PN 3

SimTech EXC 2075 Project Network 3 "Data-integrated model reduction for particles and continua"

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41 to 50 of 803 Results

README.md Apr 23, 2024 - Replication Data for: Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous Materials Markdown Text - 136 B - MD5: 1567ad2f87deb772986ebfa8e26648a6
README.md Apr 23, 2024 - Replication Data for: Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous Materials Markdown Text - 201 B - MD5: c4e9e6890da2982290ec253f2912bd6b
README.md Apr 23, 2024 - Replication Data for: Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous Materials Markdown Text - 321 B - MD5: 457d9490e4cb4a3eabba3381197045df
README.md Apr 23, 2024 - Replication Data for: Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous Materials Markdown Text - 523 B - MD5: 4e462c449dcdb4cdb79fbcefd7d3549e
spce.txt Apr 23, 2024 - Replication Data for: Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous Materials Plain Text - 538 B - MD5: c3b5afc49160f9cdbcb213058e9d12a6
spce.txt Apr 23, 2024 - Replication Data for: Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous Materials Plain Text - 538 B - MD5: c3b5afc49160f9cdbcb213058e9d12a6
spce.txt Apr 23, 2024 - Replication Data for: Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous Materials Plain Text - 538 B - MD5: c3b5afc49160f9cdbcb213058e9d12a6
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 the trained potentials.
generating_minimal_training_sets_for_machine_learned_potentials.tar.gz Apr 11, 2024 - Replication Data for: Generating Minimal Training Sets for Machine Learned Potentials Gzip Archive - 1.7 GB - MD5: a7315aa714d0e0dbe2e05e8a275a73dc Data for reproducing paper results.
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 calculation of densities from DFT, viscosity and velocity profiles from entro...

README.md

Apr 23, 2024 - Replication Data for: Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous Materials

Markdown Text - 136 B -

README.md

Apr 23, 2024 - Replication Data for: Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous Materials

Markdown Text - 201 B -

README.md

Apr 23, 2024 - Replication Data for: Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous Materials

Markdown Text - 321 B -

README.md

Apr 23, 2024 - Replication Data for: Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous Materials

Markdown Text - 523 B -

spce.txt

Apr 23, 2024 - Replication Data for: Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous Materials

Plain Text - 538 B -

spce.txt

Apr 23, 2024 - Replication Data for: Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous Materials

Plain Text - 538 B -

spce.txt

Apr 23, 2024 - Replication Data for: Bridging Microscopic Dynamics and Hydraulic Permeability in Mechanically-Deformed Nanoporous Materials

Plain Text - 538 B -

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 the trained potentials.

generating_minimal_training_sets_for_machine_learned_potentials.tar.gz

Apr 11, 2024 - Replication Data for: Generating Minimal Training Sets for Machine Learned Potentials

Gzip Archive - 1.7 GB -

Data for reproducing paper results.

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 calculation of densities from DFT, viscosity and velocity profiles from entro...

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