PN 3

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

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1 to 10 of 30 Results

Data for: ART-SM: Boosting Fragment-Based Backmapping by Machine Learning Apr 16, 2025 - PN 3-11 Pluhackova, Kristyna; Pfaendner, Christian; Unger, Benjamin; Korn, Viktoria Helena, 2025, "Data for: ART-SM: Boosting Fragment-Based Backmapping by Machine Learning", https://doi.org/10.18419/DARUS-4134, DaRUS, V1 The simulation files, molecule topologies, and analysis workflows required to generate the results of our paper 'ART-SM: Boosting Fragment-Based Backmapping by Machine Learning' published in J. Chem. Theory Comput.. In details: simulations.tar.gz: Contains the pdb (molecular structure), xtc (trajectory), mdp (MD parameters), itp (topology), and top...
Supplementary Data for '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 '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 used and useful gromacs files (topologies and mdp files) jupyter noteb...
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 corresponding training sets; 2) The atomistic structure of 2delta Kear-Wilsdor...
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 (ISOTHERM), and run the equilibrium and non-equilibrium MD simulations, respec...
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.
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...
Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes Feb 16, 2024 - PN3-5 Sriram, Siddharth, 2024, "Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes", https://doi.org/10.18419/DARUS-3881, DaRUS, V1 The datasets and codes provided here are associated with our article entitled "Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle". The main idea of the work is to develop surrogate models using the concepts of machine learning (ML) to predict the onset of wrinkling insta...
Replication data of C6 group for: "Disentanglement of surface and confinement effects for diene metathesis in mesoporous confinement" Dec 22, 2023 - SFB 1333 C6 - Holm group, ICP Tischler, Ingo; Schlaich, Alexander; Holm, Christian, 2023, "Replication data of C6 group for: "Disentanglement of surface and confinement effects for diene metathesis in mesoporous confinement"", https://doi.org/10.18419/DARUS-3642, DaRUS, V1 The simulation scripts and the simulation data of the journal article mentioned under related publications from C6 group can be found here. The data is structured according to figures and schemes in the research article and contains the following data types: compressed (tar) text data files and python scripts. The structure within the tar file is a...
Softwarepackage CCMOR2 Dec 19, 2023 - Projects without PN Affiliation Rettberg, Johannes; Wittwar, Dominik; Herkert, Robin, 2023, "Softwarepackage CCMOR2", https://doi.org/10.18419/DARUS-3839, DaRUS, V1 The dataset entails the code of the CCMOR2 package developed in Matlab. This project aims to model and perform certified model order reduction on multi-physical systems. The systems are formulated in the port-Hamiltonian framework which incorporates useful system theoretic properties such as stability and passivity. The approach is subvided into th...
Data for: Dynamically stabilized phases with full ab initio accuracy: Thermodynamics of Ti, Zr, Hf with a focus on the hcp-bcc transition Dec 14, 2023 - Materials Design Jung, Jong Hyun; Forslund, Axel; Srinivasan, Prashanth; Grabowski, Blazej, 2023, "Data for: Dynamically stabilized phases with full ab initio accuracy: Thermodynamics of Ti, Zr, Hf with a focus on the hcp-bcc transition", https://doi.org/10.18419/DARUS-3582, DaRUS, V1, UNF:6:PcXLVWUQ0T4geRQy0F0sgg== [fileUNF] Data for the publication, Dynamically stabilized phases with full ab initio accuracy: Thermodynamics of Ti, Zr, Hf with a focus on the hcp-bcc transition, Phys. Rev. B 108, 184107 (2023). This data set contains 1) - the training sets (VASP files), - the low moment-tensor-potentials (MTPs) and high-MTPs (for seperate hcp and bcc phases and combined...

Data for: ART-SM: Boosting Fragment-Based Backmapping by Machine Learning

Apr 16, 2025 - PN 3-11

Pluhackova, Kristyna; Pfaendner, Christian; Unger, Benjamin; Korn, Viktoria Helena, 2025, "Data for: ART-SM: Boosting Fragment-Based Backmapping by Machine Learning", https://doi.org/10.18419/DARUS-4134, DaRUS, V1

The simulation files, molecule topologies, and analysis workflows required to generate the results of our paper 'ART-SM: Boosting Fragment-Based Backmapping by Machine Learning' published in J. Chem. Theory Comput.. In details: simulations.tar.gz: Contains the pdb (molecular structure), xtc (trajectory), mdp (MD parameters), itp (topology), and top...

Supplementary Data for '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 '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 used and useful gromacs files (topologies and mdp files) jupyter noteb...

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 corresponding training sets; 2) The atomistic structure of 2delta Kear-Wilsdor...

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 (ISOTHERM), and run the equilibrium and non-equilibrium MD simulations, respec...

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.

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...

Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes

Feb 16, 2024 - PN3-5

Sriram, Siddharth, 2024, "Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes", https://doi.org/10.18419/DARUS-3881, DaRUS, V1

The datasets and codes provided here are associated with our article entitled "Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle". The main idea of the work is to develop surrogate models using the concepts of machine learning (ML) to predict the onset of wrinkling insta...

Replication data of C6 group for: "Disentanglement of surface and confinement effects for diene metathesis in mesoporous confinement"

Dec 22, 2023 - SFB 1333 C6 - Holm group, ICP

Tischler, Ingo; Schlaich, Alexander; Holm, Christian, 2023, "Replication data of C6 group for: "Disentanglement of surface and confinement effects for diene metathesis in mesoporous confinement"", https://doi.org/10.18419/DARUS-3642, DaRUS, V1

The simulation scripts and the simulation data of the journal article mentioned under related publications from C6 group can be found here. The data is structured according to figures and schemes in the research article and contains the following data types: compressed (tar) text data files and python scripts. The structure within the tar file is a...

Softwarepackage CCMOR2

Dec 19, 2023 - Projects without PN Affiliation

Rettberg, Johannes; Wittwar, Dominik; Herkert, Robin, 2023, "Softwarepackage CCMOR2", https://doi.org/10.18419/DARUS-3839, DaRUS, V1

The dataset entails the code of the CCMOR2 package developed in Matlab. This project aims to model and perform certified model order reduction on multi-physical systems. The systems are formulated in the port-Hamiltonian framework which incorporates useful system theoretic properties such as stability and passivity. The approach is subvided into th...

Data for: Dynamically stabilized phases with full ab initio accuracy: Thermodynamics of Ti, Zr, Hf with a focus on the hcp-bcc transition

Dec 14, 2023 - Materials Design

Jung, Jong Hyun; Forslund, Axel; Srinivasan, Prashanth; Grabowski, Blazej, 2023, "Data for: Dynamically stabilized phases with full ab initio accuracy: Thermodynamics of Ti, Zr, Hf with a focus on the hcp-bcc transition", https://doi.org/10.18419/DARUS-3582, DaRUS, V1, UNF:6:PcXLVWUQ0T4geRQy0F0sgg== [fileUNF]

Data for the publication, Dynamically stabilized phases with full ab initio accuracy: Thermodynamics of Ti, Zr, Hf with a focus on the hcp-bcc transition, Phys. Rev. B 108, 184107 (2023). This data set contains 1) - the training sets (VASP files), - the low moment-tensor-potentials (MTPs) and high-MTPs (for seperate hcp and bcc phases and combined...

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