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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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    <item>
      <title>DFT dataset and NEP model for MA,Ge,Sn,I3</title>
      <description>MA(Ge,Sn)I3 neuroevolution potential and DFT training data

Training data and machine-learned interatomic potential for MAGeI3, MASnI3 and their mixed compositions.

* `train.xyz` Full training set, 668 structures in extended XYZ format. Reference energies, forces, virials and Born effective charges from FHI-aims.* `nep.txt` The NEP potential, usable directly with GPUMD or calorine.* `control.in` Representative FHI-aims input for a single-point reference calculation.

Reference calculations

FHI-aims with the hybrid meta-GGA r²SCAN50 (`libxc HYB_MGGA_XC_R2SCAN50`), `intermediate` species defaults, scalar-relativistic `atomic_zora`, `sc_accuracy_rho 1e-6`.

The included k_grid is provided as an example and was generated using a k-point density parameter of 5.6, which corresponds to a reciprocal-space sampling of approximately 0.18 Å⁻¹ for the example cell. For other structures, the k_grid should be regenerated from the chosen k-point density.

NEP Potential

Fourth-generation NEP with charge support (`nep4_zbl_charge1`), six species (C, N, H, Ge, Sn, I), radial and angular cutoffs of 8 and 4 Å, a ZBL repulsive term with `use_typewise_cutoff_zbl 0.7`, and `lambda_q 0.1`.Fitted to the complete `train.xyz` for 300000 generations.Root-mean-square errors against the training data are 4.3 meV/atom for energies, 0.126 eV/Å for forces, 0.020 eV/atom for virials and 0.072 e for Born effective charges.</description>
      <pubDate>Sun, 09 Aug 2026 00:00:00 GMT</pubDate>
      <link>https://researchdata.se/sv/catalogue/dataset/doi-10-5281-zenodo-21863902</link>
      <guid>https://researchdata.se/sv/catalogue/dataset/doi-10-5281-zenodo-21863902</guid>
      <dc:publisher>Chalmers tekniska högskola</dc:publisher>
      <dc:creator>Ngoipala, Apinya</dc:creator>
      <dc:creator>Fransson, Erik</dc:creator>
      <dc:creator>Erhart, Paul</dc:creator>
      <dc:creator>Wiktor, Julia</dc:creator>
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