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| Hauptseite > Publikationsdatenbank > HRS Instability in Oxide-Based Bipolar Resistive Switching Cells > print |
| Hauptseite > Publikationsdatenbank > HRS Instability in Oxide-Based Bipolar Resistive Switching Cells > print |
| 001 | 889691 | ||
| 005 | 20230209132311.0 | ||
| 024 | 7 | _ | |a 10.1109/TED.2020.3018096 |2 doi |
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| 037 | _ | _ | |a FZJ-2021-00315 |
| 082 | _ | _ | |a 620 |
| 100 | 1 | _ | |a Wiefels, Stefan |0 P:(DE-Juel1)187229 |b 0 |e Corresponding author |u fzj |
| 245 | _ | _ | |a HRS Instability in Oxide-Based Bipolar Resistive Switching Cells |
| 260 | _ | _ | |a New York, NY |c 2020 |b IEEE |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 520 | _ | _ | |a One of the key challenges in the reliability of valence change [valence change-based memory (VCM)] resistive switching random access memories (ReRAMs) is the short-term instability of the programed state. Due to read noise, program verify or shaping algorithms are ineffective and read current (or resistance) distributions always revert to their intrinsic statistics. In this work, we analyze the instability of the high resistive state (HRS) measured on ZrO 2 -based devices via Factorial Hidden Markov Models. The extracted current jumps are explained by distinct ionic jumps via physics-based kinetic Monte Carlo (KMC) models. The simulation results reveal jumps of oxygen vacancies from the densely packed filament (plug) region to a sparsely packed gap (disc) region as origin of the most critical, large current jumps. These findings are used to extend our compact model (JART v1b) by a read noise module. We demonstrate simulated HRS instability in excellent agreement with our experimental data. Whereas the KMC approach provides a physical understanding of the processes underlying the HRS instability, the compact model enables the simulation of read noise up to industrially relevant array scales. |
| 536 | _ | _ | |a 521 - Controlling Electron Charge-Based Phenomena (POF3-521) |0 G:(DE-HGF)POF3-521 |c POF3-521 |f POF III |x 0 |
| 536 | _ | _ | |a Modelling the Valency Change Memory Effect in Resistive Switching Random Access Memory (RRAM). (jpgi70_20200501) |0 G:(DE-Juel1)jpgi70_20200501 |c jpgi70_20200501 |f Modelling the Valency Change Memory Effect in Resistive Switching Random Access Memory (RRAM). |x 1 |
| 536 | _ | _ | |a BMBF-16ES1134 - Verbundprojekt: Neuro-inspirierte Technologien der künstlichen Intelligenz für die Elektronik der Zukunft - NEUROTEC - (BMBF-16ES1134) |0 G:(DE-82)BMBF-16ES1134 |c BMBF-16ES1134 |x 2 |
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| 588 | _ | _ | |a Dataset connected to CrossRef |
| 700 | 1 | _ | |a Bengel, Christopher |0 0000-0002-2892-9837 |b 1 |
| 700 | 1 | _ | |a Kopperberg, Nils |0 0000-0001-5422-7372 |b 2 |
| 700 | 1 | _ | |a Zhang, Kaihua |0 0000-0001-6358-2202 |b 3 |
| 700 | 1 | _ | |a Waser, Rainer |0 P:(DE-Juel1)131022 |b 4 |
| 700 | 1 | _ | |a Menzel, Stephan |0 P:(DE-Juel1)158062 |b 5 |
| 773 | _ | _ | |a 10.1109/TED.2020.3018096 |g Vol. 67, no. 10, p. 4208 - 4215 |0 PERI:(DE-600)2028088-9 |n 10 |p 4208 - 4215 |t IEEE transactions on electron devices |v 67 |y 2020 |x 1557-9646 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/889691/files/09187543.pdf |y Restricted |
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