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71 to 80 of 104 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
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
read_npz.py
May 26, 2023 - Data for: Performance of two complementary machine-learned potentials in modelling chemically complex systems
Python Source Code - 238 B - MD5: 64d14bcaa8283dca5e2c0ed59cb0b573
script which demonstrates the fields in npz files
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