journal article·2023-03-29Open access

Photoferroelectric All-van-der-Waals Heterostructure for Multimode Neuromorphic Ferroelectric Transistors

Mohamed Soliman, Krishna Maity, Arnaud Gloppe, Aymen Mahmoudi, Abdelkarim Ouerghi, Bernard Doudin, Bohdan Kundys, Jean-Francois Dayen

ACS Applied Materials & Interfaces· Volume 15· Issue 12

Abstract

Interface-driven effects in ferroelectric van der Waals (vdW) heterostructures provide fresh opportunities in the search for alternative device architectures toward overcoming the von Neumann bottleneck. However, their implementation is still in its infancy, mostly by electrical control. It is of utmost interest to develop strategies for additional optical and multistate control in the quest for novel neuromorphic architectures. Here, we demonstrate the electrical and optical control of the ferroelectric polarization states of ferroelectric field effect transistors (FeFET). The FeFETs, fully made of ReS 2 /hBN/CuInP 2 S 6 vdW materials, achieve an on/off ratio exceeding 10 7, a hysteresis memory window up to 7 V wide, and multiple remanent states with a lifetime exceeding 10 3 s. Moreover, the ferroelectric polarization of the CuInP 2 S 6 (CIPS) layer can be controlled by photoexciting the vdW heterostructure. We perform wavelength-dependent studies, which allow for identifying two mechanisms at play in the optical control of the polarization: band-to-band photocarrier generation into the 2D semiconductor ReS 2 and photovoltaic voltage into the 2D ferroelectric CIPS. Finally, heterosynaptic plasticity is demonstrated by operating our FeFET in three different synaptic modes: electrically stimulated, optically stimulated, and optically assisted synapse. Key synaptic functionalities are emulated including electrical long-term plasticity, optoelectrical plasticity, optical potentiation, and spike rate-dependent plasticity. The simulated artificial neural networks demonstrate an excellent accuracy level of 91% close to ideal-model synapses. These results provide a fresh background for future research on photoferroelectric vdW systems and put ferroelectric vdW heterostructures on the roadmap for the next neuromorphic computing architectures.
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

Université de Strasbourg, CNRS, Institut de Physique et Chimie des Matériaux de Strasbourg (IPCMS), UMR 7504, 23 rue du Loess, Strasbourg 67034, France

CNRS, Centre de Nanosciences et de Nanotechnologies, Université Paris-Saclay, 91120 Palaiseau, France

Institut Universitaire de France (IUF), 1 rue Descartes, 75231 cedex 05 Paris, France

Funding

Agence Nationale de la Recherche · H2020 Marie Sklodowska-Curie Actions · Institut Universitaire de France

References (90)

Show source-provided references
1. 10.1038/530398a10.1038/530398a ↗
2. 10.1038/s41565-020-0655-z10.1038/s41565-020-0655-z ↗
3. 10.1038/s41928-017-0006-810.1038/s41928-017-0006-8 ↗
4. 10.1145/216585.21658810.1145/216585.216588 ↗
5. 10.1038/s41928-020-0435-710.1038/s41928-020-0435-7 ↗
6. 10.1109/JPROC.2009.201429810.1109/JPROC.2009.2014298 ↗
7. 10.1002/aisy.20190013610.1002/aisy.201900136 ↗
8. 10.1002/aisy.20200009910.1002/aisy.202000099 ↗
9. 10.1038/s41467-018-07572-510.1038/s41467-018-07572-5 ↗
10. 10.1126/sciadv.aba617310.1126/sciadv.aba6173 ↗
11. 10.1002/smll.20190069510.1002/smll.201900695 ↗
12. 10.1002/adfm.20190370010.1002/adfm.201903700 ↗
13. 10.1063/1.472991510.1063/1.4729915 ↗
14. Mulaosmanovic H. · 2017 · T17610.23919/VLSIT.2017.7998165 ↗
15. 10.1038/ncomms1473610.1038/ncomms14736 ↗
16. 10.1109/TCAD.2018.278972310.1109/TCAD.2018.2789723 ↗
17. 10.1038/s41928-020-00492-710.1038/s41928-020-00492-7 ↗
18. 10.1038/ncomms1080810.1038/ncomms10808 ↗
19. 10.1021/acsnano.9b0768710.1021/acsnano.9b07687 ↗
20. 10.1021/acsnano.2c0103510.1021/acsnano.2c01035 ↗
21. 10.1002/sstr.20200002910.1002/sstr.202000029 ↗
22. 10.1002/adom.20200214610.1002/adom.202002146 ↗
23. 10.1002/aelm.20180070910.1002/aelm.201800709 ↗
24. 10.1038/s41467-020-20660-910.1038/s41467-020-20660-9 ↗
25. 10.1039/D0NR06872A10.1039/D0NR06872A ↗
26. 10.1038/s41566-017-0068-110.1038/s41566-017-0068-1 ↗
27. 10.1002/adma.20170490810.1002/adma.201704908 ↗
28. 10.1021/acsnano.5b0207810.1021/acsnano.5b02078 ↗
29. 10.1038/s41467-018-05640-410.1038/s41467-018-05640-4 ↗
30. 10.1002/adom.20210235310.1002/adom.202102353 ↗
31. 10.1063/5.001955510.1063/5.0019555 ↗
32. 10.1038/s41928-019-0338-710.1038/s41928-019-0338-7 ↗
33. 10.1038/s41928-020-0441-910.1038/s41928-020-0441-9 ↗
34. 10.1002/adma.20200509810.1002/adma.202005098 ↗
35. 10.1002/adma.20200708110.1002/adma.202007081 ↗
36. 10.1002/aelm.20190110710.1002/aelm.201901107 ↗
37. 10.1002/adma.20200562010.1002/adma.202005620 ↗
38. 10.1021/acsnano.2c0728110.1021/acsnano.2c07281 ↗
39. 10.1002/adfm.20200544310.1002/adfm.202005443 ↗
40. 10.1021/acs.chemrev.1c0073510.1021/acs.chemrev.1c00735 ↗
41. 10.1063/1.511217110.1063/1.5112171 ↗
42. 10.1021/acs.nanolett.5b0255910.1021/acs.nanolett.5b02559 ↗
43. 10.1038/s41565-020-0724-310.1038/s41565-020-0724-3 ↗
44. 10.1103/PhysRevApplied.13.06403410.1103/PhysRevApplied.13.064034 ↗
45. 10.1021/acsnano.1c0173510.1021/acsnano.1c01735 ↗
46. 10.1021/acsaelm.1c0049210.1021/acsaelm.1c00492 ↗
47. 10.1021/acsnano.1c0913610.1021/acsnano.1c09136 ↗
48. 10.1038/s41467-021-21320-210.1038/s41467-021-21320-2 ↗
49. Sheffield Eaton, S.; Douglas Butler, M. C. P. Ferroelectric Retention Method. Patent Numer AU2295488A, 1988.
50. 10.1103/PhysRevB.58.911910.1103/PhysRevB.58.9119 ↗
51. 10.1021/acsnano.8b0181010.1021/acsnano.8b01810 ↗
52. 10.1038/ncomms1235710.1038/ncomms12357 ↗
53. 10.1063/1.35191010.1063/1.351910 ↗
54. Chen P.-Y. · 2017
55. 10.1021/acsami.6b1386610.1021/acsami.6b13866 ↗
56. 10.1021/acsami.1c0750510.1021/acsami.1c07505 ↗
57. Jerry M. · 2018 · 6.2.1
58. 10.1073/pnas.110616110810.1073/pnas.1106161108 ↗
59. Milo V. · 2017 · 16.8.1
60. 10.1109/TVLSI.2018.281897810.1109/TVLSI.2018.2818978 ↗
61. 10.1007/s11467-020-0986-010.1007/s11467-020-0986-0 ↗
62. 10.1038/ncomms425210.1038/ncomms4252 ↗
63. 10.1038/s41467-021-26200-310.1038/s41467-021-26200-3 ↗
64. 10.1063/1.318282410.1063/1.3182824 ↗
65. 10.1038/s41563-019-0532-z10.1038/s41563-019-0532-z ↗
66. 10.1021/acsnano.1c0897010.1021/acsnano.1c08970 ↗
67. 10.1103/PhysRevLett.127.13680310.1103/PhysRevLett.127.136803 ↗
68. 10.1088/1674-1056/26/3/03710610.1088/1674-1056/26/3/037106 ↗
69. 10.1063/1.480765810.1063/1.4807658 ↗
70. 10.1038/ncomms146410.1038/ncomms1464 ↗
71. 10.1021/acs.nanolett.0c0130210.1021/acs.nanolett.0c01302 ↗
72. 10.1021/acsphotonics.9b0101510.1021/acsphotonics.9b01015 ↗
73. 10.1002/adfm.20200420610.1002/adfm.202004206 ↗
74. 10.1038/s41928-022-00847-210.1038/s41928-022-00847-2 ↗
75. 10.1038/s41467-022-29182-y10.1038/s41467-022-29182-y ↗
76. 10.1021/acsanm.0c0140810.1021/acsanm.0c01408 ↗
77. 10.1038/s41586-022-05524-010.1038/s41586-022-05524-0 ↗
78. 10.1021/ACS.NANOLETT.2C0428910.1021/ACS.NANOLETT.2C04289 ↗
79. 10.1063/1.496110810.1063/1.4961108 ↗
80. 10.1021/acs.nanolett.7b0158410.1021/acs.nanolett.7b01584 ↗
81. 10.1038/s41699-017-0040-410.1038/s41699-017-0040-4 ↗
82. 10.1002/pi.598010.1002/pi.5980 ↗
83. 10.1002/aelm.20160046010.1002/aelm.201600460 ↗
84. 10.1088/1361-6528/ac189f10.1088/1361-6528/ac189f ↗
85. 10.1002/adma.20180093210.1002/adma.201800932 ↗
86. 10.1038/3606910.1038/36069 ↗
87. 10.1002/adma.20140453110.1002/adma.201404531 ↗
88. 10.1021/acsami.2c0306610.1021/acsami.2c03066 ↗
89. 10.1109/TED.2021.306871610.1109/TED.2021.3068716 ↗
90. 10.1063/1.488609610.1063/1.4886096 ↗