PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 15, 2024ACS Nano3 citations

Spin–Orbit Torque Vector Quantification in Nanoscale Magnetic Tunnel Junctions

View Full Paper
KSKiran Kumar Vudya SethuFYFarrukh YasinJSJohan Swerts

Key Points

Key points are not available for this paper at this time.

Abstract

Spin–orbit torques (SOT) allow ultrafast, energy-efficient toggling of magnetization state by an in-plane charge current for applications such as magnetic random-access memory (SOT-MRAM). Tailoring the SOT vector comprising of antidamping (TAD) and fieldlike (TFL) torques could lead to faster, more reliable, and low-power SOT-MRAM. Here, we establish a method to quantify the longitudinal (TAD) and transverse (TFL) components of the SOT vector and its efficiency χAD and χFL, respectively, in nanoscale three-terminal SOT magnetic tunnel junctions (SOT-MTJ). Modulation of nucleation or switching field (BSF) for magnetization reversal by SOT effective fields (BSOT) leads to the modification of SOT-MTJ hysteresis loop behavior from which χAD and χFL are quantified. Surprisingly, in nanoscale W/CoFeB SOT-MTJ, we find χFL to be (i) twice as large as χAD and (ii) 6 times as large as χFL in micrometer-sized W/CoFeB Hall-bar devices. Our quantification is supported by micromagnetic and macrospin simulations which reproduce experimental SOT-MTJ Stoner–Wohlfarth astroid behavior only for χFL > χAD. Additionally, from the threshold current for current-induced magnetization switching with a transverse magnetic field, we show that in SOT-MTJ, TFL plays a more prominent role in magnetization dynamics than TAD. Due to SOT-MRAM geometry and nanodimensionality, the potential role of nonlocal spin Hall spin current accumulated adjacent to the SOT-MTJ in the mediation of TFL and χFL amplification merits to be explored.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Sethu et al. (2024) studied this question.

synapsesocial.com/papers/68e69ff8b6db643587623905https://doi.org/10.1021/acsnano.3c11289
Ask AI
Helpful
Bookmark
Share
View Full Paper