51 to 60 of 2,109 Results
Apr 7, 2026 - Institute of Thermodynamics and Thermal Process Engineering
Nurhuda, Maryam; Teh, Tiong Wei; Packwood, Daniel; Hansen, Niels, 2026, "Supplementary material to 'Machine Learning Prediction of Henry Coefficients of Polar and Nonpolar Gases in Covalent Organic Frameworks: Effects of Interlayer Shifts and Functionalization'", https://doi.org/10.18419/DARUS-5781, DaRUS, V1, UNF:6:VGCNG6AIwbpDFjn2nWVA4w== [fileUNF]
Electronic supplementary materials for the publication stated below. Henry coefficients are calculated by Widom insertion (in RASPA 2.0.47). Contents: - Henry coefficients (CSV) - CoRE-COF original, slipped, and functionalized files (CIF) - RASPA input files. |
Apr 7, 2026 - Coarse-grained non-equilibrium dynamics with generative machine learning
Egenlauf, Patrick; Březinová, Iva; Andergassen, Sabine; Klopotek, Miriam, 2026, "Replication Data for: Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations", https://doi.org/10.18419/DARUS-5613, DaRUS, V3
This dataset contains all relevant data to reproduce the results of the paper titled "Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations". It contains the exact time series data of the two-particle reduced density matrix (2RDM) for each parameter configuration of the parameter scan, with... |
Apr 2, 2026 - Institute of Geodesy
Saemian, Peyman; Tourian, Mohammad J., 2026, "SVS: SWOT Validation Set for Global River Discharge Evaluation", https://doi.org/10.18419/DARUS-5843, DaRUS, V1
The SWOT Validation Set (SVS) is a global gauge-based dataset created for validating river discharge estimates derived from the SWOT mission. It provides discharge time series, gauge metadata, information on the matching of gauges to SWORD river reaches, and auxiliary attributes needed for systematic comparison between satellite-based and in situ d... |
Apr 2, 2026 - SFB 1333 C5 - Groß/ Hansen group, ITT
Wimmer, Erik Jasper; Högler, Marc, 2026, "Replication Data for: "Palladium Hydride Catalysts Confined in Silica Mesopores: Effects on Catalytic Enyne Cyclization"", https://doi.org/10.18419/DARUS-5129, DaRUS, V1, UNF:6:PRcvl3sxtPpN96tzjitc4Q== [fileUNF]
All primary data files of measurement and processed data of the journal article mentioned under related publications from Estes group and Hansen group can be found here. The data ist structured according to the material names and chapters with the following data types: NMR (Bruker, .mnova), Adsorption data (.pdf), TEM (.TIF), MD simulations |
Apr 1, 2026 - Holm group
Grad, Jean-Noël; Tischler, Ingo; Reinauer, Alexander; Kobayashi, Hideki; Kuron, Michael; Hennig, Frederik; Holzer, Markus; Santos Neves, Pedro Miguel; Kamath, Satish Santhosh; Holm, Christian; Weeber, Rudolf, 2026, "Replication Data for: Coupling ESPResSo and waLBerla for scalable soft matter simulations with hydrodynamic interactions", https://doi.org/10.18419/DARUS-5827, DaRUS, V1, UNF:6:KByfmZAwKeYFysqgpoexBQ== [fileUNF]
Build scripts, benchmark scripts, raw data, and analysis scripts accompanying the manuscript "Coupling ESPResSo and waLBerla for scalable soft matter simulations with hydrodynamic interactions". |
Mar 25, 2026 - Institute for Theoretical Physics III: Büchler Group
Roser, Felix; Springer, Etienne Maurice; Büchler, Hans Peter; Lang, Nicolai, 2026, "Replication Data for: "Robust detection of an entanglement transition in the projective transverse-field Ising model"", https://doi.org/10.18419/DARUS-5305, DaRUS, V1
Numerical data to reproduce the plots in Figures 1-3 of the paper "Robust detection of an entanglement transition in the projective transverse-field Ising model" and Figure S3 of the supplementary material. |
Mar 24, 2026 - Institute of Aerospace Thermodynamics
Molina Vogelsang, Pablo, 2026, "Replication Data for: Defocused Shadowgraphy μPTV for Analyzing the Spreading Mechanism of an Impacting Droplet onto a Thin Liquid Film", https://doi.org/10.18419/DARUS-5798, DaRUS, V1, UNF:6:5eUhuBlw71HogHgfbgwTDA== [fileUNF]
Related Publication Supplementary material to: P. Molina Vogelsang, T. Fuchs, S. Schubert & G. Lamanna “Defocused Shadowgraphy μPTV for Analyzing the Spreading Mechanism of an Impacting Droplet onto a Thin Liquid Film” DOI: [DOI will be added after publication] Dataset Description The data were obtained using shadowgraphy-based Defocusing Micro Par... |
Mar 24, 2026 - Timber Constructions
Klemm, Julian; Grönquist, Philippe; Hein, Helen Luisa; Nowak, Jana, 2026, "Python Source Code zu "Material-, Ressourcen- und Emissionseffizienz verschiedener Vollholzwerkstoffe für Stützen im mehrgeschossigen Holzbau"", https://doi.org/10.18419/DARUS-5524, DaRUS, V1
Python Source Code zu "Material-, Ressourcen- und Emissionseffizienz verschiedener Vollholzwerkstoffe für Stützen im mehrgeschossigen Holzbau" |
Mar 24, 2026 - Publication: Rigorous vertical averaging for pseudo-3D modeling of precipitation obstructed fluid flow
Krach, David; Weinhardt, Felix; Class, Holger; Steeb, Holger; Schneider, Martin, 2026, "Code and benchmarks for a vertically averaged drag term for pseudo-3D Stokes simulations", https://doi.org/10.18419/DARUS-5624, DaRUS, V1
Content: This data set includes snapshots of the code used to compute the benchmarks and applications in Krach et al (2026). The included software tools allow users to conduct pseudo-3D Stokes simulations with a geometry-informed drag term as well as analytical drag terms using DuMux. Users can determine permeability, volumetric flux, and local pre... |
Mar 24, 2026 - Publication: Rigorous vertical averaging for pseudo-3D modeling of precipitation obstructed fluid flow
Krach, David; Weinhardt, Felix; Class, Holger; Steeb, Holger; Schneider, Martin, 2026, "Results for pseudo-3D Stokes simulations using a vertically averaged drag term", https://doi.org/10.18419/DARUS-5626, DaRUS, V1
Content: This data set includes all the necessary input data to fully replicate the benchmarks and applications in Krach et al.(2026). In addition, the results for all solvers are provided as raw simulation output as well as in condense form. Complete datasets: 01_SINGLE_PRECIPITATE, 02_SEGMENT1, 03_SEGMENT2, 04_SEGMENT3, 05_WHOLE_DOMAIN Each data... |
