journal article·2026-05

Controllable and Cost‐Efficient Three‐Terminal GaN Nano‐Synapse for Brain‐Inspired Computing

Xiushuo Gu, Zhiyang Liu, Jianya Zhang, Xing Huang, Yukun Zhao, Lifeng Bian

Small· Volume 22· Issue 27
Publisher page

Abstract

ABSTRACT Although the development of highly controllable and low‐cost three‐terminal synaptic nano‐devices is essential for advancing neuromorphic electronics, achieving precise alignment of single nanowire and stable electrical gating still remains severely challenging. Here, we propose and demonstrate a three‐terminal artificial synaptic nano‐device based on the GaN nanowire successfully, enabled by a dielectrophoretic‐assisted assembly strategy that ensures controllable nanowire placement. Benefiting from this cost‐efficient method and with an engineered gate‐coupled interface, the nano‐device exhibits robust and gate‐tunable synaptic plasticity, including short‐/long‐term memory transition, paired‐pulse facilitation, and spike‐timing‐dependent plasticity. By modulating optical spike parameters and gate voltages, the key cognitive behaviors such as learning–forgetting–relearning are effectively emulated, with negative gating significantly accelerating memory reinforcement. They are mainly attributed to the gate‐regulated optoelectronic mechanisms, particularly carrier modulation and oxygen‐vacancy‐induced persistent photoconductivity. Thanks to the excellent regulatory capability of electrical gating, the postsynaptic current of nano‐device can be enhanced over 1,000%. Furthermore, the recognition accuracy can surpass 95% accuracy by gating modulation when integrated into a spiking neural network. This work highlights the promise of three‐terminal nano‐synapses as effective and cost‐efficient building blocks for next‐generation neuromorphic systems.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Neural Networks and Reservoir Computing · Ferroelectric and Negative Capacitance Devices

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

Affiliations

State Key Laboratory of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University Shanghai China

School of Nano‐Tech and Nano‐Bionics University of Science and Technology of China (USTC) Hefei China

Division of Nano‐Devices Research Suzhou Institute of Nano‐Tech and Nano‐Bionics (SINANO) Chinese Academy of Sciences (CAS) Suzhou China

Key Laboratory of Intelligent Optoelectronic Devices and Chips of Jiangsu Higher Education Institutions School of Physical Science and Technology Suzhou University of Science and Technology Suzhou China

School of Petroleum Engineering Xi'an Shiyou University Xi'an Shaanxi China

Guangdong Institute of Semiconductor Micro‐Nano Manufacturing Technology Foshan China

Funding

National Natural Science Foundation of China · Natural Science Foundation of Shanghai Municipality · Basic and Applied Basic Research Foundation of Guangdong Province

References (74)

Show source-provided references
1. 10.1038/s41565‐025‐01984‐310.1038/s41565‐025‐01984‐3 ↗
2. 10.1002/aelm.20240073210.1002/aelm.202400732 ↗
3. 10.1038/s41377‐025‐01773‐610.1038/s41377‐025‐01773‐6 ↗
4. 10.1002/adfm.20250425010.1002/adfm.202504250 ↗
5. 10.1002/adfm.20220909110.1002/adfm.202209091 ↗
6. 10.1038/s41586‐021‐03453‐y10.1038/s41586‐021‐03453‐y ↗
7. 10.1021/acs.nanolett.2c0345310.1021/acs.nanolett.2c03453 ↗
8. 10.1002/adma.20231070410.1002/adma.202310704 ↗
9. 10.1038/s41467‐024‐44723‐310.1038/s41467‐024‐44723‐3 ↗
10. 10.1002/adfm.20231265810.1002/adfm.202312658 ↗
11. 10.1002/adfm.20230213510.1002/adfm.202302135 ↗
12. 10.1038/s43246‐025‐00803‐510.1038/s43246‐025‐00803‐5 ↗
13. 10.1038/s41528‐025‐00459‐810.1038/s41528‐025‐00459‐8 ↗
14. 10.1039/D4MH01625D10.1039/D4MH01625D ↗
15. 10.1016/j.mtnano.2024.10048010.1016/j.mtnano.2024.100480 ↗
16. 10.1002/adfm.20231244410.1002/adfm.202312444 ↗
17. 10.1016/j.nantod.2024.10253410.1016/j.nantod.2024.102534 ↗
18. 10.1002/brx2.7000410.1002/brx2.70004 ↗
19. 10.1002/adma.20221152510.1002/adma.202211525 ↗
20. 10.1021/acsami.4c0343510.1021/acsami.4c03435 ↗
21. 10.1088/1361‐6463/adae1e10.1088/1361‐6463/adae1e ↗
22. 10.1002/adom.20220210510.1002/adom.202202105 ↗
23. 10.1016/S0009‐2614(03)00428‐710.1016/S0009‐2614(03)00428‐7 ↗
24. 10.1016/S0022‐0248(98)00262‐010.1016/S0022‐0248(98)00262‐0 ↗
25. 10.1038/s41928‐021‐00611‐y10.1038/s41928‐021‐00611‐y ↗
26. 10.59717/j.xinn-inform.2026.10002710.59717/j.xinn-inform.2026.100027 ↗
27. 10.1002/EXP.2022016210.1002/EXP.20220162 ↗
28. 10.1016/j.mssp.2023.10734410.1016/j.mssp.2023.107344 ↗
29. 10.1002/adfm.20230603010.1002/adfm.202306030 ↗
30. 10.1002/adfm.20220880710.1002/adfm.202208807 ↗
31. 10.1038/s41565‐020‐0647‐z10.1038/s41565‐020‐0647‐z ↗
32. 10.1038/s41377‐022‐00912‐710.1038/s41377‐022‐00912‐7 ↗
33. 10.1021/acs.nanolett.0c0073310.1021/acs.nanolett.0c00733 ↗
34. 10.1002/adma.20180396110.1002/adma.201803961 ↗
35. 10.1038/ncomms1457910.1038/ncomms14579 ↗
36. 10.1109/ACCESS.2020.301537210.1109/ACCESS.2020.3015372 ↗
37. 10.1039/D2TC04010G10.1039/D2TC04010G ↗
38. 10.1021/acsomega.2c0477510.1021/acsomega.2c04775 ↗
39. 10.1186/s11671‐021‐03539‐610.1186/s11671‐021‐03539‐6 ↗
40. 10.1063/1.313335810.1063/1.3133358 ↗
41. 10.1007/s12274‐023‐6069‐010.1007/s12274‐023‐6069‐0 ↗
42. 10.1364/OL.50975210.1364/OL.509752 ↗
43. 10.1016/j.chip.2025.10014910.1016/j.chip.2025.100149 ↗
44. 10.1016/j.cap.2009.09.00410.1016/j.cap.2009.09.004 ↗
45. 10.1039/D3NA00491K10.1039/D3NA00491K ↗
46. 10.1063/5.015215610.1063/5.0152156 ↗
47. 10.1016/j.neuron.2019.05.04110.1016/j.neuron.2019.05.041 ↗
48. 10.1007/s00339‐023‐06490‐810.1007/s00339‐023‐06490‐8 ↗
49. 10.1039/D2TC02168D10.1039/D2TC02168D ↗
50. 10.1016/j.apsusc.2023.15902210.1016/j.apsusc.2023.159022 ↗
51. 10.1016/j.jksues.2020.07.00810.1016/j.jksues.2020.07.008 ↗
52. 10.1007/s00018‐025‐05893‐510.1007/s00018‐025‐05893‐5 ↗
53. 10.1116/1.58303610.1116/1.583036 ↗
54. 10.1109/TED.2022.316124510.1109/TED.2022.3161245 ↗
55. 10.1088/1674-4926/2405003710.1088/1674-4926/24050037 ↗
56. 10.1002/lpor.20240031910.1002/lpor.202400319 ↗
57. 10.1002/advs.20230251610.1002/advs.202302516 ↗
58. 10.1016/j.scib.2025.05.04410.1016/j.scib.2025.05.044 ↗
59. 10.1002/adma.20180144710.1002/adma.201801447 ↗
60. 10.1038/s41928‐024‐01142‐y10.1038/s41928‐024‐01142‐y ↗
61. 10.1002/smll.20230949910.1002/smll.202309499 ↗
62. 10.1038/s41377‐025‐01792‐310.1038/s41377‐025‐01792‐3 ↗
63. 10.1021/acs.nanolett.1c0027110.1021/acs.nanolett.1c00271 ↗
64. 10.1038/s41467‐022‐34178‐910.1038/s41467‐022‐34178‐9 ↗
65. 10.1021/acsnano.3c1185610.1021/acsnano.3c11856 ↗
66. 10.1002/adfm.20231680210.1002/adfm.202316802 ↗
67. 10.1038/s41928‐025‐01433‐y10.1038/s41928‐025‐01433‐y ↗
68. 10.1002/aisy.20200009910.1002/aisy.202000099 ↗
69. 10.1109/MM.2018.11213035910.1109/MM.2018.112130359 ↗
70. 10.1016/j.chip.2024.10009810.1016/j.chip.2024.100098 ↗
71. 10.1063/5.020300210.1063/5.0203002 ↗
72. 10.1021/acsnano.2c0310010.1021/acsnano.2c03100 ↗
73. 10.1021/acsami.2c1909710.1021/acsami.2c19097 ↗
74. 10.1016/j.neucom.2019.10.10410.1016/j.neucom.2019.10.104 ↗