Simulation of the resistance switching performance and synaptic behavior of TiO 2 -based RRAM devices with CoFe 2 O 4 insertion layers
Source abstract
Abstract
/TiN device during the reset and set processes are fitted linearly in logarithmic coordinates, and the ohmic conduction mechanism or the space-limited charge conduction mechanism is mainly satisfied in the high and low resistance states. Finally, the application of dual-layer devices on biological synapses is studied, and the basic biological characteristics of enhancement, inhibition and paired pulse promotion are simulated successfully. In addition, the redox reaction induced by oxygen vacancy migration also promotes the formation and rupture of the conductive filament. Results of the study show this ferrite material as an insertion layer in a resistive random-access memory structure that offers potential for future information storage and bioneuromorphic computation devices.
Source: openalex_inverted_index · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Neuroscience and Neural Engineering
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Integrated Circuits, Anhui University, Hefei 230601, China
Funding
University Natural Science Research Project of Anhui Province · National Natural Science Foundation of China
References (32)
Show source-provided references
1. Ambrogio · IEEE Electron Device Lett. · 2016 · 37 · 126810.1109/LED.2016.2600574 ↗
2. Jin · Materials · 2021 · 14 · 627510.3390/ma14216275 ↗
3. Zhang · Materials · 2021 · 14 · 333010.3390/ma14123330 ↗
4. Wu · J. Alloys Compd. · 2019 · 779 · 79410.1016/j.jallcom.2018.11.345 ↗
5. Zhao · Appl. Phys. Lett. · 2021 · 118 · 04210310.1063/5.0036730 ↗
6. Rahmani · Semicond. Sci. Technol. · 2021 · 36 · 09503110.1088/1361-6641/ac18f7 ↗
7. Lee · Semicond. Sci. Technol. · 2021 · 36 · 08500410.1088/1361-6641/ac038e ↗
8. Prakash · Vacuum · 2017 · 143 · 10210.1016/j.vacuum.2017.05.041 ↗
9. Jung · Appl. Phys. Lett. · 2021 · 118 · 11210610.1063/5.0036528 ↗
10. Sun · Nanotechnology · 2019 · 30 · 36570110.1088/1361-6528/ab2507 ↗
11. Kumar · Nanotechnology · 2021 · 32 · 44570410.1088/1361-6528/ac17c4 ↗
12. Das · ACS Appl. Electron. Mater. · 2020 · 2 · 134310.1021/acsaelm.0c00130 ↗
13. Yoon · Appl. Surf. Sci. · 2019 · 478 · 13410.1016/j.apsusc.2019.01.229 ↗
14. Ansh · J. Phys. D: Appl. Phys. · 2022 · 55 · 08510210.1088/1361-6463/ac3281 ↗
15. Matsukatova · Appl. Phys. Lett. · 2020 · 117 · 24350110.1063/5.0030069 ↗
16. Hu · Semicond. Sci. Technol. · 2023 · 38 · 05500310.1088/1361-6641/acc2df ↗
17. Ismail · Curr. Appl. Phys. · 2017 · 17 · 130310.1016/j.cap.2017.06.012 ↗
18. Yang · Appl. Surf. Sci. · 2008 · 254 · 268510.1016/j.apsusc.2007.10.006 ↗
19. Hu · Microelectron. Eng. · 2018 · 189 · 2810.1016/j.mee.2017.12.014 ↗
20. Qi · Semicond. Sci. Technol. · 2022 · 37 · 03501810.1088/1361-6641/ac3cc7 ↗
21. Jian · Jpn. J. Appl. Phys. · 2018 · 57 · 01150110.7567/JJAP.57.011501 ↗
22. Lin · Jpn. J. Appl. Phys. · 2015 · 54 · 04DJ0810.7567/JJAP.54.04DJ08 ↗
23. Kadhim · ACS Appl. Electron. Mater. · 2019 · 1 · 31810.1021/acsaelm.8b00070 ↗
24. Wang · Sci. Rep. · 2015 · 5 · 1015010.1038/srep10150 ↗
25. Jin · Appl. Surf. Sci. · 2012 · 263 · 67810.1016/j.apsusc.2012.09.135 ↗
26. Hu · Appl. Phys. Lett. · 2014 · 104 · 14350210.1063/1.4870627 ↗
27. Jabeen · Mater. Res. Express · 2017 · 4 · 05640110.1088/2053-1591/aa6dec ↗
28. Wu · Nanoscale Res. Lett. · 2019 · 14 · 17710.1186/s11671-019-3015-x ↗
29. Wu · Nanomaterials · 2020 · 10 · 45710.3390/nano10030457 ↗
30. Lin · Electronics · 2021 · 10 · 73110.3390/electronics10060731 ↗
31. Mahata · Appl. Phys. Lett. · 2021 · 119 · 22160110.1063/5.0068090 ↗
32. Liu · Adv. Electron. Mater. · 2020 · 6 · 190101210.1002/aelm.201901012 ↗