11 to 20 of 331 Results
Menzel, Stephan; Bengel, Christopher, 2025, "JART VCM v1b Readvar", https://doi.org/10.26165/JUELICH-DATA/VCRB1E, Jülich DATA, V1
The JART VCM v1b Readvar model represents a further extension of the JART VCM v1b var model which additionally considers read noise. The equivalent circuit diagram of the JART VCM v1b Readvar model can be seen in Fig. 1 (JART_VCM_v1b_Readvar.jpg) [1]. The read noise is implemente... |
Menzel, Stephan; Bengel, Christopher, 2025, "JART VCM v1 generic", https://doi.org/10.26165/JUELICH-DATA/QELKG7, Jülich DATA, V1
The JART VCM v1 generic model is a special variant of the more general JART VCM v1 model. It provides in total 16 data sets to study the influence of the nonlinearity SL of the switching kinetics and the resistance ratio r on different circuit designs [1]. Four different slopes a... |
Mar 25, 2025 - Peter Grünberg Institute (PGI) – Electronic Materials (PGI-7)
Zurhelle, Alexander, 2025, "JART OxRelax", https://doi.org/10.26165/JUELICH-DATA/VC9OCI, Jülich DATA, V1
In the search for an oxide-based 2D electron system with a large concentration of highly mobile electrons, a promising strategy is to introduce electrons through donor doping while spatially separating electrons and donors to prevent scattering. In SrTiO3, this can be achieved by... |
Menzel, Stephan; Bengel, Christopher, 2025, "JART VCM v1b var", https://doi.org/10.26165/JUELICH-DATA/FERGKU, Jülich DATA, V1
The JART VCM v1b var model represents an extension of the JART VCM v1b model which additionally considers device-to-device and cycle-to-cycle variability. The ECD can be seen in Fig. 1. The physical equations are the same as in the v1b model. Device-to-device variability is achie... |
Menzel, Stephan; Bengel, Christopher, 2025, "JART ECM v1", https://doi.org/10.26165/JUELICH-DATA/4F3ITW, Jülich DATA, V1
The JART ECM v1 model describes the switching dynamics of Electrochemical Metallization Cells, which are also known as Conductive Bridge RAM (CBRAM) or atomic switches. The model includes the redox-reactions at the metal insulator interfaces, ion hopping transport, and the electr... |
Menzel, Stephan; Bengel, Christopher, 2025, "JART VCM v1", https://doi.org/10.26165/JUELICH-DATA/TQOP7I, Jülich DATA, V1
Short description: The JART VCM v1 model was developed to simulate the switching characteristics of devices based on the valence change mechanism (also called OxRAM). In this model, the ionic defect concentration (oxygen vacancies) in the disc region close to the active electrode... |
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Menzel, Stephan; Bengel, Christopher, 2025, "JART VCM v1b", https://doi.org/10.26165/JUELICH-DATA/LUA8QY, Jülich DATA, V1
The JART VCM v1b var model represents an extension of the JART VCM v1b model which additionally considers device-to-device and cycle-to-cycle variability. The ECD can be seen in Fig. 1. The physical equations are the same as in the v1b model. Device-to-device variability is achie... |
Menzel, Stephan; Bengel, Christopher, 2025, "JART VCM v2", https://doi.org/10.26165/JUELICH-DATA/NFHTAR, Jülich DATA, V1
The JARV VCM v2 model is an extension of the JART VCM v1 model. It includes two different switching locations I and II (see JART VCM v2.jpg). Thus, the model uses two state variables. In addition, diffusion between region I and II is included in this model, enabling the simulatio... |
Mar 24, 2025 - Institute of Neuroscience and Medicine – Structural and functional organisation of the brain (INM-1)
Oberstrass, Alexander; Vaca-Cerda, Esteban; Upschulte, Eric; Niu, Meiqi; Palomero-Gallagher, Nicola; Graessel, David; Schiffer, Christian; Axer, Markus; Amunts, Katrin; Dickscheid, Timo, 2025, "Replication Data for: From Fibers to Cells: Fourier-Based Registration Enables Virtual Cresyl Violet Staining From 3D Polarized Light Imaging", https://doi.org/10.26165/JUELICH-DATA/ZOBFV7, Jülich DATA, V1
This dataset contains replication data for the article "From Fibers to Cells: Fourier-Based Registration Enables Virtual Cresyl Violet Staining From 3D Polarized Light Imaging." It comprises 31 square regions of interest (ROIs), each measuring 4,069 pixels (~5.3 mm), extracted fr... |
Mar 12, 2025 - mGROWA Germany
Herrmann, Frank; McNamara, Ian; Flörke, Martina; Uschan, Thorben, 2025, "Grundwassergewinnungsindizes (GWGI) in Deutschland in Bezug auf die Grundwassergewinnung im Jahr 2019", https://doi.org/10.26165/JUELICH-DATA/PCOLRP, Jülich DATA, V1
Grundwassergewinnungsindizes (GWGI) in Deutschland in Bezug auf die Grundwassergewinnung im Jahr 2019. Weitere Details sind im Begleitdokument verfügbar: https://datapub.fz-juelich.de/mgrowa/GWGI_Germany_v2023/ |
