Effective electrical manipulation of a topological antiferromagnet by orbital torques

Zhenyi Zheng, Tao Zeng, Tieyang Zhao, Shu Shi, Lizhu Ren, Tongtong Zhang, Lanxin Jia, Youdi Gu, Rui Xiao, Hengan Zhou, Qihan Zhang, Jiaqi Lu, Guilei Wang, Chao Zhao, Huihui Li (), Beng Kang Tay () and Jingsheng Chen ()
Additional contact information
Zhenyi Zheng: National University of Singapore
Tao Zeng: National University of Singapore
Tieyang Zhao: National University of Singapore
Shu Shi: National University of Singapore
Lizhu Ren: National University of Singapore
Tongtong Zhang: Nanyang Technological University
Lanxin Jia: National University of Singapore
Youdi Gu: National University of Singapore
Rui Xiao: National University of Singapore
Hengan Zhou: National University of Singapore
Qihan Zhang: National University of Singapore
Jiaqi Lu: National University of Singapore
Guilei Wang: Beijing Superstring Academy of Memory Technology
Chao Zhao: Beijing Superstring Academy of Memory Technology
Huihui Li: Beijing Superstring Academy of Memory Technology
Beng Kang Tay: Nanyang Technological University
Jingsheng Chen: National University of Singapore

Nature Communications, 2024, vol. 15, issue 1, 1-8

Abstract: Abstract The electrical control of the non-trivial topology in Weyl antiferromagnets is of great interest for the development of next-generation spintronic devices. Recent studies suggest that the spin Hall effect can switch the topological antiferromagnetic order. However, the switching efficiency remains relatively low. Here, we demonstrate the effective manipulation of antiferromagnetic order in the Weyl semimetal Mn3Sn using orbital torques originating from either metal Mn or oxide CuOx. Although Mn3Sn can convert orbital current to spin current on its own, we find that inserting a heavy metal layer, such as Pt, of appropriate thickness can effectively reduce the critical switching current density by one order of magnitude. In addition, we show that the memristor-like switching behaviour of Mn3Sn can mimic the potentiation and depression processes of a synapse with high linearity—which may be beneficial for constructing accurate artificial neural networks. Our work paves a way for manipulating the topological antiferromagnetic order and may inspire more high-performance antiferromagnetic functional devices.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.nature.com/articles/s41467-024-45109-1 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-45109-1

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-024-45109-1

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().