Data for: Free-energy perturbation in the exchange-correlation space accelerated by machine learning: Application to silica polymorphs

Dataset

DOI

Data for the Publication Free-energy perturbation in the exchange-correlation space accelerated by machine learning: Application to silica polymorphs

This data set contains:

Data for/from the direct upsampling for the rung 1–3 functionals:

        The effective harmonic potentials
        The final moment-tensor potentials (for each phase and functional)
        The training sets for the moment-tensor potentials (VASP OUTCARs)
        Tables of the thermodynamic properties for each phase and functional


Input data for the functional evaluation procedure developed in the associated paper

Identifier
DOI	https://doi.org/10.18419/DARUS-4999
Related Identifier	IsSupplementTo https://doi.org/10.1038/s41524-025-01874-1
Metadata Access	https://darus.uni-stuttgart.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18419/DARUS-4999

Provenance
Creator	Forslund, Axel ; Jung, Jong Hyun (ORCID: 0000-0002-2409-975X); Ikeda, Yuji ; Grabowski, Blazej
Publisher	DaRUS
Contributor	Grabowski, Blazej
Publication Year	2025
Funding Reference	European Commission info:eu-repo/grantAgreement/EC/H2020/865855 ; DFG 358283783 - SFB 1333 ; The state of Baden-Württemberg ; DFG ; Erlangen National High Performance Computing Center (NHR@FAU) of the Friedrich-Alexander Universität Erlangen-Nürnberg (FAU) ; Federal and Bavarian state authorities ; DFG 440719683 ; DFG EXC 2075 - 390740016 ; DFG 519607530 ; Royal Institute of Technology
Rights	CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess	true
Contact	Grabowski, Blazej (University of Stuttgart)

Representation
Resource Type	Dataset
Format	application/zip
Size	140595324; 52572012
Version	1.0
Discipline	Chemistry; Design; Fine Arts, Music, Theatre and Media Studies; Humanities; Natural Sciences; Physics