Inorganic p-Type Tellurium-Based Synaptic Transistors: Complementary Synaptic Pairs with n-Type Devices for Energy-Efficient Operation
Source abstract
Abstract
Neuromorphic computing is a rapidly emerging technology that can overcome the limitations of von Neumann-type architecture-based computing systems, offering the potential for implementing next-generation computing architectures. Here, we propose a p-type three-terminal synaptic device that successfully mimics the function of biological synapses. The proposed tellurium (Te) synaptic transistors incorporating SiO 2 or Al 2 O 3 gate dielectric layers modulate the synaptic weight─that is, the channel conductance─essential for realizing synaptic characteristics. Synaptic devices with optimal Al 2 O 3 layers exhibit large hysteresis properties that efficiently induce conductance modulation, demonstrating low power consumption, good linearity, and short-/long-term plasticity. Furthermore, the proposed optimal Te synaptic transistor achieved a high recognition accuracy of 93.8%. These findings suggest that Te-based synaptic devices fabricated utilizing thin-film processes could enhance the efficiency of future neuromorphic computing systems.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Photoreceptor and optogenetics research · Neuroscience and Neural Engineering
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Materials Science and Engineering, Chungnam National University, Daejeon 34134, Republic of Korea
Department of Energy and Materials Engineering, Dongguk University, Seoul 04620, Republic of Korea
Department of Electrical and Computer Engineering, Inha University, Incheon 22212, Republic of Korea
Division of Materials Science and Engineering, Hanyang University, Seoul 04763, Republic of Korea
Funding
National Research Foundation of Korea · Dongguk University · Chungnam National University
References (47)
Show source-provided references
1. 10.1109/TVLSI.2022.316184710.1109/TVLSI.2022.3161847 ↗
2. 10.1007/s11432-020-3227-110.1007/s11432-020-3227-1 ↗
3. 10.1088/1741-2560/13/5/05100110.1088/1741-2560/13/5/051001 ↗
4. 10.1109/5.5835610.1109/5.58356 ↗
5. 10.1038/s43588-021-00184-y10.1038/s43588-021-00184-y ↗
6. 10.1166/jnn.2016.1223410.1166/jnn.2016.12234 ↗
7. 10.1002/adfm.20190370010.1002/adfm.201903700 ↗
8. 10.1126/sciadv.abm853710.1126/sciadv.abm8537 ↗
9. 10.1088/1361-6463/aade3f10.1088/1361-6463/aade3f ↗
10. 10.1038/nature1444110.1038/nature14441 ↗
11. 10.1002/smsc.20210004910.1002/smsc.202100049 ↗
12. 10.1021/acsami.1c1936410.1021/acsami.1c19364 ↗
13. 10.1002/adma.20180019510.1002/adma.201800195 ↗
14. 10.1002/aelm.20210033610.1002/aelm.202100336 ↗
15. 10.1002/smll.20190069510.1002/smll.201900695 ↗
16. 10.1021/acsami.6b1374610.1021/acsami.6b13746 ↗
17. 10.1002/adfm.20220996910.1002/adfm.202209969 ↗
18. 10.1088/2752-5724/acc67810.1088/2752-5724/acc678 ↗
19. 10.1088/2631-7990/acee2e10.1088/2631-7990/acee2e ↗
20. 10.1021/acsami.3c0916210.1021/acsami.3c09162 ↗
21. 10.1002/aelm.20220130610.1002/aelm.202201306 ↗
22. 10.1021/acs.chemmater.3c0241710.1021/acs.chemmater.3c02417 ↗
23. 10.1002/pssr.20230048710.1002/pssr.202300487 ↗
24. 10.1016/j.mattod.2023.02.00310.1016/j.mattod.2023.02.003 ↗
25. 10.1016/j.device.2023.10006910.1016/j.device.2023.100069 ↗
26. 10.1038/s41565-019-0585-910.1038/s41565-019-0585-9 ↗
27. 10.3390/nano1012232610.3390/nano10122326 ↗
28. 10.1021/acsaelm.8b0006010.1021/acsaelm.8b00060 ↗
29. 10.1038/srep0528410.1038/srep05284 ↗
30. 10.1021/acsnano.7b0011310.1021/acsnano.7b00113 ↗
31. 10.1109/TED.2014.232308510.1109/TED.2014.2323085 ↗
32. 10.1016/j.microrel.2003.12.00510.1016/j.microrel.2003.12.005 ↗
33. 10.1007/s11051-022-05512-510.1007/s11051-022-05512-5 ↗
34. 10.1038/s41928-018-0058-410.1038/s41928-018-0058-4 ↗
35. 10.1021/acsnano.8b0383110.1021/acsnano.8b03831 ↗
36. 10.1038/s41467-024-44884-110.1038/s41467-024-44884-1 ↗
37. 10.1002/adma.20231165210.1002/adma.202311652 ↗
38. 10.1016/j.apmt.2024.10210310.1016/j.apmt.2024.102103 ↗
39. 10.3390/nano1107177310.3390/nano11071773 ↗
40. 10.1109/TCAD.2024.335822010.1109/TCAD.2024.3358220 ↗
41. 10.1038/s41598-022-07505-910.1038/s41598-022-07505-9 ↗
42. 10.1039/D0TC05738J10.1039/D0TC05738J ↗
43. 10.1021/acsami.9b2292510.1021/acsami.9b22925 ↗
44. 10.1021/acsami.0c2227110.1021/acsami.0c22271 ↗
45. 10.1002/aelm.20220015510.1002/aelm.202200155 ↗
46. 10.1021/acsami.1c0548410.1021/acsami.1c05484 ↗
47. 10.1021/acsami.3c0025410.1021/acsami.3c00254 ↗