Sodium-Controlled Interfacial Resistive Switching in Thin Film Niobium Oxide for Neuromorphic Applications
Source abstract
Abstract
High Resolution Image Download MS PowerPoint Slide A double layer 2-terminal device is employed to show Na-controlled interfacial resistive switching and neuromorphic behavior. The bilayer is based on interfacing biocompatible NaNbO 3 and Nb 2 O 5, which allows the reversible uptake of Na + in the Nb 2 O 5 layer. We demonstrate voltage-controlled interfacial barrier tuning via Na + transfer, enabling conductivity modulation and spike-amplitude- and spike-timing-dependent plasticity. The neuromorphic behavior controlled by Na + ion dynamics in biocompatible materials shows potential for future low-power sensing electronics and smart wearables with local processing.
Source: openalex_inverted_index · Quality: baseline
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
Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS, U.K.
Electrical Engineering Division, Department of Engineering, University of Cambridge, JJ Thomson Avenue, Cambridge CB3 0FA, U.K.
Thin Film Physics Division, Department of Physics, Chemistry and Biology (IFM), Linköping University, Linköping SE-581 83, Sweden
Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
Department of Materials Science and Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
Funding
Engineering and Physical Sciences Research Council · Royal Society · UK Research and Innovation · Henry Royce Institute · Royal Academy of Engineering · Vetenskapsr?det · Leverhulme Trust · University of Cambridge · H2020 European Research Council
References (91)
Show source-provided references
1. 10.1109/MM.2022.316322610.1109/MM.2022.3163226 ↗
2. 10.1038/d41586-018-06610-y10.1038/d41586-018-06610-y ↗
3. 10.1038/s41928-018-0117-x10.1038/s41928-018-0117-x ↗
4. 10.1002/adma.20220335210.1002/adma.202203352 ↗
5. 10.1088/1361-6633/ab8f8610.1088/1361-6633/ab8f86 ↗
6. 10.1002/adma.20190276110.1002/adma.201902761 ↗
7. 10.1063/5.007352810.1063/5.0073528 ↗
8. 10.1063/5.014939310.1063/5.0149393 ↗
9. 10.1016/j.comcom.2022.07.02610.1016/j.comcom.2022.07.026 ↗
10. 10.1088/2634-4386/ac4a8310.1088/2634-4386/ac4a83 ↗
11. 10.1002/adma.20090037510.1002/adma.200900375 ↗
12. 10.1039/D3CS00259D10.1039/D3CS00259D ↗
13. 10.1002/aelm.20210054910.1002/aelm.202100549 ↗
14. 10.1088/2631-7990/acee2e10.1088/2631-7990/acee2e ↗
15. 10.1038/s41467-019-11187-910.1038/s41467-019-11187-9 ↗
16. 10.1021/acsami.6b0491910.1021/acsami.6b04919 ↗
17. 10.1038/srep1375310.1038/srep13753 ↗
18. 10.1126/sciadv.adg194610.1126/sciadv.adg1946 ↗
19. 10.1002/aelm.20210005010.1002/aelm.202100050 ↗
20. 10.1038/srep3953910.1038/srep39539 ↗
21. 10.1016/j.apsusc.2020.14716710.1016/j.apsusc.2020.147167 ↗
22. 10.1002/aelm.20210021910.1002/aelm.202100219 ↗
23. 10.1038/s41467-020-16866-610.1038/s41467-020-16866-6 ↗
24. 10.1021/acsami.9b0022610.1021/acsami.9b00226 ↗
25. 10.1038/nmat485610.1038/nmat4856 ↗
26. 10.1109/LED.2019.289777710.1109/LED.2019.2897777 ↗
27. 10.1002/adma.20160431010.1002/adma.201604310 ↗
28. 10.1002/adma.20210691310.1002/adma.202106913 ↗
29. 10.1088/1361-6528/abaa0e10.1088/1361-6528/abaa0e ↗
30. 10.1113/jphysiol.1949.sp00431010.1113/jphysiol.1949.sp004310 ↗
31. 10.1016/j.brainres.2011.05.03710.1016/j.brainres.2011.05.037 ↗
32. 10.1371/journal.pcbi.100519310.1371/journal.pcbi.1005193 ↗
33. 10.1021/acsnano.0c1004910.1021/acsnano.0c10049 ↗
34. 10.1002/adma.20200301810.1002/adma.202003018 ↗
35. 10.1021/acsnano.1c0467610.1021/acsnano.1c04676 ↗
36. 10.1002/adfm.20220990710.1002/adfm.202209907 ↗
37. 10.3389/fnins.2021.61130010.3389/fnins.2021.611300 ↗
38. 10.1038/s41467-021-23744-210.1038/s41467-021-23744-2 ↗
39. 10.1038/s41928-022-00859-y10.1038/s41928-022-00859-y ↗
40. 10.1021/jacs.7b0314110.1021/jacs.7b03141 ↗
41. 10.1021/jacs.6b0434510.1021/jacs.6b04345 ↗
42. 10.1021/acsami.1c0220710.1021/acsami.1c02207 ↗
43. 10.1016/j.isci.2019.10076710.1016/j.isci.2019.100767 ↗
44. 10.3390/coatings1212187310.3390/coatings12121873 ↗
45. 10.1002/adfm.20180039410.1002/adfm.201800394 ↗
46. 10.1016/j.apsusc.2021.15211410.1016/j.apsusc.2021.152114 ↗
47. 10.1016/j.jallcom.2020.15839410.1016/j.jallcom.2020.158394 ↗
48. 10.1063/5.002050110.1063/5.0020501 ↗
49. 10.1209/0295-5075/116/1700310.1209/0295-5075/116/17003 ↗
50. 10.1021/am502114910.1021/am5021149 ↗
51. 10.1016/j.sse.2012.01.00510.1016/j.sse.2012.01.005 ↗
52. 10.1021/acsami.3c1443110.1021/acsami.3c14431 ↗
53. 10.1021/acsami.0c1954410.1021/acsami.0c19544 ↗
54. 10.1088/1361-6528/ab788910.1088/1361-6528/ab7889 ↗
55. 10.1063/1.494037210.1063/1.4940372 ↗
56. Zaman, A.; Yakopcic, C.; Wang, S.; Shin, E.; Wang, W.; Taha, T. M.; Subramanyam, G. Analysis of Lithium Niobate Memristor Devices for Neuromorphic Programability. 2019 IEEE National Aerospace and Electronics Conference (NAECON); IEEE, 2019; pp 41–45.10.1109/NAECON46414.2019.9058020 ↗
57. 10.1016/j.apsusc.2022.15365310.1016/j.apsusc.2022.153653 ↗
58. 10.1038/s41563-023-01612-210.1038/s41563-023-01612-2 ↗
59. 10.1109/TED.2022.322749810.1109/TED.2022.3227498 ↗
60. 10.1016/j.jeurceramsoc.2019.06.04110.1016/j.jeurceramsoc.2019.06.041 ↗
61. 10.1021/acsnano.5b0593410.1021/acsnano.5b05934 ↗
62. 10.1016/j.ceramint.2022.02.06810.1016/j.ceramint.2022.02.068 ↗
63. 10.1016/j.ensm.2018.08.02210.1016/j.ensm.2018.08.022 ↗
64. 10.1002/adfm.20221497010.1002/adfm.202214970 ↗
65. 10.1107/S056774087500360310.1107/S0567740875003603 ↗
66. 10.1038/s41928-017-0006-810.1038/s41928-017-0006-8 ↗
67. 10.1063/1.512491510.1063/1.5124915 ↗
68. 10.3389/fnins.2021.69095010.3389/fnins.2021.690950 ↗
69. 10.3389/fnins.2016.0033310.3389/fnins.2016.00333 ↗
70. 10.3389/fnins.2019.0059310.3389/fnins.2019.00593 ↗
71. 10.1088/0268-1242/29/10/10400210.1088/0268-1242/29/10/104002 ↗
72. Jin H. · 2018
73. 10.1080/14686996.2023.218371210.1080/14686996.2023.2183712 ↗
74. 10.1002/aelm.20180079510.1002/aelm.201800795 ↗
75. 10.1038/s41586-020-2735-510.1038/s41586-020-2735-5 ↗
76. 10.1038/s41578-022-00434-z10.1038/s41578-022-00434-z ↗
77. 10.1007/s00521-021-06361-410.1007/s00521-021-06361-4 ↗
78. 10.1002/aelm.20210093510.1002/aelm.202100935 ↗
79. 10.1016/0306-4522(83)90010-610.1016/0306-4522(83)90010-6 ↗
80. 10.1364/OE.50400210.1364/OE.504002 ↗
81. 10.1007/s10008005009210.1007/s100080050092 ↗
82. 10.1021/cm00013a02510.1021/cm00013a025 ↗
83. 10.1186/s40580-023-00392-410.1186/s40580-023-00392-4 ↗
84. 10.1016/j.jcis.2019.12.01510.1016/j.jcis.2019.12.015 ↗
85. 10.1002/adfm.20210706010.1002/adfm.202107060 ↗
86. 10.1016/j.jelechem.2006.07.01310.1016/j.jelechem.2006.07.013 ↗
87. 10.5796/electrochemistry.62.5610.5796/electrochemistry.62.56 ↗
88. 10.1016/0167-2738(87)90023-310.1016/0167-2738(87)90023-3 ↗
89. 10.1063/1.171199910.1063/1.1711999 ↗
90. 10.1016/0022-3697(66)90164-810.1016/0022-3697(66)90164-8 ↗
91. 10.1063/1.488980010.1063/1.4889800 ↗