Stuttgart Center for Simulation Science (SC SimTech)

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1 to 10 of 344 Results

Stepwise Benchmarking: Data-Scarce Groundwater Heat Pumps' Modeling(Universität Stuttgart) Apr 14, 2026Surrogate models for groundwater flow simulations This dataverse contains the datasets for all steps of our stepwise benchmark based on input data from the region of Munich. The first step starts with a single heat pump in a heterogeneous 2D subsurface aquifer with seasonal operational pump parameters. The second step contains two potentially interacting heat plumes and fewer data points due to th...
Trained Neural Networks on Simulated Data of Groundwater Heat Plume Characteristics Apr 14, 2026 - Surrogate models for groundwater flow simulations Baratto, Thomas, 2026, "Trained Neural Networks on Simulated Data of Groundwater Heat Plume Characteristics", https://doi.org/10.18419/DARUS-5815, DaRUS, V1, UNF:6:UMWqR0dTYJ/r2z0j/MZJgw== [fileUNF] Inference package for thermal plume prediction (v1.0.0). Contains pre-trained MLP and random network models, the ba-predict CLI, sample input files, and a Dockerfile. CPU-only - no GPU required. Extract with: tar xzf ba-thermal-plume-v1.0.0.tar.gz && cd ba-thermal-plume-v1.0.0 && pip install -e . Full source code (training scripts, data, tests) ava...
Replication Data for: Version 1.0.0 - FEniCSx-preCICE: Coupling FEniCSx to other simulation software Apr 9, 2026 - Usability and Sustainability of Simulation Software Vinnitchenko, Niklas; Desai, Ishaan; Rodenberg, Benjamin; Hildebrand, Philip; Humbert, Angelika; Uekermann, Benjamin, 2026, "Replication Data for: Version 1.0.0 - FEniCSx-preCICE: Coupling FEniCSx to other simulation software", https://doi.org/10.18419/DARUS-5847, DaRUS, V1 This dataset contains software and result files for the publication: Version 1.0.0 - FEniCSx-preCICE: Coupling FEniCSx to other simulation software in the journal SoftwareX.
Replication Data for: Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations 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...
Supplementary Data to: "Activation mechanism of the full-length histidine kinase LvrB from pathogenic Leptospira" Mar 20, 2026 - PN 3-11 Pluhackova, Kristyna; Hiller, Sebastian; Agustoni, Elia, 2026, "Supplementary Data to: "Activation mechanism of the full-length histidine kinase LvrB from pathogenic Leptospira"", https://doi.org/10.18419/DARUS-5664, DaRUS, V2 MD data (author K. Pluhackova): Initial coordinate and simulation input files and a coordinate files of the final outputs as well as of the simulation trajectories (protein only) for all-atom MD simulations of LvrB performed using CHARMM36m/TIP4p in GROMACS2023. (pdb, xtc) Simulation data on phosphorylated aspartic acid (residue APP) with parameter...
Replication Data for: Optimal information injection and transfer mechanisms for active matter reservoir computing (Gaimann and Klopotek, 2025) Mar 11, 2026 - PN 6-15 Gaimann, Mario U.; Klopotek, Miriam, 2025, "Replication Data for: Optimal information injection and transfer mechanisms for active matter reservoir computing (Gaimann and Klopotek, 2025)", https://doi.org/10.18419/DARUS-4805, DaRUS, V2, UNF:6:C1gH8zVD6YKFF/O3ZhSaSA== [fileUNF] This repository contains raw and post-processed replication data for the publication "Optimal information injection and transfer mechanisms for active matter reservoir computing" (Gaimann and Klopotek, 2025). The datasets contain physical observables recorded during non-equilibrium simulations of active matter systems (swarms) driven by an external...
Supplementary Videos for: Optimal information injection and transfer mechanisms for active matter reservoir computing (Gaimann and Klopotek, 2025) Mar 11, 2026 - PN 6-15 Gaimann, Mario U.; Klopotek, Miriam, 2025, "Supplementary Videos for: Optimal information injection and transfer mechanisms for active matter reservoir computing (Gaimann and Klopotek, 2025)", https://doi.org/10.18419/DARUS-4806, DaRUS, V2 This dataset contains supplementary videos for the publication "Optimal information injection and transfer mechanisms for active matter reservoir computing" (Gaimann and Klopotek, 2025) (to be published). The datasets contain physical observables recorded during non-equilibrium simulations of active matter systems (swarms) driven by an external for...
Replication Data for: Apax: A Flexible and Performant Framework For The Development of Machine-Learned Interatomic Potentials Mar 10, 2026 - PN 6A-3 Schäfer, Moritz; Segreto, Nico; Zills, Fabian; Holm, Christian; Kästner, Johannes, 2026, "Replication Data for: Apax: A Flexible and Performant Framework For The Development of Machine-Learned Interatomic Potentials", https://doi.org/10.18419/DARUS-5007, DaRUS, V1 This repository contains the data for our paper on "Apax: A Flexible and Performant Framework For The Development of Machine-Learned Interatomic Potentials". This includes both the simulation results as well as workflows and input files needed to recreate the results. Different experiments are contained on different branches and a more detailed REA...
PN 3 A-5(Universität Stuttgart) Mar 10, 2026PN 3 AI software tools for materials development
Data for: Excited State Opto-Ionic Reservoir Computing in Hybrid Perovskite Electrochemically-Gated Luminescent Cells Mar 3, 2026 - Deschler group Dataverse Kollenz, Philipp, 2026, "Data for: Excited State Opto-Ionic Reservoir Computing in Hybrid Perovskite Electrochemically-Gated Luminescent Cells", https://doi.org/10.18419/DARUS-5656, DaRUS, V1 This dataset contains measurement data related to the paper "Excited State Opto-Ionic Reservoir Computing in Hybrid Perovskite Electrochemically-Gated Luminescent Cells". The data originates from optical and electrical experiments investigating neuromorphic reservoir computing based on opto-ionic dynamics in hybrid lead-halide perovskite devices.Th...

Stepwise Benchmarking: Data-Scarce Groundwater Heat Pumps' Modeling(Universität Stuttgart)

Apr 14, 2026Surrogate models for groundwater flow simulations

This dataverse contains the datasets for all steps of our stepwise benchmark based on input data from the region of Munich. The first step starts with a single heat pump in a heterogeneous 2D subsurface aquifer with seasonal operational pump parameters. The second step contains two potentially interacting heat plumes and fewer data points due to th...

Trained Neural Networks on Simulated Data of Groundwater Heat Plume Characteristics

Apr 14, 2026 - Surrogate models for groundwater flow simulations

Baratto, Thomas, 2026, "Trained Neural Networks on Simulated Data of Groundwater Heat Plume Characteristics", https://doi.org/10.18419/DARUS-5815, DaRUS, V1, UNF:6:UMWqR0dTYJ/r2z0j/MZJgw== [fileUNF]

Inference package for thermal plume prediction (v1.0.0). Contains pre-trained MLP and random network models, the ba-predict CLI, sample input files, and a Dockerfile. CPU-only - no GPU required. Extract with: tar xzf ba-thermal-plume-v1.0.0.tar.gz && cd ba-thermal-plume-v1.0.0 && pip install -e . Full source code (training scripts, data, tests) ava...

Replication Data for: Version 1.0.0 - FEniCSx-preCICE: Coupling FEniCSx to other simulation software

Apr 9, 2026 - Usability and Sustainability of Simulation Software

Vinnitchenko, Niklas; Desai, Ishaan; Rodenberg, Benjamin; Hildebrand, Philip; Humbert, Angelika; Uekermann, Benjamin, 2026, "Replication Data for: Version 1.0.0 - FEniCSx-preCICE: Coupling FEniCSx to other simulation software", https://doi.org/10.18419/DARUS-5847, DaRUS, V1

This dataset contains software and result files for the publication: Version 1.0.0 - FEniCSx-preCICE: Coupling FEniCSx to other simulation software in the journal SoftwareX.

Replication Data for: Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations

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...

Supplementary Data to: "Activation mechanism of the full-length histidine kinase LvrB from pathogenic Leptospira"

Mar 20, 2026 - PN 3-11

Pluhackova, Kristyna; Hiller, Sebastian; Agustoni, Elia, 2026, "Supplementary Data to: "Activation mechanism of the full-length histidine kinase LvrB from pathogenic Leptospira"", https://doi.org/10.18419/DARUS-5664, DaRUS, V2

MD data (author K. Pluhackova): Initial coordinate and simulation input files and a coordinate files of the final outputs as well as of the simulation trajectories (protein only) for all-atom MD simulations of LvrB performed using CHARMM36m/TIP4p in GROMACS2023. (pdb, xtc) Simulation data on phosphorylated aspartic acid (residue APP) with parameter...

Replication Data for: Optimal information injection and transfer mechanisms for active matter reservoir computing (Gaimann and Klopotek, 2025)

Mar 11, 2026 - PN 6-15

Gaimann, Mario U.; Klopotek, Miriam, 2025, "Replication Data for: Optimal information injection and transfer mechanisms for active matter reservoir computing (Gaimann and Klopotek, 2025)", https://doi.org/10.18419/DARUS-4805, DaRUS, V2, UNF:6:C1gH8zVD6YKFF/O3ZhSaSA== [fileUNF]

This repository contains raw and post-processed replication data for the publication "Optimal information injection and transfer mechanisms for active matter reservoir computing" (Gaimann and Klopotek, 2025). The datasets contain physical observables recorded during non-equilibrium simulations of active matter systems (swarms) driven by an external...

Supplementary Videos for: Optimal information injection and transfer mechanisms for active matter reservoir computing (Gaimann and Klopotek, 2025)

Mar 11, 2026 - PN 6-15

Gaimann, Mario U.; Klopotek, Miriam, 2025, "Supplementary Videos for: Optimal information injection and transfer mechanisms for active matter reservoir computing (Gaimann and Klopotek, 2025)", https://doi.org/10.18419/DARUS-4806, DaRUS, V2

This dataset contains supplementary videos for the publication "Optimal information injection and transfer mechanisms for active matter reservoir computing" (Gaimann and Klopotek, 2025) (to be published). The datasets contain physical observables recorded during non-equilibrium simulations of active matter systems (swarms) driven by an external for...

Replication Data for: Apax: A Flexible and Performant Framework For The Development of Machine-Learned Interatomic Potentials

Mar 10, 2026 - PN 6A-3

Schäfer, Moritz; Segreto, Nico; Zills, Fabian; Holm, Christian; Kästner, Johannes, 2026, "Replication Data for: Apax: A Flexible and Performant Framework For The Development of Machine-Learned Interatomic Potentials", https://doi.org/10.18419/DARUS-5007, DaRUS, V1

This repository contains the data for our paper on "Apax: A Flexible and Performant Framework For The Development of Machine-Learned Interatomic Potentials". This includes both the simulation results as well as workflows and input files needed to recreate the results. Different experiments are contained on different branches and a more detailed REA...

PN 3 A-5(Universität Stuttgart)

Mar 10, 2026PN 3

AI software tools for materials development

Data for: Excited State Opto-Ionic Reservoir Computing in Hybrid Perovskite Electrochemically-Gated Luminescent Cells

Mar 3, 2026 - Deschler group Dataverse

Kollenz, Philipp, 2026, "Data for: Excited State Opto-Ionic Reservoir Computing in Hybrid Perovskite Electrochemically-Gated Luminescent Cells", https://doi.org/10.18419/DARUS-5656, DaRUS, V1

This dataset contains measurement data related to the paper "Excited State Opto-Ionic Reservoir Computing in Hybrid Perovskite Electrochemically-Gated Luminescent Cells". The data originates from optical and electrical experiments investigating neuromorphic reservoir computing based on opto-ionic dynamics in hybrid lead-halide perovskite devices.Th...

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