Recent progress in neuromorphic and memory devices based on graphdiyne
Source abstract
Abstract
Graphdiyne (GDY) is an emerging two-dimensional carbon allotrope featuring a direct bandgap and fascinating physical and chemical properties, and it has demonstrated its promising potential in applications of catalysis, energy conversion and storage, electrical/optoelectronic devices, etc. In particular, the recent breakthrough in the synthesis of large-area, high-quality and ultrathin GDY films provides a feasible approach to developing high-performance electrical devices based on GDY. Recently, various GDY-based electrical and optoelectronic devices including multibit optoelectronic memories, ultrafast nonvolatile memories, artificial synapses and memristors have been proposed, in which GDY plays a crucial role. It is essential to summarize the recent breakthrough of GDY in device applications as a guidance, especially considering that the existing GDY-related reviews mainly focus on the applications in catalysis and energy-related fields. Herein, we review GDY-based novel memory and neuromorphic devices and their applications in neuromorphic computing and artificial visual systems. This review will provide an insight into the design and preparation of GDY-based devices and broaden the application fields of GDY.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · 2D Materials and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Nankai University
Tianjin University of Technology
Funding
National Natural Science Foundation of China
References (100+)
Show source-provided references
1. 10.1126/science.124850610.1126/science.1248506 ↗
2. 10.1016/j.inffus.2017.10.00610.1016/j.inffus.2017.10.006 ↗
3. 10.1016/j.ijinfomgt.2014.10.00710.1016/j.ijinfomgt.2014.10.007 ↗
4. 10.1038/nature1357010.1038/nature13570 ↗
5. 10.1016/S1369-7021(06)71539-510.1016/S1369-7021(06)71539-5 ↗
6. 10.1016/j.micpro.2019.01.00910.1016/j.micpro.2019.01.009 ↗
7. 10.1038/s41928-017-0006-810.1038/s41928-017-0006-8 ↗
8. 10.1088/1361-6633/ab8f8610.1088/1361-6633/ab8f86 ↗
9. 10.1109/MSSC.2016.254619910.1109/MSSC.2016.2546199 ↗
10. 10.1038/3502328210.1038/35023282 ↗
11. 10.1038/nnano.2012.24010.1038/nnano.2012.240 ↗
12. 10.1038/nnano.2015.2910.1038/nnano.2015.29 ↗
13. 10.1038/s41565-018-0102-610.1038/s41565-018-0102-6 ↗
14. 10.1038/s41565-021-00921-410.1038/s41565-021-00921-4 ↗
15. 10.1038/s41565-021-00904-510.1038/s41565-021-00904-5 ↗
16. 10.1002/adma.20180019510.1002/adma.201800195 ↗
17. 10.1002/adma.20200301810.1002/adma.202003018 ↗
18. 10.1038/s41586-019-1677-210.1038/s41586-019-1677-2 ↗
19. 10.1126/science.120923610.1126/science.1209236 ↗
20. Bear M, Connors B, Paradiso M. The central visual system. In: Neuroscience: exploring the brain. 3rd ed. Philadelphia (PA): Lippincott Williams & Wilkins; 2007. p. 309–340.
21. 10.1038/nature0301010.1038/nature03010 ↗
22. 10.1021/acs.chemrev.9b0073010.1021/acs.chemrev.9b00730 ↗
23. 10.1002/adma.20170472910.1002/adma.201704729 ↗
24. 10.1063/1.511353610.1063/1.5113536 ↗
25. 10.1063/1.512224910.1063/1.5122249 ↗
26. 10.1063/1.512402710.1063/1.5124027 ↗
27. 10.1016/j.mattod.2017.12.00110.1016/j.mattod.2017.12.001 ↗
28. 10.1002/aisy.20200005510.1002/aisy.202000055 ↗
29. 10.1002/aelm.20180086610.1002/aelm.201800866 ↗
30. 10.1126/science.125464210.1126/science.1254642 ↗
31. 10.1109/MM.2018.11213035910.1109/MM.2018.112130359 ↗
32. 10.1080/14686996.2021.191127710.1080/14686996.2021.1911277 ↗
33. 10.1080/14686996.2020.172539510.1080/14686996.2020.1725395 ↗
34. 10.1038/s41928-018-0023-210.1038/s41928-018-0023-2 ↗
35. 10.1002/adma.20200361010.1002/adma.202003610 ↗
36. 10.1002/sstr.20200002910.1002/sstr.202000029 ↗
37. 10.1002/adfm.20210562510.1002/adfm.202105625 ↗
38. 10.1002/adfm.20190370010.1002/adfm.201903700 ↗
39. Chen Y, Gao Z, Zhang F, et al., editors. Recent progress in self‐powered multifunctional e‐skin for advanced applications. Exploration. 2022;2(1):20210112.
40. Zhang Y, Gao X, Wu Y, et al., editors. Self‐powered technology based on nanogenerators for biomedical applications. Exploration. 2021;1(1):90–114.
41. 10.1080/14686996.2020.175211510.1080/14686996.2020.1752115 ↗
42. 10.1038/s41563-019-0291-x10.1038/s41563-019-0291-x ↗
43. 10.1038/nature0693210.1038/nature06932 ↗
44. 10.1038/s41928-019-0221-610.1038/s41928-019-0221-6 ↗
45. Wang Z, Rao M, Han JW, et al. Capacitive neural network with neuro-transistors. Nat Commun. 2018;9(1):1–10.
46. 10.1038/nmat305410.1038/nmat3054 ↗
47. 10.1038/nnano.2017.8310.1038/nnano.2017.83 ↗
48. 10.1038/s41563-017-0001-510.1038/s41563-017-0001-5 ↗
49. 10.1002/adfm.20110314810.1002/adfm.201103148 ↗
50. 10.1038/nature1444110.1038/nature14441 ↗
51. 10.1002/aelm.20160009010.1002/aelm.201600090 ↗
52. 10.1038/d41586-020-00592-610.1038/d41586-020-00592-6 ↗
53. 10.1038/s41565-019-0501-310.1038/s41565-019-0501-3 ↗
54. 10.1021/acs.nanolett.1c0324010.1021/acs.nanolett.1c03240 ↗
55. 10.1002/adfm.20220127610.1002/adfm.202201276 ↗
56. 10.1002/adfm.20210801410.1002/adfm.202108014 ↗
57. 10.1002/aisy.20220001910.1002/aisy.202200019 ↗
58. 10.1002/advs.20210141710.1002/advs.202101417 ↗
59. 10.1002/adma.20070025110.1002/adma.200700251 ↗
60. 10.1109/TED.2006.87027310.1109/TED.2006.870273 ↗
61. 10.1109/LED.2021.309777710.1109/LED.2021.3097777 ↗
62. 10.1002/adma.20160342810.1002/adma.201603428 ↗
63. 10.1002/smll.20200801710.1002/smll.202008017 ↗
64. 10.1038/s41586-019-1226-z10.1038/s41586-019-1226-z ↗
65. 10.1038/s41586-022-04523-510.1038/s41586-022-04523-5 ↗
66. 10.1038/s41467-021-26230-x10.1038/s41467-021-26230-x ↗
67. 10.1039/b922733d10.1039/b922733d ↗
68. 10.1039/C8CS00773J10.1039/C8CS00773J ↗
69. 10.1021/acs.chemrev.8b0028810.1021/acs.chemrev.8b00288 ↗
70. 10.1016/j.chempr.2020.06.01110.1016/j.chempr.2020.06.011 ↗
71. 10.1039/c3cs60388a10.1039/c3cs60388a ↗
72. 10.1021/acs.accounts.7b0020510.1021/acs.accounts.7b00205 ↗
73. 10.1016/S1872-2067(20)63601-410.1016/S1872-2067(20)63601-4 ↗
74. 10.1007/s12274-021-3456-210.1007/s12274-021-3456-2 ↗
75. 10.1016/j.scib.2021.03.02010.1016/j.scib.2021.03.020 ↗
76. 10.1007/s11426-020-9763-910.1007/s11426-020-9763-9 ↗
77. 10.1038/s41467-018-05878-y10.1038/s41467-018-05878-y ↗
78. 10.1038/s41467-018-03896-410.1038/s41467-018-03896-4 ↗
79. 10.1038/s41467-018-07790-x10.1038/s41467-018-07790-x ↗
80. 10.1038/s41557-018-0100-110.1038/s41557-018-0100-1 ↗
81. 10.1021/jacs.8b1369510.1021/jacs.8b13695 ↗
82. 10.1021/acsami.8b0334510.1021/acsami.8b03345 ↗
83. 10.1007/s40242-021-1344-710.1007/s40242-021-1344-7 ↗
84. 10.1007/s12274-022-4157-110.1007/s12274-022-4157-1 ↗
85. 10.1021/acsami.9b1280110.1021/acsami.9b12801 ↗
86. 10.1021/acsami.8b0094910.1021/acsami.8b00949 ↗
87. 10.1002/smll.20200144010.1002/smll.202001440 ↗
88. 10.1002/adma.20180438610.1002/adma.201804386 ↗
89. 10.1007/s40242-021-1038-110.1007/s40242-021-1038-1 ↗
90. 10.1021/acsami.7b1721910.1021/acsami.7b17219 ↗
91. 10.1021/acsami.8b0311810.1021/acsami.8b03118 ↗
92. 10.1002/adma.20180320210.1002/adma.201803202 ↗
93. 10.1002/adma.20180054810.1002/adma.201800548 ↗
94. 10.1021/jp212181h10.1021/jp212181h ↗
95. 10.1021/nn102472s10.1021/nn102472s ↗
96. 10.1039/c2nr12026g10.1039/c2nr12026g ↗
97. 10.1039/D0RA01777A10.1039/D0RA01777A ↗
98. 10.1016/j.cplett.2015.05.00910.1016/j.cplett.2015.05.009 ↗
99. 10.1126/sciadv.aat637810.1126/sciadv.aat6378 ↗
100. 10.1016/j.chempr.2021.01.02110.1016/j.chempr.2021.01.021 ↗