Materials Design

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51 to 60 of 109 Results

8.mtp Oct 29, 2024 - Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials Unknown - 7.3 KB - MD5: 1c935b8799191952ff73f418debbf3e3
8.mtp Oct 29, 2024 - Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials Unknown - 7.3 KB - MD5: c2e3ee89b7afb5be27e30e07cd9ed6c3
8.mtp Oct 29, 2024 - Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials Unknown - 7.2 KB - MD5: 9088b0f6a6db98bb108793dfd7d4d67b
active_learning.sh Oct 29, 2024 - Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials Shell Script - 4.0 KB - MD5: 2d7dcc8db713b385823146fb569c1d3f
orderedbulk.txt Oct 29, 2024 - Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials Plain Text - 2.3 MB - MD5: 1f131f726365e5f600e26e7f76cde292
sigma3_-111.txt Oct 29, 2024 - Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials Plain Text - 2.2 MB - MD5: 78589de14996a1421f854b09818285c7
sigma3_1-12.txt Oct 29, 2024 - Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials Plain Text - 2.5 MB - MD5: 3e7865d0d35e10140d083d1563c40876
sigma5.txt Oct 29, 2024 - Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials Plain Text - 2.1 MB - MD5: a08b793c7e7c29ad384ce749484e4a7f
figures_data_thermo_properties.tar.gz Mar 8, 2024 - Data for: Electronic Moment Tensor Potentials include both electronic and vibrational degrees of freedom Gzip Archive - 208.2 MB - MD5: 02869003ed9591a9fe8e5ea5b8595daa Data for the four figures in the manuscript. This also includes the thermodynamic properties with different contributions.
Nb.tar.gz Mar 8, 2024 - Data for: Electronic Moment Tensor Potentials include both electronic and vibrational degrees of freedom Gzip Archive - 24.9 MB - MD5: 99df3e36b9ad64780fa8eb01c614ddfd The MTPs that make up the eMTP, along with the training set for each of the MTPs, the INCAR and KPOINTS used for generating the training data; the Hesse matrices used as reference in the thermodynamic integration; and the free energy contributions in parametrised form.

8.mtp

Oct 29, 2024 - Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials

Unknown - 7.3 KB -

8.mtp

Oct 29, 2024 - Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials

Unknown - 7.3 KB -

8.mtp

Oct 29, 2024 - Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials

Unknown - 7.2 KB -

active_learning.sh

Oct 29, 2024 - Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials

Shell Script - 4.0 KB -

orderedbulk.txt

Oct 29, 2024 - Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials

Plain Text - 2.3 MB -

sigma3_-111.txt

Oct 29, 2024 - Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials

Plain Text - 2.2 MB -

sigma3_1-12.txt

Oct 29, 2024 - Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials

Plain Text - 2.5 MB -

sigma5.txt

Oct 29, 2024 - Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials

Plain Text - 2.1 MB -

figures_data_thermo_properties.tar.gz

Mar 8, 2024 - Data for: Electronic Moment Tensor Potentials include both electronic and vibrational degrees of freedom

Gzip Archive - 208.2 MB -

Data for the four figures in the manuscript. This also includes the thermodynamic properties with different contributions.

Nb.tar.gz

Mar 8, 2024 - Data for: Electronic Moment Tensor Potentials include both electronic and vibrational degrees of freedom

Gzip Archive - 24.9 MB -

The MTPs that make up the eMTP, along with the training set for each of the MTPs, the INCAR and KPOINTS used for generating the training data; the Hesse matrices used as reference in the thermodynamic integration; and the free energy contributions in parametrised form.

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