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81 to 90 of 117 Results
100APB_thermodynamic.txt
Jun 30, 2023 - Replication Data for: Strong impact of spin fluctuations on the antiphase boundaries of weak itinerant ferromagnetic Ni3Al
Plain Text - 125.8 KB - MD5: b49021534108df4456b9dcdc4f127f49
111APB_thermodynamic.txt
Jun 30, 2023 - Replication Data for: Strong impact of spin fluctuations on the antiphase boundaries of weak itinerant ferromagnetic Ni3Al
Plain Text - 125.8 KB - MD5: 2681d95bd34730d8c89e52aee55cb468
Bulk_thermodynamic.txt
Jun 30, 2023 - Replication Data for: Strong impact of spin fluctuations on the antiphase boundaries of weak itinerant ferromagnetic Ni3Al
Plain Text - 125.7 KB - MD5: 79caa586782d28f4eff6028ee5b12d55
MTP-training-set.tar.gz
Jun 30, 2023 - Replication Data for: Strong impact of spin fluctuations on the antiphase boundaries of weak itinerant ferromagnetic Ni3Al
Gzip Archive - 554.0 MB - MD5: 2179eeb854d0bcaf778578d24b2c5b60
Data for: Performance of two complementary machine-learned potentials in modelling chemically complex systems
May 26, 2023
Gubaev, Konstantin; Zaverkin, Viktor; Srinivasan, Prashanth; Duff, Andrew; Kästner, Johannes; Grabowski, Blazej, 2023, "Data for: Performance of two complementary machine-learned potentials in modelling chemically complex systems", https://doi.org/10.18419/DARUS-3516, DaRUS, V1
Data for the publication "Performance of two complementary machine-learned potentials in modelling chemically complex systems", npj. Comp. Mat. This data set contains the datasets of structures in cfg and npz formats INCAR file which was used for VASP calculations python script for reading npz format These are essentially the 2-, 3-, and 4-componen...
CFG_in_distribution_splits.zip
May 26, 2023 - Data for: Performance of two complementary machine-learned potentials in modelling chemically complex systems
ZIP Archive - 70.6 MB - MD5: 53917b372f27e55e617380404c104c2b
training data with 10 cross-validation split, in cfg format
CFG_out_of_distribution.zip
May 26, 2023 - Data for: Performance of two complementary machine-learned potentials in modelling chemically complex systems
ZIP Archive - 201.0 KB - MD5: 99ceed914dda02103fbc6e7c11f110de
testing data in cfg format
INCAR
May 26, 2023 - Data for: Performance of two complementary machine-learned potentials in modelling chemically complex systems
Plain Text - 517 B - MD5: 3481f8c54ebde1c13d6e016ef5b9d493
INCAR file for VASP which was used for calculations
NPZ_in_distribution_splits.zip
May 26, 2023 - Data for: Performance of two complementary machine-learned potentials in modelling chemically complex systems
ZIP Archive - 150.8 MB - MD5: 9bb786377c7162282fa8cbdd11d275da
training data with 10 cross-validation split, in npz format
NPZ_out_of_distribution.zip
May 26, 2023 - Data for: Performance of two complementary machine-learned potentials in modelling chemically complex systems
ZIP Archive - 422.9 KB - MD5: 61b2216e1359cffb4d09edca08980e52
testing data in NPZ format
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