2026-10-14 https://api.researchdata.se/oai-pmh

oai:researchdata.se:doi-10-5281-zenodo-15809229/0 2026-03-03 subject:ssif:103 subject:ssif:1 subject:ssif:10201 subject:ssif:102 principal:slug:chalmers-university-of-technology

info:eu-repo/semantics/other http://purl.org/dc/dcmitype/Dataset https://doi.org/10.5281/zenodo.15809229 Models and data supporting the paper "Predicting neutron experiments from first principles: A workflow powered by machine learning" https://orcid.org/0000-0002-8549-6839 https://orcid.org/0000-0001-5272-6530 https://orcid.org/0000-0001-5262-3339 https://orcid.org/0000-0002-5282-7726 https://orcid.org/0000-0003-3023-8565 Skoro, Goran Turanyi, Rastislav https://orcid.org/0000-0002-6501-4089 https://orcid.org/0000-0002-2516-6061 Physical Sciences Fysik Computer Sciences Datavetenskap (datalogi) This record accompanies the publication "Predicting neutron experiments from first principles: A workflow powered by machine learning". It comprises the machine-learned interatomic potentials (MLIPs) constructed and employed in that work with their respective training data as well as the experimental inelastic neutron scattering data for crystalline benzene presented in the publication. Hydrogenated Sc-doped BaTiO3 nep-BaScTiOH.txt – MLIP based on the neuroevolution potential (NEP) form nep-BaScTiOH.zip – model ensemble with the underlying training and validation data BaScTiOH-R2SCAN.db – database with reference data, in sql-lite format, readable using the ase package Benzene nep-benzene.txt – MLIP based on the neuroevolution potential (NEP) form nep-benzene.zip – model ensemble with the underlying training and validation data benzene-CX.db – database with reference data, in sql-lite format, readable using the ase package reduced-benzene-tosca.zip – experimental inelastic neutron scattering data info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ Chalmers University of Technology Chalmers tekniska högskola 2025-07-04T00:00:00Z