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1 to 10 of 121 Results

Data for: Microstructural Insights into Fast Ion Transport in Solid Electrolytes via Multiscale Modeling Jul 16, 2026 Ou, Yongliang; Scholz, Lena; Keshav, Sanath; Ikeda, Yuji; Kraft, Marvin; Divinski, Sergiy; Gomez-Bombarelli, Rafael; Zeier, Wolfgang; Fritzen, Felix; Grabowski, Blazej, 2026, "Data for: Microstructural Insights into Fast Ion Transport in Solid Electrolytes via Multiscale Modeling", https://doi.org/10.18419/DARUS-5959, DaRUS, V2 The atomistic dataset includes DFT and MD input files, training configurations, and fitted MTPs. The continuum dataset contains the employed geometries, full-field solutions, and effective responses. Scripts for performing quality-level-based local active learning, generating bulk, GB, and polycrystal structures, and analysis are included. Scripts...
PolycrystalDiffusion-main.zip Jul 16, 2026 - Data for: Microstructural Insights into Fast Ion Transport in Solid Electrolytes via Multiscale Modeling ZIP Archive - 58.8 KB - MD5: f2bf9f29747c9cd2b26846fad583f5b6
Codes.zip Jul 6, 2026 - Data for: Microstructural Insights into Fast Ion Transport in Solid Electrolytes via Multiscale Modeling ZIP Archive - 2.9 GB - MD5: cb7385c90dab9ea39c083854e4900927
Figures.zip Jul 6, 2026 - Data for: Microstructural Insights into Fast Ion Transport in Solid Electrolytes via Multiscale Modeling ZIP Archive - 167.5 MB - MD5: 77b90a0f36bafc4c5465084e1b7c7135
Data for: Machine learning interatomic potentials for ordered mesoporous yttrium silicates Jun 17, 2026 Frank, Daniel Kevin, 2026, "Data for: Machine learning interatomic potentials for ordered mesoporous yttrium silicates", https://doi.org/10.18419/DARUS-6117, DaRUS, V1 Data for the master's thesis "Machine learning interatomic potentials for ordered mesoporous yttrium silicates" by Daniel Kevin Frank. This dataset contains the files mentioned in the thesis, the three domain-specific Moment Tensor Potentials (MTPs) with their training sets, and instructions to create the Python environments. The files mentioned in...
DaRUS.zip Jun 17, 2026 - Data for: Machine learning interatomic potentials for ordered mesoporous yttrium silicates ZIP Archive - 226.0 MB - MD5: 8933a1fc76d699c5e2f9ead665ea8ea4
Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials May 21, 2026 Ou, Yongliang; Ikeda, Yuji; Scholz, Lena; Divinski, Sergiy; Fritzen, Felix; Grabowski, Blazej, 2024, "Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials", https://doi.org/10.18419/DARUS-4510, DaRUS, V2 The data in this repository support the findings presented in the article "Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials" by Ou et al. The repository contains the training sets, the fitted machine-learning interatomic potentials (MTPs), and the relaxed bulk and gr...
data.zip May 21, 2026 - Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials ZIP Archive - 31.6 MB - MD5: d5c85bb9407e9222441f1b4b52621a01
Data for: Machine-learning interatomic potentials achieving CCSD(T) accuracy for systems with extended covalent networks and van der Waals interactions Feb 24, 2026 Ikeda, Yuji; Forslund, Axel; Kumar, Pranav; Ou, Yongliang; Jung, Jong Hyun; Koehn, Andreas; Grabowski, Blazej, 2026, "Data for: Machine-learning interatomic potentials achieving CCSD(T) accuracy for systems with extended covalent networks and van der Waals interactions", https://doi.org/10.18419/DARUS-5272, DaRUS, V1 Data for reproducing the results in the manuscript "Machine-learning interatomic potentials achieving CCSD(T) accuracy for systems with extended covalent networks and van der Waals interactions". Find further details in README.md.
0.TBLITE.zip Feb 24, 2026 - Data for: Machine-learning interatomic potentials achieving CCSD(T) accuracy for systems with extended covalent networks and van der Waals interactions ZIP Archive - 5.4 MB - MD5: e47de33e072b0e00ef67bb153ef9e829 GFN2-xTB results. Further details are found in `README.md`.

Data for: Microstructural Insights into Fast Ion Transport in Solid Electrolytes via Multiscale Modeling

Jul 16, 2026

Ou, Yongliang; Scholz, Lena; Keshav, Sanath; Ikeda, Yuji; Kraft, Marvin; Divinski, Sergiy; Gomez-Bombarelli, Rafael; Zeier, Wolfgang; Fritzen, Felix; Grabowski, Blazej, 2026, "Data for: Microstructural Insights into Fast Ion Transport in Solid Electrolytes via Multiscale Modeling", https://doi.org/10.18419/DARUS-5959, DaRUS, V2

The atomistic dataset includes DFT and MD input files, training configurations, and fitted MTPs. The continuum dataset contains the employed geometries, full-field solutions, and effective responses. Scripts for performing quality-level-based local active learning, generating bulk, GB, and polycrystal structures, and analysis are included. Scripts...

PolycrystalDiffusion-main.zip

Jul 16, 2026 - Data for: Microstructural Insights into Fast Ion Transport in Solid Electrolytes via Multiscale Modeling

ZIP Archive - 58.8 KB -

Codes.zip

Jul 6, 2026 - Data for: Microstructural Insights into Fast Ion Transport in Solid Electrolytes via Multiscale Modeling

ZIP Archive - 2.9 GB -

Figures.zip

Jul 6, 2026 - Data for: Microstructural Insights into Fast Ion Transport in Solid Electrolytes via Multiscale Modeling

ZIP Archive - 167.5 MB -

Data for: Machine learning interatomic potentials for ordered mesoporous yttrium silicates

Jun 17, 2026

Frank, Daniel Kevin, 2026, "Data for: Machine learning interatomic potentials for ordered mesoporous yttrium silicates", https://doi.org/10.18419/DARUS-6117, DaRUS, V1

Data for the master's thesis "Machine learning interatomic potentials for ordered mesoporous yttrium silicates" by Daniel Kevin Frank. This dataset contains the files mentioned in the thesis, the three domain-specific Moment Tensor Potentials (MTPs) with their training sets, and instructions to create the Python environments. The files mentioned in...

DaRUS.zip

Jun 17, 2026 - Data for: Machine learning interatomic potentials for ordered mesoporous yttrium silicates

ZIP Archive - 226.0 MB -

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

May 21, 2026

Ou, Yongliang; Ikeda, Yuji; Scholz, Lena; Divinski, Sergiy; Fritzen, Felix; Grabowski, Blazej, 2024, "Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials", https://doi.org/10.18419/DARUS-4510, DaRUS, V2

The data in this repository support the findings presented in the article "Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials" by Ou et al. The repository contains the training sets, the fitted machine-learning interatomic potentials (MTPs), and the relaxed bulk and gr...

data.zip

May 21, 2026 - Data for: Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials

ZIP Archive - 31.6 MB -

Data for: Machine-learning interatomic potentials achieving CCSD(T) accuracy for systems with extended covalent networks and van der Waals interactions

Feb 24, 2026

Ikeda, Yuji; Forslund, Axel; Kumar, Pranav; Ou, Yongliang; Jung, Jong Hyun; Koehn, Andreas; Grabowski, Blazej, 2026, "Data for: Machine-learning interatomic potentials achieving CCSD(T) accuracy for systems with extended covalent networks and van der Waals interactions", https://doi.org/10.18419/DARUS-5272, DaRUS, V1

Data for reproducing the results in the manuscript "Machine-learning interatomic potentials achieving CCSD(T) accuracy for systems with extended covalent networks and van der Waals interactions". Find further details in README.md.

0.TBLITE.zip

Feb 24, 2026 - Data for: Machine-learning interatomic potentials achieving CCSD(T) accuracy for systems with extended covalent networks and van der Waals interactions

ZIP Archive - 5.4 MB -

GFN2-xTB results. Further details are found in `README.md`.

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