SimTech EXC 2075 Project Network 3 "Data-integrated model reduction for particles and continua"
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1 to 10 of 39 Results
PN 3-15(Universität Stuttgart)
Jan 10, 2025
Bottom-up modeling of conducting porous materials via molecular simulation
PN 3A-8(Universität Stuttgart)
Dec 17, 2024
SimTech PN 3A-8: "Certified Coupled Model Order Reduction (CCMOR)"
PN 3-5(Universität Stuttgart)
Dec 17, 2024
SimTech Project PN 3-5 "Data-integrated Multiscale Modeling of Diffusion-driven Processes in Porous Media" and SimTech Project PN 3-5 (II) "Data-driven multi-scale stability analysis of multi-stimuli-responsive hydrogels"
PN 3A-9(Universität Stuttgart)
Dec 13, 2024
Bottom-up modelling of COF/electrode systems for CO2 reduction in confinement
Supplementary Data for 'To enter or not to enter: The vastly different energy landscapes of the membrane insertions of monomeric gasdermin D and A3'
Nov 7, 2024 - PN 3-11
Korn, Viktoria Helena; Pluhackova, Kristyna, 2024, "Supplementary Data for 'To enter or not to enter: The vastly different energy landscapes of the membrane insertions of monomeric gasdermin D and A3'", https://doi.org/10.18419/darus-4474, DaRUS, V1
Simulation files, molecular structures and trajectories, and jupyter notebooks used for analysis underlaying our publication on membrane insertion of monomeric gasdermin D to E. coli polar lipid extract (PLE). In detail: charmm36-july2017.ff simulation directory for GROMACS 202X...
Replication Data for: Origin of the yield stress anomaly in L12 intermetallics unveiled with physically informed machine-learning potentials
Oct 8, 2024 - PN 3-10
Xu, Xiang, 2024, "Replication Data for: Origin of the yield stress anomaly in L12 intermetallics unveiled with physically informed machine-learning potentials", https://doi.org/10.18419/darus-4480, DaRUS, V1
Data for the manuscript "Origin of the yield stress anomaly in L12 intermetallics unveiled with physically-informed machine-learning potentials", https://doi.org/10.1016/j.actamat.2024.120423. This data set contains: 1) the utilized moment-tensor-potentials (MTP) and the correspo...
Replication Data for: Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous Materials
Apr 23, 2024 - Simulation input scripts to study Transport of Water In Soft confinemenT (TWIST)
Schlaich, Alexander, 2024, "Replication Data for: Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous Materials", https://doi.org/10.18419/darus-3966, DaRUS, V1
Simulation input scripts used for "Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous Materials" The folders the corresponding simulation and analysis files to setup the simulation systems (SETUP), perform the GCMC/MD simulations (ISOTHER...
Replication Data for: Generating Minimal Training Sets for Machine Learned Potentials
Apr 11, 2024 - Holm group
Finkbeiner, Jan; Tovey, Samuel; Holm, Christian, 2024, "Replication Data for: Generating Minimal Training Sets for Machine Learned Potentials", https://doi.org/10.18419/darus-4099, DaRUS, V1
Data and scripts for replicating results and the investigation presented in the paper. This includes the dft parameters for generating training data, all training and data selection scripts for the neural networks, scripts for running and analysing the production simulations with...
Additional Material: Viscosities of Inhomogeneous Systems from Generalized Entropy Scaling
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 calcula...
PN 3A-7(Universität Stuttgart)
Mar 8, 2024
Advanced Learning Strategies for Machine Learned Interatomic Potentials
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