Dual SOT Switching Modes in a Single Device Geometry for Neuromorphic Computing

Neuromorphic computing aims to replicate the brain's efficient processing through artificial neurons and synapses, requiring binary and multilevel switching. We present a PtMn/(Co/Pd)<sub>4</sub>/Ta device that uniquely enables dual spin-orbit torque (SOT) switching modes─binary and multilevel (analog)─within the same geometry and stack structure, eliminating the need for device modifications. Binary SOT switching is achieved via domain wall nucleation and propagation at moderate current levels (∼65 mA), while multilevel switching occurs via domain nucleation mode without significant propagation after a high-current treatment (∼85 mA). The transition between two modes originates from structural changes after the current treatment. These modes allow for neuronal and synaptic functionalities, with the device achieving 96% accuracy in digit/letter recognition on the MNIST data set using an artificial neural network (ANN). The device's robust perpendicular magnetic anisotropy (PMA), dual-mode switching under a small in-plane field (<i>H</i><sub>X</sub>), and simplified fabrication underscore its promise as an energy-efficient solution for neuromorphic computing.

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Publication Details

Journal
Nano Letters
Published
2025-04-17
DOI
https://doi.org/10.1021/acs.nanolett.5c01100
Citations
2
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.46

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article

Dual SOT Switching Modes in a Single Device Geometry for Neuromorphic Computing

Tamkeen Farooq, Hsin‐Ya Sung, Rudis Ismael Salinas Padilla, Wen‐Wei Wu et al.
2 citations
Nano Letters
Advanced Memory and Neural Computing
1.46
article

Dual SOT Switching Modes in a Single Device Geometry for Neuromorphic Computing

Tamkeen Farooq, Hsin‐Ya Sung, Rudis Ismael Salinas Padilla, Wen‐Wei Wu, Abhijeet Ranjan, Ming‐Yen Lu, Chong-Chi Chi, Rahul Mishra, Chih‐Huang Lai, Po-Hung Lin
article en
2 citations

Abstract

Neuromorphic computing aims to replicate the brain's efficient processing through artificial neurons and synapses, requiring binary and multilevel switching. We present a PtMn/(Co/Pd)<sub>4</sub>/Ta device that uniquely enables dual spin-orbit torque (SOT) switching modes─binary and multilevel (analog)─within the same geometry and stack structure, eliminating the need for device modifications. Binary SOT switching is achieved via domain wall nucleation and propagation at moderate current levels (∼65 mA), while multilevel switching occurs via domain nucleation mode without significant propagation after a high-current treatment (∼85 mA). The transition between two modes originates from structural changes after the current treatment. These modes allow for neuronal and synaptic functionalities, with the device achieving 96% accuracy in digit/letter recognition on the MNIST data set using an artificial neural network (ANN). The device's robust perpendicular magnetic anisotropy (PMA), dual-mode switching under a small in-plane field (<i>H</i><sub>X</sub>), and simplified fabrication underscore its promise as an energy-efficient solution for neuromorphic computing.

Nano LettersVol. 25(17)
National Yang Ming Chiao Tung University (TW), National Tsing Hua University (TW), Indian Institute of Technology Delhi (IN)
National Science and Technology Council
Affordable and clean energy
Openalex Percentile: Top 18%
Advanced Memory and Neural Computing
1.46
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