Koh, M. Z. X., Kumar, A., & Ho, P. (2025). Beyond binary: multistate computing and neural systems with compound magnetic tunnel junctions. Journal of Physics D: Applied Physics, 59(2), 023002. https://doi.org/10.1088/1361-6463/ae27dc
Abstract:
Abstract
The magnetic random access memory (MRAM) architecture, comprising nonvolatile, fast, and energy-efficient magnetic tunnel junctions (MTJs), presents a promising platform for implementing native in-memory and neuromorphic computing tailored for edge AI applications. Integrating the MTJ-based neural network of neurons and synapses within the MRAM architecture overcomes the conventional von Neumann bottleneck, enabling computation to be performed directly where the data is stored. Here, we present an overview of MTJ technologies proposed for artificial neural networks, specifically focusing on the recent advancements in the compound MTJ concept. The compound MTJ—comprising an array of MTJ cells on a three-terminal spin–orbit torque device structure—is capable of hosting multiple resistance states and tunable conductance levels, which are well-suited for emulating the flexibility and plasticity of artificial synaptic weights. We highlight developments on compound MTJ designs with demonstrable multistate stability, and enhanced synaptic strength and resolution through the bimodal tuning of tunnel magnetoresistance and discrete states. Next, we discuss a promising strategy to expand the switching voltage window between successive states through planar rotations of constituent MTJs, engendering low write errors and high synaptic tolerance. Finally, we discuss emerging material platforms—field-immune, low-power antiferromagnets and altermagnets—as enablers of high density, multistate compound MTJs for scalable and robust in-memory and neuromorphic computing technologies.
License type:
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Funding Info:
This research / project is supported by the A*STAR - Manufacturing, Trade and Connectivity Individual Research Grants
Grant Reference no. : M23M6c0101
This research / project is supported by the A*STAR - Manufacturing, Trade and Connectivity Individual Research Grants
Grant Reference no. : M24N7c0086
Description:
This is the Accepted Manuscript version of an article accepted for publication in Journal of Physics D: Applied Physics. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at 10.1088/1361-6463/ae27dc