STRAINTRONIC NANOMAGNETIC DEVICES FOR NON-BOOLEAN COMPUTING

Nanomagnetic devices have been projected as an alternative to transistor-based switching devices due to their non-volatility and potentially superior energy-efficiency. The energy efficiency is enhanced by the use of straintronics which involves the application of a voltage to a piezoelectric layer to generate a strain which is ultimately transferred to an elastically coupled magnetostrictive nanomaget, causing magnetization rotation. The low energy dissipation and non-volatility characteristics make straintronic nanomagnets very attractive for both Boolean and non-Boolean computing applications. There was relatively little research on straintronic switching in devices built with real nanomagnets that invariably have defects and imperfections, or their adaptation to non-Boolean computing, both of which have been studied in this work. Detailed studies of the effects of nanomagnet material fabrication defects and surface roughness variation (found in real nanomagnets) on the switching process and ultimately device performance of those switches have been performed theoretically. The results of these studies place the viability of straintronics logic (Boolean) and/or memory in question. With a view to analog computing and signal processing, analog spin wave based device operation has been evaluated in the presence of defects and it was found that defects impact their performance, which can be a major concern for the spin wave based device community. Additionally, the design challenge for low barrier nanomagnet which is the building block of binary stochastic neurons based probabilistic computing device in case of real nanomagnets has also been investigated. This study also cast some doubt on the efficacy of probabilistic computing devices. Fortunately, there are some non-Boolean applications based on the collective action of array of nanomagnets which are very forgiving of material defects. One example is image processing using dipole coupled nanomagnets which is studied here and it showed promising result for noise correction and edge enhancement of corrupted pixels in an image. Moreover, a single magneto tunnel junction based microwave oscillator was proposed for the first time and theoretical simulations showed that it is capable of better performance compared to traditional microwave oscillators. The experimental part of this work dealt with spin wave modes excited by surface acoustic waves, studied with time resolved magneto optic Kerr effect (TR-MOKE). New hybrid spin wave modes were observed for the first time. An experiment was carried out to emulate simulated annealing in a system of dipole coupled magnetostrictive nanomagnets where strain served as the simulated annealing agent. This was a promising outcome and it is the first demonstration of the hardware variant of simulated annealing of a many body system based on magnetostrictive nanomagnets. Finally, a giant spin Hall effect actuated surface acoustic wave antenna was demonstrated experimentally. This is the first observation of photon to phonon conversion using spin-orbit torque and although the observed conversion efficiency was poor (1%), it opened the pathway for a new acoustic radiator. These studies complement past work done in the area of straintronics

Low Barrier Nanomagnet Design for Binary Stochastic Neurons: Design Challenges for Real Nanomagnets with Fabrication Defects

Much attention has been focused on the design of low barrier nanomagnets (LBM), whose magnetizations vary randomly in time owing to thermal noise, for use in binary stochastic neurons (BSN) which are hardware accelerators for machine learning. The performance of BSNs depend on two important parameters: the correlation time associated with the random magnetization dynamics in a LBM, and the spin-polarized pinning current which stabilizes the magnetization of a LBM in a chosen direction within a chosen time. Here, we show that common fabrication defects in LBMs make these two parameters unpredictable since they are strongly sensitive to the defects. That makes the design of BSNs with real LBMs very challenging. Unless the LBMs are fabricated with extremely tight control, the BSNs which use them could be unreliable or suffer from poor yield.Comment: Accepted for publication in IEEE Magnetics Letter

Experimental Demonstration of an Extreme Sub-Wavelength Nanomagnetic Acoustic Antenna Actuated by Spin-Orbit Torque from a Heavy Metal Nanostrip

A novel on-chip extreme sub-wavelength "acoustic antenna" whose radiation efficiency is ~50 times larger than the theoretical limit for a resonantly driven antenna is demonstrated. The antenna is composed of magnetostrictive nanomagnets deposited on a piezoelectric substrate. The nanomagnets are partially in contact with a heavy metal (Pt) nanostrip. Passage of alternating current through the nanostrip exerts alternating spin-orbit torque on the nanomagnets and periodically rotates their magnetizations. During the rotation, the magnetostrictive nanomagnets expand and contract, thereby setting up alternating tensile and compressive strain in the piezoelectric substrate underneath. This leads to the generation of a surface acoustic wave in the substrate and makes the nanomagnet assembly act as an acoustic antenna. The measured radiation efficiency of this acoustic antenna at the detected frequency is ~1%, while the wavelength to antenna dimension ratio is ~ 67:1. For a standard antenna driven at acoustic resonance, the efficiency would have been limited to ~ (1/67)^2 = 0.02%. It was possible to beat that limit (by ~50 times) via actuating the antenna not by acoustic resonance, but by using a completely different mechanism involving spin-orbit torque originating from the giant spin Hall effect in Pt

A Nanomagnetic Voltage-Tunable Correlation Generator between Two Random Bit Streams for Stochastic Computing

Graphical probabilistic circuit models of stochastic computing are more powerful than the predominant deep learning models, but also have more demanding requirements. For example, they require "programmable stochasticity", e.g. generating two random binary bit streams with tunable amount of correlation between the corresponding bits in the two streams. Electronic implementation of such a system would call for several components leaving a large footprint on a chip and dissipating excessive amount of energy. Here, we show an elegant implementation with just two dipole-coupled magneto-tunneling junctions (MTJ), with magnetostrictive soft layers, fabricated on a piezoelectric film. The resistance states of the two MTJs (high or low) encode the bits in the two streams. The first MTJ is driven to a random resistance state via a current or voltage generating spin transfer torque and/or voltage controlled magnetic anisotropy, while the second MTJ's resistance state is determined solely by dipole coupling with the first. The effect of dipole coupling can be varied with local strain applied to the second MTJ with a local voltage (~0.2 V) and that varies the correlation between the resistance states of the two MTJs and hence between the bits in the two streams (from 0% to 100%). This paradigm can be extended to arbitrary number of bit streams

Image Processing with Dipole-Coupled Nanomagnets: Noise Suppression and Edge Enhancement Detection

Hardware based image processing offers speed and convenience not found in software-centric approaches. Here, we show theoretically that a two-dimensional periodic array of dipole-coupled elliptical nanomagnets, delineated on a piezoelectric substrate, can act as a dynamical system for specific image processing functions. Each nanomagnet has two stable magnetization states that encode pixel color (black or white). An image containing black and white pixels is first converted to voltage states and then mapped into the magnetization states of a nanomagnet array with magneto-tunneling junctions (MTJs). The same MTJs are employed to read out the processed pixel colors later. Dipole interaction between the nanomagnets implements specific image processing tasks such as noise reduction and edge enhancement detection. These functions are triggered by applying a global strain to the nanomagnets with a voltage dropped across the piezoelectric substrate. An image containing an arbitrary number of black and white pixels can be processed in few nanoseconds with very low energy cost