Description:

This talk will consist of two parts: First, we review the status of ferromagnetic (FM) memory devices, also referred to as magnetic random-access memory (MRAM), which use the current-induced spin-transfer torque (STT) effect to switch their magnetic state. We discuss how emerging materials, physical mechanisms, and device concepts enable significant advances beyond today’s STT-MRAM, and could open fundamentally new directions in how we design computers: 

(i) As an example of new physics, we discuss electric-field-controlled magnetic devices that utilize the voltage-controlled magnetic anisotropy (VCMA) effect for switching, and present recent results on developing the first VCMA-MRAM devices with sub-1V write voltage [1]. 

(ii) As an example of new materials, we examine devices based on antiferromagnetic (AFM) materials, which may offer advantages such as picosecond switching, improved scalability, and immunity to external magnetic fields. We review recent progress in manipulating the Néel vector of such materials by current-induced spin-orbit torque (SOT) [2-4] and discuss perspectives for their further development. We also present recent results on electrical readout of the Néel vector in tunnel junctions with non-collinear AFM electrodes. 

Second, we will discuss how appropriately designed stochastic (FM- or AFM-based) nanomagnets can be used to fulfill unconventional roles within a computing system, notably as electrically controlled stochastic bitstream (SBS) generators. We then discuss the application of such MRAM-based SBS generators to true random number generation and stochastic computing (SC), and present our recent results on the implementation of an SC-based artificial neural network using a series of stochastic MRAM cells [5]. We then show examples of how a network of stochastic MRAM bits with appropriately designed control/readout circuitry – referred to as probabilistic (p-) bits – can be used to solve computationally difficult optimization problems.

[1] Y. Shao et al., Communications Materials 3, 87 (2022)
[2] J. Shi et al., Nature Electronics 3, 92 (2020)
[3] S. Arpaci et al., Nature Communications 12, 3828 (2021)
[4] Z. Zheng et al., Nature Communications 12, 4555 (2021)CG
[5] Y. Shao et al., IEEE Magnetics Letters 12, 4501005 (2021)

Pedram Khalili, Associate Professor of Electrical and Computer Engineering, Northwestern University

Host: Venkat Chandrasekhar