.RB2510190-1 | TOSCA | 24 September 2028 | Download |
Publisher: STFC ISIS Neutron and Muon Source
Data format: RAW/Nexus
Select the data format above to find
out more about it.
Data Citation
The recommended format for citing this dataset in a research
publication is as:
[author], [date], [title], [publisher],
[doi]
For Example:
Dr Keith Butler et al; (2025): Benchmarking machine learnt interatomic potentials for analysis of neutron spectroscopy data, STFC ISIS Neutron and Muon Source, https://doi.org/10.5286/ISIS.E.RB2510190
Data is released under the CC-BY-4.0 license.
