journal article·2023-08Open access

Reversible Diode with Tunable Band Alignment for Photoelectricity‐Induced Artificial Synapse

Chi Zhang, Jing Ning, Wei Lu, Boyu Wang, Xuan Cui, Xiaoxiao Zhu, Xue Shen, Xin Feng, Yanbo Wang, Dong Wang, Xinran Wang, Jincheng Zhang, Yue Hao

Small· Volume 19· Issue 34

Abstract

Abstract The advent of big data era has put forward higher requirements for electronic nanodevices that have low energy consumption for their application in analog computing with memory and logic circuit to address attendant energy efficiency issues. Here, a miniaturized diode with a reversible switching state based on N‐n MoS2 homojunction used a bandgap renormalization effect through the band alignment type regulated by both dielectric and polarization, controllably switched between type‐I and type‐II, which can be simulated as artificial synapse for sensing memory processing because of its rectification, nonvolatile characteristic and high optical responsiveness. The device demonstrates a rectification ratio of 103. When served as memory retention time, it can attain at least 7000 s. For the synapse simulation, it has an ultralow‐level energy consumption because of the pA‐level operation current with 5 pJ for long‐term potentiation and 7.8 fJ for long‐term depression. Furthermore, the paired pulse facilitation index reaches up to 230%, and it realizes the function of optical storage that can be applied to simulate visual cells.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Semiconductor materials and devices

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

Affiliations

The State Key Discipline Laboratory of Wide Band Gap Semiconductor Technology Xidian University Xi'an 710071 P. R. China

Shaanxi Joint Key Laboratory of Graphene Xidian University Xi'an 710071 P. R. China

Xidian‐Wuhu Research Institute Wuhu 241000 P. R. China

National Laboratory of Solid‐State Microstructures School of Electronic Science and Engineering and Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing 210093 P. R. China

Funding

National Natural Science Foundation of China · Fundamental Research Funds for the Central Universities

References (40)

Show source-provided references
1. M. M.Waldrop The chips are down for Moore's law. Nature 2016 530 144–147 https://doi.org/10.1038/530144a.10.1038/530144a ↗
2. 10.1002/adma.20180622710.1002/adma.201806227 ↗
3. 10.1002/adfm.20210078110.1002/adfm.202100781 ↗
4. 10.1038/nature1067910.1038/nature10679 ↗
5. 10.1038/nature0693210.1038/nature06932 ↗
6. 10.1038/s41928-017-0006-810.1038/s41928-017-0006-8 ↗
7. T.Wan B.Shao S.Ma Y.Zhou Q.Li Y.Chai In‐Sensor Computing: Materials Devices and Integration Technologies. Advanced Materials Portico2022 2203830 https://doi.org/10.1002/adma.202203830.10.1002/adma.202203830 ↗
8. 10.1038/nmat406110.1038/nmat4061 ↗
9. 10.1103/PhysRevB.93.23543510.1103/PhysRevB.93.235435 ↗
10. 10.1103/PhysRevLett.111.21680510.1103/PhysRevLett.111.216805 ↗
11. 10.1038/ncomms1525110.1038/ncomms15251 ↗
12. 10.1103/PhysRevB.97.04140910.1103/PhysRevB.97.041409 ↗
13. 10.1021/acs.nanolett.6b0327610.1021/acs.nanolett.6b03276 ↗
14. 10.1038/srep2918410.1038/srep29184 ↗
15. 10.1038/s41928-019-0207-410.1038/s41928-019-0207-4 ↗
16. 10.1016/j.physe.2022.11536010.1016/j.physe.2022.115360 ↗
17. 10.1038/s41565-017-0022-x10.1038/s41565-017-0022-x ↗
18. 10.1126/science.aab409710.1126/science.aab4097 ↗
19. 10.1021/acsnano.5b0318810.1021/acsnano.5b03188 ↗
20. 10.1038/s41467-020-20314-w10.1038/s41467-020-20314-w ↗
21. 10.1038/s41928-020-00492-710.1038/s41928-020-00492-7 ↗
22. 10.1002/adma.20150477910.1002/adma.201504779 ↗
23. 10.1021/acsnano.2c0427110.1021/acsnano.2c04271 ↗
24. 10.1002/adma.20160431010.1002/adma.201604310 ↗
25. 10.1038/nature2574710.1038/nature25747 ↗
26. 10.1038/s41565-019-0501-310.1038/s41565-019-0501-3 ↗
27. 10.1002/adma.20200870910.1002/adma.202008709 ↗
28. 10.1038/s41467-020-20257-210.1038/s41467-020-20257-2 ↗
29. 10.1038/nnano.2015.5610.1038/nnano.2015.56 ↗
30. Wang H. · Nanoscale · 2020 · 12
31. 10.1038/nnano.2015.2910.1038/nnano.2015.29 ↗
32. 10.1002/adma.20190130010.1002/adma.201901300 ↗
33. 10.1038/s41928-022-00713-110.1038/s41928-022-00713-1 ↗
34. 10.1002/smll.20170093310.1002/smll.201700933 ↗
35. 10.1021/nl503639710.1021/nl5036397 ↗
36. 10.1007/s12274-020-3052-x10.1007/s12274-020-3052-x ↗
37. 10.1038/nnano.2016.17110.1038/nnano.2016.171 ↗
38. 10.1021/acs.nanolett.7b0136510.1021/acs.nanolett.7b01365 ↗
39. 10.1088/2053-1583/aac96b10.1088/2053-1583/aac96b ↗
40. 10.1002/adma.20170328610.1002/adma.201703286 ↗