Solution-Processed Multiterminal Artificial Synapses Based on Ion-Doped Solid Electrolytes
Source abstract
Abstract
Brain-inspired neuromorphic computing is a revolutionary technology to create an intelligent and energy-efficient computing system. However, neuromorphic devices fabricated with complementary metal-oxide-semiconductor technology have a few drawbacks such as high energy consumption and circuit complexity. Also, such devices have different mechanisms compared to biological synapses, which transmit signals using ion dynamics. Here, we propose a three-terminal artificial synapse based on ion movement. The synapse uses solution-processed reduced graphene oxide (rGO) and ion-doped solid polymer electrolyte. The rGO-based artificial synapse shows synaptic behaviors including excitatory postsynaptic current and paired-pulse facilitation as short-term plasticity. The artificial synapse emulates the transition characteristics of a biological synapse from short-term to long-term plasticity depending on the amplitudes of the applied bias pulses. These results demonstrate the feasibility of using rGO and ion-doped solid electrolyte in construction of 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, Pohang University of Science and Technology (POSTECH), Pohang 37673, Korea
Funding
National Research Foundation of Korea
References (74)
Show source-provided references
1. 10.1038/s41928-017-0006-810.1038/s41928-017-0006-8 ↗
2. 10.1126/science.125464210.1126/science.1254642 ↗
3. 10.1088/0957-4484/24/38/38200110.1088/0957-4484/24/38/382001 ↗
4. 10.1109/MSPEC.2017.793422810.1109/MSPEC.2017.7934228 ↗
5. 10.1126/science.120923610.1126/science.1209236 ↗
6. 10.1021/nl203687n10.1021/nl203687n ↗
7. 10.1038/nature1444110.1038/nature14441 ↗
8. 10.1002/adma.20160431010.1002/adma.201604310 ↗
9. 10.1021/acsnano.7b0303310.1021/acsnano.7b03033 ↗
10. 10.1002/adma.20150636310.1002/adma.201506363 ↗
11. 10.1021/acsnano.7b0011310.1021/acsnano.7b00113 ↗
12. 10.1038/nmat485610.1038/nmat4856 ↗
13. 10.1002/adfm.20160444710.1002/adfm.201604447 ↗
14. 10.1038/ncomms415810.1038/ncomms4158 ↗
15. 10.1002/adfm.20170692710.1002/adfm.201706927 ↗
16. 10.1016/j.mser.2014.06.00210.1016/j.mser.2014.06.002 ↗
17. 10.1021/nn503464q10.1021/nn503464q ↗
18. 10.1021/nn501824r10.1021/nn501824r ↗
19. 10.1002/adma.20170591410.1002/adma.201705914 ↗
20. 10.1021/acsnano.7b0833110.1021/acsnano.7b08331 ↗
21. 10.1038/s41563-017-0001-510.1038/s41563-017-0001-5 ↗
22. 10.1021/acsnano.7b0334710.1021/acsnano.7b03347 ↗
23. 10.1039/C9NR02767J10.1039/C9NR02767J ↗
24. 10.1109/JPROC.2018.279084010.1109/JPROC.2018.2790840 ↗
25. 10.1088/0957-4484/27/36/36520410.1088/0957-4484/27/36/365204 ↗
26. 10.1002/adma.20170090610.1002/adma.201700906 ↗
27. 10.1016/j.orgel.2015.02.02110.1016/j.orgel.2015.02.021 ↗
28. 10.1063/1.493855310.1063/1.4938553 ↗
29. 10.1038/nature2574710.1038/nature25747 ↗
30. 10.1002/adma.20180019510.1002/adma.201800195 ↗
31. 10.1039/C9NR03073E10.1039/C9NR03073E ↗
32. 10.1021/acs.nanolett.9b0018010.1021/acs.nanolett.9b00180 ↗
33. 10.1038/ncomms367610.1038/ncomms3676 ↗
34. 10.1021/acsami.6b1374610.1021/acsami.6b13746 ↗
35. 10.1002/adma.20180235310.1002/adma.201802353 ↗
36. 10.1002/adma.20190037910.1002/adma.201900379 ↗
37. 10.1002/adfm.20190270210.1002/adfm.201902702 ↗
38. 10.1038/nature1145810.1038/nature11458 ↗
39. 10.1088/0022-3727/44/31/31300110.1088/0022-3727/44/31/313001 ↗
40. 10.1021/cr900070d10.1021/cr900070d ↗
41. 10.1021/acs.nanolett.5b0328310.1021/acs.nanolett.5b03283 ↗
42. 10.1039/C7NR03106H10.1039/C7NR03106H ↗
43. 10.1007/s12274-010-0035-310.1007/s12274-010-0035-3 ↗
44. 10.1021/nl803536710.1021/nl8035367 ↗
45. 10.1021/nl903161710.1021/nl9031617 ↗
46. 10.1021/nn100780v10.1021/nn100780v ↗
47. 10.1038/nnano.2008.8310.1038/nnano.2008.83 ↗
48. 10.1021/nl071771510.1021/nl0717715 ↗
49. 10.1016/j.carbon.2011.11.01010.1016/j.carbon.2011.11.010 ↗
50. 10.1021/nn101550610.1021/nn1015506 ↗
51. 10.1021/cm902182y10.1021/cm902182y ↗
52. 10.1038/srep2171510.1038/srep21715 ↗
53. 10.1126/science.106702010.1126/science.1067020 ↗
54. 10.1002/adfm.20110198910.1002/adfm.201101989 ↗
55. 10.1016/j.matchemphys.2017.03.04810.1016/j.matchemphys.2017.03.048 ↗
56. 10.1039/C6NR07616E10.1039/C6NR07616E ↗
57. 10.1002/smll.20170119310.1002/smll.201701193 ↗
58. 10.1063/1.480437410.1063/1.4804374 ↗
59. 10.1146/annurev.physiol.64.092501.11454710.1146/annurev.physiol.64.092501.114547 ↗
60. 10.1038/nmat305410.1038/nmat3054 ↗
61. 10.1021/nn202983n10.1021/nn202983n ↗
62. 10.1007/s00422-004-0523-110.1007/s00422-004-0523-1 ↗
63. 10.1021/acsami.6b0886610.1021/acsami.6b08866 ↗
64. 10.1063/1.497706910.1063/1.4977069 ↗
65. 10.1038/nature0301010.1038/nature03010 ↗
66. 10.1038/nrn255810.1038/nrn2558 ↗
67. 10.1002/adma.20120311610.1002/adma.201203116 ↗
68. 10.1002/adma.20100028210.1002/adma.201000282 ↗
69. 10.1002/adma.20180154810.1002/adma.201801548 ↗
70. 10.1080/0001873810010136710.1080/00018738100101367 ↗
71. 10.1021/la990402o10.1021/la990402o ↗
72. 10.1016/S1388-2481(98)00005-810.1016/S1388-2481(98)00005-8 ↗
73. 10.1002/cnma.20160010710.1002/cnma.201600107 ↗
74. 10.1007/s11356-013-1499-y10.1007/s11356-013-1499-y ↗