journal article·2022-04-26

Programmable Spin–Orbit Torque Multistate Memory and Spin Logic Cell

Yibo Fan, Xiang Han, Xiaonan Zhao, Yanan Dong, Yanxue Chen, Lihui Bai, Shishen Yan, Yufeng Tian

ACS Nano· Volume 16· Issue 4
Publisher page

Abstract

Controllable spin-orbit torque based nonvolatile memory is highly desired for constructing energy efficient reconfigurable logic-in-memory computing suitable for emerging data-intensive applications. Here, we report our exploration of the IrMn/Co/Ru/CoPt/CoO heterojunction as a potential candidate for applications in both multistate memory and programmable spin logic. The studied heterojunction can be programmed into four different magnetic configurations at will by tuning both the in-plane exchange bias at the interface of IrMn and Co layers and the out-of-plane exchange bias at the interface of CoPt and CoO layers. Moreover, on the basis of the controllable exchange bias effect, 10 states of nonvolatile memory and multiple logic-in-memory functions have been demonstrated. Our findings indicate that IrMn/Co/Ru/CoPt/CoO multilayered structures can be used as a building block for next-generation logic-in-memory and multifunctional multidimensional spintronic devices.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Magnetic properties of thin films

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

Affiliations

School of Physics, State Key Laboratory of Crystal Materials, Shandong University, Jinan 250100, China

Spintronics Institute, University of Jinan, Jinan 250022, China

Funding

Government of Shandong Province · National Natural Science Foundation of China · Higher Education Discipline Innovation Project

References (41)

Show source-provided references
1. 10.1038/s41928-018-0092-210.1038/s41928-018-0092-2 ↗
2. 10.1109/T-C.1969.22275410.1109/T-C.1969.222754 ↗
3. 10.1038/s41563-019-0291-x10.1038/s41563-019-0291-x ↗
4. 10.1038/s41586-020-2861-010.1038/s41586-020-2861-0 ↗
5. 10.1126/science.122156110.1126/science.1221561 ↗
6. 10.1038/nmat202310.1038/nmat2023 ↗
7. 10.1016/j.mattod.2017.07.00710.1016/j.mattod.2017.07.007 ↗
8. 10.1109/TED.2011.217841610.1109/TED.2011.2178416 ↗
9. 10.1109/TMAG.2021.307858310.1109/TMAG.2021.3078583 ↗
10. 10.1021/acsami.0c1018410.1021/acsami.0c10184 ↗
11. 10.1103/PhysRevLett.109.09660210.1103/PhysRevLett.109.096602 ↗
12. 10.1038/nature1030910.1038/nature10309 ↗
13. 10.1038/nmat261310.1038/nmat2613 ↗
14. 10.1002/adma.20190714810.1002/adma.201907148 ↗
15. 10.1038/nnano.2014.32410.1038/nnano.2014.324 ↗
16. 10.1126/sciadv.aau669610.1126/sciadv.aau6696 ↗
17. 10.1038/nnano.2016.8410.1038/nnano.2016.84 ↗
18. 10.1038/ncomms1085410.1038/ncomms10854 ↗
19. 10.1038/nnano.2016.10910.1038/nnano.2016.109 ↗
20. 10.1038/nnano.2014.9410.1038/nnano.2014.94 ↗
21. 10.1038/s41928-018-0160-710.1038/s41928-018-0160-7 ↗
22. 10.1002/adma.20190792910.1002/adma.201907929 ↗
23. 10.1021/acs.nanolett.0c0064710.1021/acs.nanolett.0c00647 ↗
24. 10.1038/s41928-018-0099-810.1038/s41928-018-0099-8 ↗
25. 10.1002/aelm.20200029610.1002/aelm.202000296 ↗
26. 10.1002/adma.20180131810.1002/adma.201801318 ↗
27. 10.1002/aelm.20160028210.1002/aelm.201600282 ↗
28. 10.1021/acs.nanolett.7b0472210.1021/acs.nanolett.7b04722 ↗
29. 10.1002/adfm.20210535910.1002/adfm.202105359 ↗
30. 10.1002/aelm.20190109010.1002/aelm.201901090 ↗
31. 10.1103/PhysRevLett.87.08720210.1103/PhysRevLett.87.087202 ↗
32. 10.1038/s41467-021-22819-410.1038/s41467-021-22819-4 ↗
33. 10.1063/1.323221310.1063/1.3232213 ↗
34. 10.1209/0295-5075/114/1700810.1209/0295-5075/114/17008 ↗
35. 10.1002/adma.20050054410.1002/adma.200500544 ↗
36. 10.1063/1.487171110.1063/1.4871711 ↗
37. 10.1103/PhysRevApplied.13.01405910.1103/PhysRevApplied.13.014059 ↗
38. 10.1002/adfm.20190909210.1002/adfm.201909092 ↗
39. 10.1063/5.004108110.1063/5.0041081 ↗
40. 10.1038/nature0201410.1038/nature02014 ↗
41. 10.1109/JPROC.2016.257830310.1109/JPROC.2016.2578303 ↗