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Funding Information Agency: Deutsche Forschungsgemeinschaft Author Affiliation: Universität Stuttgart

1 to 10 of 13 Results

Replication Data for: Diamond magnetometry and gradiometry towards subpicotesla DC ﬁeld measurement May 10, 2022 - 3rd Physics Institute Zhang, Chen, 2022, "Replication Data for: Diamond magnetometry and gradiometry towards subpicotesla DC ﬁeld measurement", https://doi.org/10.18419/darus-2817, DaRUS, V1, UNF:6:jF2VO8F3SvyX3605VjOSlw== [fileUNF] Datasets to reproduce all plots in the paper. Each spreadsheet contains the horizontal and vertical data of a subfigure. The research investigates sensitivity optimization of nitrogen-vacancy center ensemble magnetometry and gradiometry. Subpicotesla magnetic field noise measurem...
Supplementary material for 'Binding free energies for the SAMPL8 CB8 "Drugs of Abuse" challenge from umbrella sampling combined with Hamiltonian replica exchange' Jan 16, 2022 - Institute of Thermodynamics and Thermal Process Engineering Markthaler, Daniel; Kraus, Hamzeh; Hansen, Niels, 2022, "Supplementary material for 'Binding free energies for the SAMPL8 CB8 "Drugs of Abuse" challenge from umbrella sampling combined with Hamiltonian replica exchange'", https://doi.org/10.18419/darus-2109, DaRUS, V1 Binding affinities of seven drug molecules (G1-G7) towards a common receptor (cucurbit[8]uril, CB8) were estimated from molecular dynamics (MD) simulations in the scope of the recent SAMPL8 CB8 "Drugs of Abuse" challenge using the GROMACS MD package. To compare with experimental...
Supplementary material for 'Confinement Effects for Efficient Macrocyclization Reactions with Supported Cationic Molybdenum Imido Alkylidene N‑Heterocyclic Carbene Complexes' Sep 14, 2021 - Molecular Simulation Kraus, Hamzeh; Hansen, Niels, 2021, "Supplementary material for 'Confinement Effects for Efficient Macrocyclization Reactions with Supported Cationic Molybdenum Imido Alkylidene N‑Heterocyclic Carbene Complexes'", https://doi.org/10.18419/darus-1752, DaRUS, V1 This dataset contains simulation input files in GROMACS format accompanying the mentioned publication. Structure, topology, and simulation parameter-files (directory Mdp) are provided for four simulations - a 2.5 nm pore with one catalyst molecule, a 2.5 nm pore with two catalyst...
Supplementary material for 'Adsorption of Light Gases in Covalent Organic Frameworks: Comparison of Classical Density Functional Theory and Grand Canonical Monte Carlo Simulations' Jul 12, 2021 - Institute of Thermodynamics and Thermal Process Engineering Kessler, Christopher; Eller, Johannes; Gross, Joachim; Hansen, Niels, 2021, "Supplementary material for 'Adsorption of Light Gases in Covalent Organic Frameworks: Comparison of Classical Density Functional Theory and Grand Canonical Monte Carlo Simulations'", https://doi.org/10.18419/darus-1775, DaRUS, V1, UNF:6:kTnkyWKU1qxxwfkXXMvp8w== [fileUNF] This dataset contains results from classical Density Functional Theory (DFT) and Grand Canonical Monte Carlo (GCMC) Simulation. We report excellent agreement between the fluid theoretical approach (DFT), which is a more coarse grained approach and stochastic simulation (GCMC) on...
Supplementary material for 'Prediction of Adsorption Isotherms and Selectivities: Comparison between Classical Density Functional Theory Based on the Perturbed-Chain Statistical Associating Fluid Theory Equation of State and Ideal Adsorbed Solution Theory' Mar 29, 2021 - Institute of Thermodynamics and Thermal Process Engineering Sauer, Elmar; Gross, Joachim, 2021, "Supplementary material for 'Prediction of Adsorption Isotherms and Selectivities: Comparison between Classical Density Functional Theory Based on the Perturbed-Chain Statistical Associating Fluid Theory Equation of State and Ideal Adsorbed Solution Theory'", https://doi.org/10.18419/darus-1643, DaRUS, V1 This dataset contains simulation results in ASCII format accompanying the mentioned publication. The filename is structured in the following kind: Number of the figure in which the data is shown, method of simulation (TMMC Transition Matrix Monte Carlo, DFT Density Functional The...
The DUNE-Phasefield Module (release 1.0) Mar 11, 2021 - C02: Upscaling of pore-scale processes involving microstructural evolution Freiherr von Wolff, Lars, 2021, "The DUNE-Phasefield Module (release 1.0)", https://doi.org/10.18419/darus-1634, DaRUS, V1 The DUNE-Phasefield module contains local operators and grid function spaces for solving Cahn-Hilliard and Cahn-Hilliard-Navier-Stokes systems in a FEM framework. The module additionally provides option-classes for physical properties, multiple Cahn-Hilliard potentials, a timeste...
Supplementary material for 'PoreMS: A software tool for generating silica pore models with user-defined surface functionalisation and pore dimensions' Feb 10, 2021 - Molecular Simulation Kraus, Hamzeh, 2021, "Supplementary material for 'PoreMS: A software tool for generating silica pore models with user-defined surface functionalisation and pore dimensions'", https://doi.org/10.18419/darus-1170, DaRUS, V1 This dataset contains Jupiter Notebooks and the necessary structure files needed for generating the pore systems discussed in the related publication. Additionally, high-resolution figures discussed in the paper are added.
The DUNE MMesh Module (Release 1.2) Feb 5, 2021 - B03: Heterogeneous multi-scale methods for two-phase flow in dynamically fracturing porous media Burbulla, Samuel, 2021, "The DUNE MMesh Module (Release 1.2)", https://doi.org/10.18419/darus-1257, DaRUS, V1 The dune-mmesh module is an implementation of the DUNE grid interface that wraps CGAL triangulations in 2D and 3D. It is also capable to export a prescribed set of cell facets as a dim-1 interface grid and remesh the grid when moving this interface.
Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System Jul 21, 2020 - PINN Dynamic System Praditia, Timothy, 2020, "Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System", https://doi.org/10.18419/darus-634, DaRUS, V1 This dataset contains four .xlsx files containing trained values of the ANN weights and biases, along with the hyperparameter values at the end of the training (with noisy dataset). These four files correspond to four different regularization methods.
Input-Output Dataset for Physics-inspired Artificial Neural Network for Dynamic System Jul 21, 2020 - PINN Dynamic System Praditia, Timothy, 2020, "Input-Output Dataset for Physics-inspired Artificial Neural Network for Dynamic System", https://doi.org/10.18419/darus-633, DaRUS, V1 This dataset contains two .mat files, one pre-processed (direct simulation results) and the other one is with added noise. The simulated problem is a thermochemical energy storage problem using CaO/Ca(OH)2 as the material choice. This dataset is used as input-output data pairs ne...

Replication Data for: Diamond magnetometry and gradiometry towards subpicotesla DC ﬁeld measurement

May 10, 2022 - 3rd Physics Institute

Zhang, Chen, 2022, "Replication Data for: Diamond magnetometry and gradiometry towards subpicotesla DC ﬁeld measurement", https://doi.org/10.18419/darus-2817, DaRUS, V1, UNF:6:jF2VO8F3SvyX3605VjOSlw== [fileUNF]

Datasets to reproduce all plots in the paper. Each spreadsheet contains the horizontal and vertical data of a subfigure. The research investigates sensitivity optimization of nitrogen-vacancy center ensemble magnetometry and gradiometry. Subpicotesla magnetic field noise measurem...

Supplementary material for 'Binding free energies for the SAMPL8 CB8 "Drugs of Abuse" challenge from umbrella sampling combined with Hamiltonian replica exchange'

Jan 16, 2022 - Institute of Thermodynamics and Thermal Process Engineering

Markthaler, Daniel; Kraus, Hamzeh; Hansen, Niels, 2022, "Supplementary material for 'Binding free energies for the SAMPL8 CB8 "Drugs of Abuse" challenge from umbrella sampling combined with Hamiltonian replica exchange'", https://doi.org/10.18419/darus-2109, DaRUS, V1

Binding affinities of seven drug molecules (G1-G7) towards a common receptor (cucurbit[8]uril, CB8) were estimated from molecular dynamics (MD) simulations in the scope of the recent SAMPL8 CB8 "Drugs of Abuse" challenge using the GROMACS MD package. To compare with experimental...

Supplementary material for 'Confinement Effects for Efficient Macrocyclization Reactions with Supported Cationic Molybdenum Imido Alkylidene N‑Heterocyclic Carbene Complexes'

Sep 14, 2021 - Molecular Simulation

Kraus, Hamzeh; Hansen, Niels, 2021, "Supplementary material for 'Confinement Effects for Efficient Macrocyclization Reactions with Supported Cationic Molybdenum Imido Alkylidene N‑Heterocyclic Carbene Complexes'", https://doi.org/10.18419/darus-1752, DaRUS, V1

This dataset contains simulation input files in GROMACS format accompanying the mentioned publication. Structure, topology, and simulation parameter-files (directory Mdp) are provided for four simulations - a 2.5 nm pore with one catalyst molecule, a 2.5 nm pore with two catalyst...

Supplementary material for 'Adsorption of Light Gases in Covalent Organic Frameworks: Comparison of Classical Density Functional Theory and Grand Canonical Monte Carlo Simulations'

Jul 12, 2021 - Institute of Thermodynamics and Thermal Process Engineering

Kessler, Christopher; Eller, Johannes; Gross, Joachim; Hansen, Niels, 2021, "Supplementary material for 'Adsorption of Light Gases in Covalent Organic Frameworks: Comparison of Classical Density Functional Theory and Grand Canonical Monte Carlo Simulations'", https://doi.org/10.18419/darus-1775, DaRUS, V1, UNF:6:kTnkyWKU1qxxwfkXXMvp8w== [fileUNF]

This dataset contains results from classical Density Functional Theory (DFT) and Grand Canonical Monte Carlo (GCMC) Simulation. We report excellent agreement between the fluid theoretical approach (DFT), which is a more coarse grained approach and stochastic simulation (GCMC) on...

Supplementary material for 'Prediction of Adsorption Isotherms and Selectivities: Comparison between Classical Density Functional Theory Based on the Perturbed-Chain Statistical Associating Fluid Theory Equation of State and Ideal Adsorbed Solution Theory'

Mar 29, 2021 - Institute of Thermodynamics and Thermal Process Engineering

Sauer, Elmar; Gross, Joachim, 2021, "Supplementary material for 'Prediction of Adsorption Isotherms and Selectivities: Comparison between Classical Density Functional Theory Based on the Perturbed-Chain Statistical Associating Fluid Theory Equation of State and Ideal Adsorbed Solution Theory'", https://doi.org/10.18419/darus-1643, DaRUS, V1

This dataset contains simulation results in ASCII format accompanying the mentioned publication. The filename is structured in the following kind: Number of the figure in which the data is shown, method of simulation (TMMC Transition Matrix Monte Carlo, DFT Density Functional The...

The DUNE-Phasefield Module (release 1.0)

Mar 11, 2021 - C02: Upscaling of pore-scale processes involving microstructural evolution

Freiherr von Wolff, Lars, 2021, "The DUNE-Phasefield Module (release 1.0)", https://doi.org/10.18419/darus-1634, DaRUS, V1

The DUNE-Phasefield module contains local operators and grid function spaces for solving Cahn-Hilliard and Cahn-Hilliard-Navier-Stokes systems in a FEM framework. The module additionally provides option-classes for physical properties, multiple Cahn-Hilliard potentials, a timeste...

Supplementary material for 'PoreMS: A software tool for generating silica pore models with user-defined surface functionalisation and pore dimensions'

Feb 10, 2021 - Molecular Simulation

Kraus, Hamzeh, 2021, "Supplementary material for 'PoreMS: A software tool for generating silica pore models with user-defined surface functionalisation and pore dimensions'", https://doi.org/10.18419/darus-1170, DaRUS, V1

This dataset contains Jupiter Notebooks and the necessary structure files needed for generating the pore systems discussed in the related publication. Additionally, high-resolution figures discussed in the paper are added.

The DUNE MMesh Module (Release 1.2)

Feb 5, 2021 - B03: Heterogeneous multi-scale methods for two-phase flow in dynamically fracturing porous media

Burbulla, Samuel, 2021, "The DUNE MMesh Module (Release 1.2)", https://doi.org/10.18419/darus-1257, DaRUS, V1

The dune-mmesh module is an implementation of the DUNE grid interface that wraps CGAL triangulations in 2D and 3D. It is also capable to export a prescribed set of cell facets as a dim-1 interface grid and remesh the grid when moving this interface.

Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System

Jul 21, 2020 - PINN Dynamic System

Praditia, Timothy, 2020, "Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System", https://doi.org/10.18419/darus-634, DaRUS, V1

This dataset contains four .xlsx files containing trained values of the ANN weights and biases, along with the hyperparameter values at the end of the training (with noisy dataset). These four files correspond to four different regularization methods.

Input-Output Dataset for Physics-inspired Artificial Neural Network for Dynamic System

Jul 21, 2020 - PINN Dynamic System

Praditia, Timothy, 2020, "Input-Output Dataset for Physics-inspired Artificial Neural Network for Dynamic System", https://doi.org/10.18419/darus-633, DaRUS, V1

This dataset contains two .mat files, one pre-processed (direct simulation results) and the other one is with added noise. The simulated problem is a thermochemical energy storage problem using CaO/Ca(OH)2 as the material choice. This dataset is used as input-output data pairs ne...

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