CHASAM 2026: Datasets for Chalmers School on Atomic Modeling
https://doi.org/10.5281/zenodo.22790961
Data used in the hands-on notebooks of the CHASAM 2026 school, https://chasam.materialsmodeling.org. All MD was run with GPUMD using a NEP potential, and each trajectory archive holds the input structure (model.xyz), the NEP model (nep.txt), the GPUMD input (run.in) and the trajectory (dump.xyz).
Zenodo record: 10.5281/zenodo.22790961
Files
Archive
System
Contents
BaTiO3_models.tar
BaTiO3
structures, a pretrained qNEP model and pretrained tensorial NEP models for dipole, polarizability and atomic virial
BaTiO3_spectroscopy.tar
BaTiO3
GPUMD runs at 100, 240, 360 and 500 K with dipole-derivative (dpdt.out) and polarizability output
CsPbI3_NPT_T650to1_size12_nframes2000.tar.gz
CsPbI3
NPT cooling run from 650 K to 1 K, 12x12x12 supercell with 8640 atoms, 2000 frames
CsPbI3_NVE_T600_size4_nframes100000.tar.gz
CsPbI3
NVE run at 600 K, 4x4x4 supercell with 320 atoms, 100000 frames
CsPbI3_NVT_T650_size18_nframes500.tar.gz
CsPbI3
NVT run at 650 K, 18x18x18 supercell with 29160 atoms, 500 frames
day1_basic_training.zip
NiAl
initial DFT training and validation databases, and one NEP model with five cross-validation splits
day2_active_learning.zip
NiAl
R2SCAN reference databases, validation data and three active-learning generations, each with structure generation, model and tests
day2_advanced_nep_hyperparameters.zip
NiAl
training and validation data, and NEP models scanning n_max, l_max and ZBL, with RMSE and MD-speed summaries
day2_advanced_two_stage_training.zip
NiAl
training and validation data, and single-stage and two-stage NEP models
day3_thermodynamic_integration.tar.gz
SiO2
Frenkel-Ladd and reversible-scaling GPUMD runs for coesite and stishovite at 8 GPa, holding NPT equilibration at 300 K, five Frenkel-Ladd switching runs per phase and three reversible-scaling ramps per phase from 300 to 1800 K
FAPI_md-run-active-learning.tar.gz
FAPbI3
NPT heating run from 1 K to 600 K, 2x2x2 supercell with 96 atoms, 2000 frames
FAPI_training.tar.gz
FAPbI3
DFT databases for two active-learning generations, and NEP models trained on 100 to 900 structures, with and without ZBL
mcmd-vcsgc-data.tar.gz
FeCr
700 VCSGC Monte Carlo/MD runs of 8000 atoms, at seven temperatures from 300 to 900 K and 100 values of phi from -2.5 to 2.5 with kappa = 200, holding concentration traces (mcmd-*.out) and thermodynamic output (thermo-*.out)
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https://doi.org/10.5281/zenodo.22790961
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