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This is the Data Repository of the University of Stuttgart.

SFB 1313 "Interface-Driven Multi-Field Processes in Porous Media"

SFB 1333 "Molecular heterogeneous catalysis in confined geometries"

Institute of Biochemistry

Institute of Applied Mechanics (MIB)

Institute of Thermodynamics and Thermal Process Engineering

Stuttgart Center for Simulation Science (SC SimTech)

Cluster of Excellence Integrative Computational Design and Construction for Architecture (EXC IntCDC)

SFB/Transregio 161 "Quantitative Methods for Visual Computing"

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571 to 580 of 126,397 Results

database.zip Jul 22, 2025 - Data for: Machine learning potentials for hydrogen absorption in TiCr2 Laves phases ZIP Archive - 92.9 MB - MD5: ebf740d28dfdf11c53fda36a850b60bb database/ contains two subfolders: Training_db/ provides DFT-calculated energies, forces, and stresses for a diverse set of hydrogenated configurations used to train the MLIPs. Test_db/ includes independent DFT-evaluated configurations used to benchmark the predictive accuracy of the trained force fields.
dilute_H_configurations.zip Jul 22, 2025 - Data for: Machine learning potentials for hydrogen absorption in TiCr2 Laves phases ZIP Archive - 120.6 KB - MD5: 28b9f7aee50619e0e388011ea347f5d2 dilute_H_configurations/ offers low-concentration hydrogen configurations for both Laves phases obtained from DFT: C14/ features single and two-hydrogen configurations with interstitial site connectivity types such as face-connected (1D) and edge-connected (2D). C15/ provides analogous configurations with similar connectivity types.
MC_structures.zip Jul 22, 2025 - Data for: Machine learning potentials for hydrogen absorption in TiCr2 Laves phases ZIP Archive - 773.4 KB - MD5: 7864b3abca4291badf91e6acb441ceee MC_structures/ contains minimum-energy hydrogenated structures generated via basin-hopping Monte Carlo (BHMC) simulations using the trained MLIPs. It includes relaxed DFT structures for both C14 and C15 phases, 108-atom C14 metal structures (excluded from the training set), and the structures generated based on Makarova.
trained_MTPs.zip Jul 22, 2025 - Data for: Machine learning potentials for hydrogen absorption in TiCr2 Laves phases ZIP Archive - 22.0 KB - MD5: 55aedfd7225c3da0aca9318f9afc6cc1 trained_MTPs/ contains the final fitted moment tensor potentials (Level 16): C14.mtp for hydrogenated C14 C15.mtp for hydrogenated C15
annotated_videos.zip Jul 22, 2025 - DAZZLE: Drone-Acquired Zebra data for Large-scale Ecology research ZIP Archive - 68.5 GB - MD5: 30a1d57090eb31a77cee8f59d03a093b Documentation README
classifier_network_dataset.zip Jul 22, 2025 - DAZZLE: Drone-Acquired Zebra data for Large-scale Ecology research ZIP Archive - 3.1 GB - MD5: 8eeada2fe6b485b03b4ac9724bdb8865 Documentation README
detector_network_dataset.zip Jul 22, 2025 - DAZZLE: Drone-Acquired Zebra data for Large-scale Ecology research ZIP Archive - 22.9 GB - MD5: 37d3b3b508a38509b1c39e394cf78cad Documentation README
readme.txt Jul 22, 2025 - DAZZLE: Drone-Acquired Zebra data for Large-scale Ecology research Plain Text - 1.0 KB - MD5: d22f803f0b51086eb773e1ac13ce8364 Documentation README
trained_classifier_networks.zip Jul 22, 2025 - DAZZLE: Drone-Acquired Zebra data for Large-scale Ecology research ZIP Archive - 754.8 MB - MD5: d43e1d871ca25ff1044e46ce9d006e45 Documentation README
trained_detector_network.zip Jul 22, 2025 - DAZZLE: Drone-Acquired Zebra data for Large-scale Ecology research ZIP Archive - 141.8 MB - MD5: 0fb3da88dfc3208bdcc07917baa5d147 Documentation README

database.zip

Jul 22, 2025 - Data for: Machine learning potentials for hydrogen absorption in TiCr2 Laves phases

ZIP Archive - 92.9 MB -

database/ contains two subfolders: Training_db/ provides DFT-calculated energies, forces, and stresses for a diverse set of hydrogenated configurations used to train the MLIPs. Test_db/ includes independent DFT-evaluated configurations used to benchmark the predictive accuracy of the trained force fields.

dilute_H_configurations.zip

Jul 22, 2025 - Data for: Machine learning potentials for hydrogen absorption in TiCr2 Laves phases

ZIP Archive - 120.6 KB -

dilute_H_configurations/ offers low-concentration hydrogen configurations for both Laves phases obtained from DFT: C14/ features single and two-hydrogen configurations with interstitial site connectivity types such as face-connected (1D) and edge-connected (2D). C15/ provides analogous configurations with similar connectivity types.

MC_structures.zip

Jul 22, 2025 - Data for: Machine learning potentials for hydrogen absorption in TiCr2 Laves phases

ZIP Archive - 773.4 KB -

MC_structures/ contains minimum-energy hydrogenated structures generated via basin-hopping Monte Carlo (BHMC) simulations using the trained MLIPs. It includes relaxed DFT structures for both C14 and C15 phases, 108-atom C14 metal structures (excluded from the training set), and the structures generated based on Makarova.

trained_MTPs.zip

Jul 22, 2025 - Data for: Machine learning potentials for hydrogen absorption in TiCr2 Laves phases

ZIP Archive - 22.0 KB -

trained_MTPs/ contains the final fitted moment tensor potentials (Level 16): C14.mtp for hydrogenated C14 C15.mtp for hydrogenated C15

annotated_videos.zip

Jul 22, 2025 - DAZZLE: Drone-Acquired Zebra data for Large-scale Ecology research

ZIP Archive - 68.5 GB -

Documentation

README

classifier_network_dataset.zip

Jul 22, 2025 - DAZZLE: Drone-Acquired Zebra data for Large-scale Ecology research

ZIP Archive - 3.1 GB -

Documentation

README

detector_network_dataset.zip

Jul 22, 2025 - DAZZLE: Drone-Acquired Zebra data for Large-scale Ecology research

ZIP Archive - 22.9 GB -

Documentation

README

readme.txt

Jul 22, 2025 - DAZZLE: Drone-Acquired Zebra data for Large-scale Ecology research

Plain Text - 1.0 KB -

Documentation

README

trained_classifier_networks.zip

Jul 22, 2025 - DAZZLE: Drone-Acquired Zebra data for Large-scale Ecology research

ZIP Archive - 754.8 MB -

Documentation

README

trained_detector_network.zip

Jul 22, 2025 - DAZZLE: Drone-Acquired Zebra data for Large-scale Ecology research

ZIP Archive - 141.8 MB -

Documentation

README

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