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1 to 10 of 19 Results
Replication Data for: https://doi.org/10.48550/arXiv.2503.10581
Sep 10, 2025
Binninger, Tobias, 2025, "Replication Data for: https://doi.org/10.48550/arXiv.2503.10581", https://doi.org/10.26165/JUELICH-DATA/VEHDXR, Jülich DATA, V1
This dataset contains the input and output data from DWave quantum annealing presented in the article "Simulating charging characteristics of lithium iron phosphate by electro-ionic optimization on a quantum annealer" (https://doi.org/10.48550/arXiv.2503.10581).
Replication Data for: https://doi.org/10.1021/acs.jpclett.3c03295
Aug 29, 2025
Bruch, Nils, 2025, "Replication Data for: https://doi.org/10.1021/acs.jpclett.3c03295", https://doi.org/10.26165/JUELICH-DATA/3GNMUU, Jülich DATA, V1
Data has been generated using COMSOL Multiphysics. Upon reasonable request to the contact person, raw data can be shared to reproduce the plots from the publication.
Replication Data for: https://doi.org/10.1063/5.0250135
Aug 29, 2025
Bruch, Nils, 2025, "Replication Data for: https://doi.org/10.1063/5.0250135", https://doi.org/10.26165/JUELICH-DATA/XHVT5W, Jülich DATA, V1
Data has been generated using COMSOL Multiphysics. Upon reasonable request to the contact person, raw data can be shared to reproduce the plots from the publication.
Replication Data for: https://doi.org/10.48550/arXiv.2507.14751
Aug 29, 2025
Bruch, Nils, 2025, "Replication Data for: https://doi.org/10.48550/arXiv.2507.14751", https://doi.org/10.26165/JUELICH-DATA/JS6SHP, Jülich DATA, V1
Data has been generated using Mathematica and analyzed within the same notebook. Upon reasonable request to the contact person, raw data can be shared to reproduce the plots from the publication.
Replication Data for: https://doi.org/10.48550/arXiv.2503.06768
Jun 17, 2025
Juhi Singh, 2025, "Replication Data for: https://doi.org/10.48550/arXiv.2503.06768", https://doi.org/10.26165/JUELICH-DATA/GG80VM, Jülich DATA, V1
The files contains all the data used for generating all figures in the manuscript. All the folders the named according to the figure numbers.
Replication Data for: Accuracy and sensitivity of NH3 measurements using the Dräger Tube Method
Replication Data for: Accuracy and sensitivity of NH3 measurements using the Dräger Tube Method
Feb 5, 2025
Kelsch, Alexander, 2024, "Replication Data for: Accuracy and sensitivity of NH3 measurements using the Dräger Tube Method", https://doi.org/10.26165/JUELICH-DATA/0LAIFH, Jülich DATA, V2
Dataset used for the work titled "Accuracy and sensitivity of NH3 measurements using the Dräger Tube Method" and R scripts for the data cleaning, analysis and figure creation.
Experimental FZJ ParFlow DE06 hydrologic forecasts
May 14, 2024
Belleflamme, Alexandre; Hammoudeh, Suad; Görgen, Klaus; Kollet, Stefan, 2024, "Experimental FZJ ParFlow DE06 hydrologic forecasts", https://doi.org/10.26165/JUELICH-DATA/GROHKP, Jülich DATA, V1
The dataset entails experimental ParFlow hydrologic model forecast simulations by BELLEFLAMME, HAMMOUDEH, GOERGEN, and KOLLET. The basic setup and configuration is described in "Belleflamme et al. (2023): Hydrological forecasting at impact scale: the integrated ParFlow hydrologic...
Convection-permitting ICON-LAM Simulations for Renewable Energy Potential Estimates over Southern Africa
Mar 20, 2024
Chen, Shuying; Poll, Stefan; Hendricks Franssen, Harrie-Jan; Heinrichs, Heidi; Vereecken, Harry; Goergen, Klaus, 2024, "Convection-permitting ICON-LAM Simulations for Renewable Energy Potential Estimates over Southern Africa", https://doi.org/10.26165/JUELICH-DATA/JYGQ65, Jülich DATA, V1
This regional atmospheric modelling dataset was produced by a dynamical downscaling setup, the ICOsahedral Nonhydrostatic (ICON) Numerical Weather Prediction (ICON-NWP) model v2.6.4 was run in limited area mode (ICON-LAM) with a weather forecast configuration (ICON-D2) from the G...
Simulation of CSDs for Automated Tuning Solutions (SimCATS)
Feb 27, 2024
Hader, Fabian; Fleitmann, Sarah; Fuchs, Fabian, 2024, "Simulation of CSDs for Automated Tuning Solutions (SimCATS)", https://doi.org/10.26165/JUELICH-DATA/QIUWRZ, Jülich DATA, V1
Simulation of CSDs for Automated Tuning Solutions (SimCATS) is a Python framework for simulating charge stability diagrams (CSDs) typically measured during the tuning process of qubits. Source code: https://github.com/f-hader/SimCATS Documentation: https://simcats.readthedocs.io/...
A tool to migrate sensor metadata from ODM1 to an API-driven sensor-management system
Jan 22, 2024
Loup, Ulrich; Sorg, Jürgen; Kunkel, Ralf, 2024, "A tool to migrate sensor metadata from ODM1 to an API-driven sensor-management system", https://doi.org/10.26165/JUELICH-DATA/BJPRZK, Jülich DATA, V1
The observation-data model (ODM) is a relational data model combining observation data and the corresponding metadata. The migration tool extracts the metadata and inserts it into a management tool for sensor and device data using API calls. The tool is implemented in Python and...
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