1 to 10 of 21 Results
Jun 17, 2025 - Institute for Materials Science
Ikeda, Yuji; Körmann, Fritz, 2025, "Data for: Impact of N on the Stacking Fault Energy and Phase Stability of FCC CrMnFeCoNi: An Ab Initio Study", https://doi.org/10.18419/DARUS-5117, DaRUS, V1
Data for the Publication Impact of N on the Stacking Fault Energy and Phase Stability of FCC CrMnFeCoNi: An Ab Initio Study The dataset contains the DFT data (VASP OUTCARs) that can reproduce the results. The following systems are included: N2 molecule CrMnFeCoNi without interstitial N CrMnFeCoNi with N at the octahedral and the tetrahedral interst... |
May 21, 2025 - A01: Molecular detail in fluid simulations: Density Functional Theory within component and momentum balances
Bursik, Benjamin; Stierle, Rolf; Bauer, Gernot; Gross, Joachim, 2025, "Supplementary Data to: Modelling Interfacial Dynamics Using Hydrodynamic Density Functional Theory: Dynamic Contact Angles and the Role of Local Viscosity", https://doi.org/10.18419/DARUS-4528, DaRUS, V1
Several files are included here: Jupyter notebooks which can be used a) to visualize density profiles of equilibrium and dynamic droplet simulations (DFT, HDFT, MD, NEMD), and to determine the respective contact angle b) to determine and plot the center of mass position of the droplet, to calculate the average or steady-state velocity of the drople... |
May 12, 2025 - PN 6-15
Gaimann, Mario U.; Klopotek, Miriam, 2025, "Replication Data for: Robustly optimal dynamics for active matter reservoir computing (Gaimann and Klopotek, 2025)", https://doi.org/10.18419/DARUS-4620, DaRUS, V1, UNF:6:JR70RsK1jeEUWlriMxeIpw== [fileUNF]
This repository contains raw and post-processed replication data for the publication "Robustly optimal dynamics for active matter reservoir computing" (Gaimann and Klopotek, 2025). The datasets contain physical observables recorded during non-equilibrium simulations of active matter systems (swarms) driven by an external force. These simulations se... |
Mar 7, 2025 - Institute of Thermodynamics and Thermal Process Engineering
Teh, Tiong Wei; Franz, Philipp; Stierle, Rolf; Hansen, Niels; Gross, Joachim, 2025, "Supplementary material for "GPU-accelerated classical density functional theory for alkane adsorption in cationic Faujasites: accuracy and performance comparison with grand canonical Monte Carlo simulations"", https://doi.org/10.18419/DARUS-4710, DaRUS, V1, UNF:6:stHJH07TlPNQ2mlEEjL5kA== [fileUNF]
The data that support the findings of the article "Classical density functional theory for alkane adsorption in cationic Faujasites: comparison with grand canonical Monte Carlo simulations". The dataset includes all adsorption data obtained from GCMC simulations (data_gcmc), from classical DFT calculations (data_dft) and RASPA input files (raspa).... |
Feb 27, 2025 - Spray Segmentation
Jose, Basil; Hampp, Fabian, 2025, "Code for using and training spray segmentation models", https://doi.org/10.18419/DARUS-4739, DaRUS, V1
This dataset contains the necessary code for using our spray segmentation model used in the paper, ML-based semantic segmentation for quantitative spray atomization description. See README for more information. |
Feb 14, 2025 - Institute of Geodesy
Saemian, Peyman; Elmi, Omid; Stroud, Molly; Riggs, Ryan; Kitambo, Benjamin M.; Papa, Fabrice; Allen, George H.; Tourian, Mohammad J., 2024, "Satellite Altimetry-based Extension of global-scale in situ river discharge Measurements (SAEM)", https://doi.org/10.18419/DARUS-4475, DaRUS, V2
The Satellite Altimetry-based Extension of global-scale in situ river discharge Measurements (SAEM) dataset provides a comprehensive solution for addressing gaps in river discharge measurements by leveraging satellite altimetry. This dataset offers enhanced coverage for river discharge estimations by utilizing data from multiple satellite missions... |
Jan 22, 2025 - Materials Design
Zhang, Xi, 2024, "Data for: Ab initio machine-learning unveils strong anharmonicity in non-Arrhenius self-diffusion of tungsten", https://doi.org/10.18419/DARUS-4564, DaRUS, V2
The dataset contains key files to reproduce the results presented in the article " Ab initio machine-learning unveils strong anharmonicity in non-Arrhenius self-diffusion of tungsten": DFT input files: INCAR, KPOINTS. All POSCAR files for DFT and thermodynamic integration Moment tensor potential (MTP) file Training dataset for MTP All Hessian Matri... |
Jul 2, 2024 - Spray Segmentation
Jose, Basil; Hampp, Fabian, 2024, "Code for training and using the droplet segmentation models", https://doi.org/10.18419/DARUS-4147, DaRUS, V1
This dataset contains the necessary code for using our spray segmentation model used in the paper, Machine learning based spray process quantification. More information can be found in the README.md. |
Mar 25, 2024 - A01: Molecular detail in fluid simulations: Density Functional Theory within component and momentum balances
Bursik, Benjamin; Stierle, Rolf; Schlaich, Alexander; Rehner, Philipp; Gross, Joachim, 2024, "Additional Material: Viscosities of Inhomogeneous Systems from Generalized Entropy Scaling", https://doi.org/10.18419/DARUS-3769, DaRUS, V1
This data set contains data of three categories: 1) LAMMPS input files (.lammps), postprocessing python script (.py) and density and velocity profiles (.dat) from NEMD. 2) DFT three-dimensional density profiles (.npy) for all systems. 3) Jupyter notebooks (.ipynb) for the calculation of densities from DFT, viscosity and velocity profiles from entro... |
Mar 1, 2024 - A01: Molecular detail in fluid simulations: Density Functional Theory within component and momentum balances
Bursik, Benjamin; Eller, Johannes; Gross, Joachim, 2024, "Supporting Information: Notebooks, Solute Configurations and Solvation Free Energy Data", https://doi.org/10.18419/DARUS-3756, DaRUS, V1, UNF:6:0QTV2eSt2s5RktyiTCTmAg== [fileUNF]
This dataset contains three types of data: 1) Jupyter notebooks (.ipynb) for the calculation of solvation free energies and for the recreation of all figures in the publication; 2) Gromacs files containing the solute and solvent topology (.gro, .itp, .top), the trajectories (.trr) and simulation parameter files (.mdp); 3) Results for solvation free... |