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      <title>DFT dataset and qNEP models for CsGeBr3, CsSnBr3, PbTiO3</title>
      <description>Charge-aware machine-learned interatomic potentials and their training data for the three perovskites PbTiO3, CsGeBr3 and CsSnBr3.

Files

Two files per system, named _:

_train.xyz – training set in extended XYZ format, with reference energies, forces and virials.

_nep.txt – the NEP potential, usable directly with GPUMD or calorine.

Systems

PbTiO3 – 345 structures, 5–320 atoms per structure, reference method VASP with r2SCAN.

CsGeBr3 – 110 structures, 5–160 atoms per structure, reference method FHI-aims with r2SCAN50.

CsSnBr3 – 103 structures, 5–320 atoms per structure, reference method FHI-aims with r2SCAN50.

Potentials

All three are fourth-generation NEPs with charge support (charge_mode 1, lambda_q 0.1), three species, radial and angular cutoffs of 8 and 4 Å, trained for 300 000 generations. The two halides additionally use a ZBL repulsive term.</description>
      <pubDate>Wed, 19 Aug 2026 00:00:00 GMT</pubDate>
      <link>https://researchdata.se/sv/catalogue/dataset/doi-10-5281-zenodo-22007823</link>
      <guid>https://researchdata.se/sv/catalogue/dataset/doi-10-5281-zenodo-22007823</guid>
      <dc:publisher>Chalmers tekniska högskola</dc:publisher>
      <dc:creator>Fransson, Erik</dc:creator>
      <dc:creator>Ngoipala, Apinya</dc:creator>
      <dc:creator>Deswal, Priyanka</dc:creator>
      <dc:creator>Berger, Ethan</dc:creator>
      <dc:creator>Erhart, Paul</dc:creator>
      <dc:creator>Wiktor, Julia</dc:creator>
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