journal article·2023-06Open access

Effect of Training Pulse Parameters on the Synaptic Plasticity of a ZrO2(Y)‐Based Memristive Device

Maria N. Koryazhkina, Margarita A. Ryabova, Evgeniya V. Okulich, Alexey I. Belov, Ivan N. Antonov, Maria E. Shenina, Sergey A. Shchanikov, Alexey N. Mikhaylov, Dmitrii O. Filatov, Davide Valenti, Bernardo Spagnolo

physica status solidi (a)· Volume 220· Issue 11

Abstract

Herein, the effect of training pulse parameters on the synaptic plasticity of a ZrO2(Y)‐based memristive device has been investigated. It is shown that the potentiation and depression significantly depend on the amplitude and shape of the training pulses. The most stable synaptic plasticity is observed when considering training pulses with rectangular shape and maximum amplitude value. In contrast, there is a rather weak dependence of the potentiation and depression on the number of pulses in trains. The observed effect can be explained in terms of the work required to change the resistive state. Moreover, a ZrO2(Y)‐based memristive device exhibits distinguishable potentiation and depression for at least 1000 cycles.
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Research context

OpenAlex topics: Advanced Memory and Neural Computing · Neuroscience and Neural Engineering · Neural dynamics and brain function

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Research and Educational Center for Physics of Solid State Nanostructures Lobachevsky State University of Nizhny Novgorod 23 Gagarin Avenue Nizhny Novgorod 603022 Russia

Dipartimento di Fisica e Chimica “Emilio Segrè” Group of Interdisciplinary Theoretical Physics Università degli Studi di Palermo Viale delle Scienze Edificio 18 I-90128 Palermo Italy

References (30)

Show source-provided references
1. 10.1038/srep3527310.1038/srep35273 ↗
2. 10.1038/nmat485610.1038/nmat4856 ↗
3. 10.1016/j.chaos.2021.11089010.1016/j.chaos.2021.110890 ↗
4. 10.1063/1.509806610.1063/1.5098066 ↗
5. 10.1088/1742-5468/ab570410.1088/1742-5468/ab5704 ↗
6. 10.1088/1742-5468/ab684a10.1088/1742-5468/ab684a ↗
7. 10.1016/j.chaos.2021.11072310.1016/j.chaos.2021.110723 ↗
8. 10.1063/1.511898010.1063/1.5118980 ↗
9. 10.1103/PhysRevE.81.04191110.1103/PhysRevE.81.041911 ↗
10. 10.1103/PhysRevLett.107.10810310.1103/PhysRevLett.107.108103 ↗
11. 10.3390/ijms2202077310.3390/ijms22020773 ↗
12. 10.3389/fnins.2011.0002610.3389/fnins.2011.00026 ↗
13. 10.1021/nl201040y10.1021/nl201040y ↗
14. 10.1515/ntrev-2018-004510.1515/ntrev-2018-0045 ↗
15. 10.1021/nl904092h10.1021/nl904092h ↗
16. 10.1038/s41699-020-00190-010.1038/s41699-020-00190-0 ↗
17. 10.1038/srep1015010.1038/srep10150 ↗
18. 10.1021/acsami.9b1716010.1021/acsami.9b17160 ↗
19. 10.1039/C8TC04903C10.1039/C8TC04903C ↗
20. 10.1016/j.apsusc.2020.14710710.1016/j.apsusc.2020.147107 ↗
21. 10.1016/j.chaos.2022.11245910.1016/j.chaos.2022.112459 ↗
22. 10.1002/pssc.20160008310.1002/pssc.201600083 ↗
23. 10.1016/j.mee.2019.11098810.1016/j.mee.2019.110988 ↗
24. 10.1016/j.chaos.2021.11089010.1016/j.chaos.2021.110890 ↗
25. 10.1002/admt.20190060710.1002/admt.201900607 ↗
26. 10.1155/2018/202849110.1155/2018/2028491 ↗
27. 10.1088/2053-1591/aa6dec10.1088/2053-1591/aa6dec ↗
28. 10.1186/s11671-022-03699-z10.1186/s11671-022-03699-z ↗
29. 10.1088/1742-6596/741/1/01217410.1088/1742-6596/741/1/012174 ↗
30. 10.1103/PhysRevApplied.11.04407810.1103/PhysRevApplied.11.044078 ↗