41 to 50 of 7,544 Results
Aug 29, 2025 - Campus Collection
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. |
Plain Text - 165 B - SHA-256: a9379c0602dba3432eb0fe65e36a5610cba110f7f1b67625a33e0599b1cc3bea
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Aug 29, 2025 - Campus Collection
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. |
Aug 29, 2025 -
Replication Data for: https://doi.org/10.1063/5.0250135
Plain Text - 165 B - SHA-256: a9379c0602dba3432eb0fe65e36a5610cba110f7f1b67625a33e0599b1cc3bea
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Aug 29, 2025 - Campus Collection
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. |
Plain Text - 195 B - SHA-256: 0c7d6b0eaadd218b6fc4e6d9011fa8c870e01dba5e76f06f97892d77adb093aa
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Aug 22, 2025 - Peter Grünberg Institute (PGI) – Electronic Materials (PGI-7)
Schnieders, Kristoffer; Stasner, Pascal; Bai, Peixuan; Wouters, Dirk; Wiefels, Stefan, 2025, "Read noise variability in thermally oxidized Tantalum oxide-based ReRAM devices", https://doi.org/10.26165/JUELICH-DATA/BO2NPG, Jülich DATA, V1
This dataset contains raw and processed read noise measurements from thermally oxidized TaOx-based VCM devices, supporting the analysis presented in the associated APL publication. The raw data includes 1 s current readout traces recorded after resistive switching. The evaluation... |
Unknown - 254.9 MB - SHA-256: 3a5dd916d8c9bb1f1d26cc6f3b311f77d952ddaa78918a7c7e85718058893cd4
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Unknown - 148.0 MB - SHA-256: 65b38a04f71cb4ec9bbd27987be7943234a24529f7df229b99dee676f24f4b6b
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Python Source Code - 29.3 KB - SHA-256: 6f2c31315617763d3e3b03d6571619edc2567c13c3535217364fa88ec7f37e40
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