Conduction channel configuration controlled digital and analog response in TiO2-based inorganic memristive artificial synapses
Source abstract
Abstract
The operating current regime is found to play a key role in determining the synaptic characteristic of memristor devices. A conduction channel that is formed using high current compliance prior to the synaptic operation results in digital behavior; the high current stimulus forms a complete conductive filament connecting the cathode and anode, and the high electric field promotes abrupt redox reactions during potentiation and depression pulsing schemes. Conversely, the conduction can be reconfigured to produce a filamentary-homogeneous hybrid channel by utilizing the low current stimulus, and this configuration enables the occurrence of analog behavior. The capabilities of memristors showing programmable digital-to-analog or analog-to-digital transformation open a wide range of applications in electronics. We propose a conduction mechanism to explain this phenomenon.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Neuroscience and Neural Engineering · Photoreceptor and optogenetics research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Centre for Electronics Frontiers, University of Southampton 1 , Southampton SO171BJ, United Kingdom
Institute of Electronics, National Yang Ming Chiao Tung University 2 , Hsinchu 30010, Taiwan
Department of Materials Science and Engineering, National Yang Ming Chiao Tung University 3 , Hsinchu 30010, Taiwan
Funding
Ministry of Science and Technology, Taiwan · Engineering and Physical Sciences Research Council · H2020 · European Commission Horizon 2020 Programme Marie Skłodowska-Curie actions-MSCA-IF-EF-ST MENESIS Project
References (33)
Show source-provided references
1. Nat. Electron. · 2018 · 1 · 2210.1038/s41928-017-0006-8 ↗
2. Nat. Electron. · 2018 · 1 · 44210.1038/s41928-018-0117-x ↗
3. Sci. Rep. · 2016 · 6 · 3261410.1038/srep32614 ↗
4. Sci. Rep. · 2020 · 10 · 259010.1038/s41598-020-58831-9 ↗
5. Front. Neurosci. · 2017 · 11 · 7010.3389/fnins.2017.00070 ↗
6. RSC Adv. · 2016 · 6 · 05666110.1039/c6ra10503c ↗
7. Adv. Funct. Mater. · 2011 · 21 · 97910.1002/adfm.201001884 ↗
8. Adv. Mater. · 2009 · 21 · 263210.1002/adma.200900375 ↗
9. Nat. Mater. · 2007 · 6 · 83310.1038/nmat2023 ↗
10. Nat. Nanotechnol. · 2010 · 5 · 14810.1038/nnano.2009.456 ↗
11. IEEE Trans. Electron Devices · 2019 · 66 · 472210.1109/ted.2019.2941764 ↗
12. Nat. Mater. · 2019 · 18 · 30910.1038/s41563-019-0291-x ↗
13. Proc. IEEE · 2018 · 106 · 26010.1109/jproc.2018.2790840 ↗
14. APL Mater. · 2019 · 7 · 05110810.1063/1.5092991 ↗
15. Nanotechnology · 2019 · 30 · 44520510.1088/1361-6528/ab3480 ↗
16. Phys. Status Solidi · 2018 · 215 · 170044010.1002/pssa.201700440 ↗
17. Nanotechnology · 2020 · 31 · 26LT0110.1088/1361-6528/ab7fcf ↗
18. Sci. Rep. · 2015 · 5 · 01596510.1038/srep15965 ↗
19. Appl. Phys. Rev. · 2020 · 7 · 01130110.1063/1.5124915 ↗
20. Solid State Commun. · 2011 · 151 · 173910.1016/j.ssc.2011.08.036 ↗
21. Jpn. J. Appl. Phys., Part 1 · 2015 · 54 · 06FH1110.7567/jjap.54.06fh11 ↗
22. J. Mater. Chem. C · 2019 · 7 · 72510.1039/c8tc04538k ↗
23. Appl. Phys. Lett. · 2016 · 108 · 01350610.1063/1.4939443 ↗
24. Sci. Rep. · 2015 · 5 · 784410.1038/srep07844 ↗
25. Electronics · 2015 · 4 · 58610.3390/electronics4030586 ↗
26. J. Appl. Phys. · 1977 · 48 · 472910.1063/1.323539 ↗
27. Appl. Surf. Sci. · 2017 · 422 · 50410.1016/j.apsusc.2017.06.062 ↗
28. Microelectron. Eng. · 2010 · 87 · 180510.1016/j.mee.2009.10.023 ↗
29. ACS Appl. Electron. Mater. · 2019 · 1 · 218410.1021/acsaelm.9b00617 ↗
30. Sci. Rep. · 2017 · 7 · 206610.1038/s41598-017-01354-7 ↗
31. Proc. IEEE · 2012 · 100 · 191110.1109/jproc.2012.2190812 ↗
32. Int. J. Circuit Theory Appl. · 2018 · 46 · 11310.1002/cta.2345 ↗
33. IEEE Electron Device Lett. · 2011 · 32 · 111610.1109/led.2011.2156377 ↗