Modulation of field-like spin orbit torque in heavy metal/ferromagnet heterostructures.


Journal

Nanoscale
ISSN: 2040-3372
Titre abrégé: Nanoscale
Pays: England
ID NLM: 101525249

Informations de publication

Date de publication:
23 Jul 2020
Historique:
pubmed: 10 7 2020
medline: 10 7 2020
entrez: 10 7 2020
Statut: ppublish

Résumé

Spin orbit torque (SOT) has drawn widespread attention in the emerging field of magnetic memory devices, such as magnetic random access memory (MRAM). To promote the performance of SOT-MRAM, most efforts have been devoted to enhance the SOT switching efficiency by improving the damping-like torque. Recently, some studies noted that the field-like torque also plays a crucial role in the nanosecond-timescale SOT dynamics. However, there is not yet an effective way to tune its relative amplitude. Here, we experimentally modulate the field-like SOT in W/CoFeB/MgO trilayers through tuning the interfacial spin accumulation. By performing spin Hall magnetoresistance measurement, we find that the CoFeB with enhanced spin dephasing, either generated from larger layer thickness or from proper annealing, can distinctly boost the spin absorption and enhance the interfacial spin mixing conductance Gr. While the damping-like torque efficiency increases with Gr, the field-like torque efficiency is found to decrease with it. The results suggest that the interfacial spin accumulation, which largely contributes to the field-like torque, is reduced by higher interfacial spin transparency. Our work shows a new path to further improve the performance of SOT-based ultrafast magnetic devices.

Identifiants

pubmed: 32643741
doi: 10.1039/d0nr02762f
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

15246-15251

Auteurs

Zilu Wang (Z)

Fert Beijing Institute, School of Microelectronics, Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, 100191, China. shikewen@buaa.edu.cn weisheng.zhao@buaa.edu.cn and Beihang-Goertek Joint Microelectronics Institute, Qingdao Research Institute, Beihang University, Qingdao, China and Hefei Innovation Research Institute, Beihang University, Hefei 230013, China.

Houyi Cheng (H)

Fert Beijing Institute, School of Microelectronics, Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, 100191, China. shikewen@buaa.edu.cn weisheng.zhao@buaa.edu.cn and Hefei Innovation Research Institute, Beihang University, Hefei 230013, China.

Kewen Shi (K)

Fert Beijing Institute, School of Microelectronics, Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, 100191, China. shikewen@buaa.edu.cn weisheng.zhao@buaa.edu.cn.

Yang Liu (Y)

Fert Beijing Institute, School of Microelectronics, Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, 100191, China. shikewen@buaa.edu.cn weisheng.zhao@buaa.edu.cn.

Junfeng Qiao (J)

Fert Beijing Institute, School of Microelectronics, Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, 100191, China. shikewen@buaa.edu.cn weisheng.zhao@buaa.edu.cn.

Daoqian Zhu (D)

Fert Beijing Institute, School of Microelectronics, Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, 100191, China. shikewen@buaa.edu.cn weisheng.zhao@buaa.edu.cn.

Wenlong Cai (W)

Fert Beijing Institute, School of Microelectronics, Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, 100191, China. shikewen@buaa.edu.cn weisheng.zhao@buaa.edu.cn.

Xueying Zhang (X)

Fert Beijing Institute, School of Microelectronics, Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, 100191, China. shikewen@buaa.edu.cn weisheng.zhao@buaa.edu.cn and Beihang-Goertek Joint Microelectronics Institute, Qingdao Research Institute, Beihang University, Qingdao, China.

Sylvain Eimer (S)

Fert Beijing Institute, School of Microelectronics, Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, 100191, China. shikewen@buaa.edu.cn weisheng.zhao@buaa.edu.cn and Hefei Innovation Research Institute, Beihang University, Hefei 230013, China.

Dapeng Zhu (D)

Fert Beijing Institute, School of Microelectronics, Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, 100191, China. shikewen@buaa.edu.cn weisheng.zhao@buaa.edu.cn and Beihang-Goertek Joint Microelectronics Institute, Qingdao Research Institute, Beihang University, Qingdao, China.

Jie Zhang (J)

Fert Beijing Institute, School of Microelectronics, Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, 100191, China. shikewen@buaa.edu.cn weisheng.zhao@buaa.edu.cn.

Albert Fert (A)

Fert Beijing Institute, School of Microelectronics, Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, 100191, China. shikewen@buaa.edu.cn weisheng.zhao@buaa.edu.cn and Unité Mixte de Physique, CNRS, Thales, University of Paris-Saclay, Palaiseau, France.

Weisheng Zhao (W)

Fert Beijing Institute, School of Microelectronics, Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, 100191, China. shikewen@buaa.edu.cn weisheng.zhao@buaa.edu.cn and Beihang-Goertek Joint Microelectronics Institute, Qingdao Research Institute, Beihang University, Qingdao, China and Hefei Innovation Research Institute, Beihang University, Hefei 230013, China.

Classifications MeSH