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Register a new userDomain Wall-Magnetic Tunnel Junction Spin Orbit Torque Devices and Circuits for In-Memory Computing
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Added by
Jean Anne Incorvia PhD
Publication date
2020
fields
Physics
and research's language is
English
Authors
Mahshid Alamdar
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There are pressing problems with traditional computing, especially for accomplishing data-intensive and real-time tasks, that motivate the development of in-memory computing devices to both store information and perform computation. Magnetic tunnel junction (MTJ) memory elements can be used for computation by manipulating a domain wall (DW), a transition region between magnetic domains. But, these devices have suffered from challenges: spin transfer torque (STT) switching of a DW requires high current, and the multiple etch steps needed to create an MTJ pillar on top of a DW track has led to reduced tunnel magnetoresistance (TMR). These issues have limited experimental study of devices and circuits. Here, we study prototypes of three-terminal domain wall-magnetic tunnel junction (DW-MTJ) in-memory computing devices that can address data processing bottlenecks and resolve these challenges by using perpendicular magnetic anisotropy (PMA), spin-orbit torque (SOT) switching, and an optimized lithography process to produce average device tunnel magnetoresistance TMR = 164%, resistance-area product RA = 31 {Omega}-{mu}m^2, close to the RA of the unpatterned film, and lower switching current density compared to using spin transfer torque. A two-device circuit shows bit propagation between devices. Device initialization variation in switching voltage is shown to be curtailed to 7% by controlling the DW initial position, which we show corresponds to 96% accuracy in a DW-MTJ full adder simulation. These results make strides in using MTJs and DWs for in-memory and neuromorphic computing applications.
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We use pulsed inductive microwave magnetometry to study the precessional magnetization dynamics of the free layer in CoFeB/MgO/CoFeB based magnetic tunnelling junction stacks with varying MgO barrier thickness. From the field dependence of the precession frequency we are able to derive the uniaxial anisotropy energy and the exchange coupling between the free and the pinned layer. Furthermore the field dependence of the effective damping parameter is derived. Below a certain threshold barrier thickness we observe an increased effective damping for antiparallel orientation of free and pinned layer which would inhibit reversible low current density spin torque magnetization reversal. Such inductive measurements, in combination with wafer probe station based magneto transport experiments, allow a fast determination of the optimum tunnel barrier thickness range for spin torque memory applications in a lithography free process.
Spintronics, the use of spin of an electron instead of its charge, has received huge attention from research communities for different applications including memory, interconnects, logic implementation, neuromorphic computing, and many other applications. Here, in this paper, we review the works within spintronics, more specifically on spin-orbit torque (SOT) within different research groups. We also provide researchers an insight into the future potentials of the SOT-based designs. This comprehensive review paper covers different aspects of SOT-based design from device and circuit to architecture level as well as more ambitious and futuristic applications of such technology.
Neuromorphic computing with spintronic devices has been of interest due to the limitations of CMOS-driven von Neumann computing. Domain wall-magnetic tunnel junction (DW-MTJ) devices have been shown to be able to intrinsically capture biological neuron behavior. Edgy-relaxed behavior, where a frequently firing neuron experiences a lower action potential threshold, may provide additional artificial neuronal functionality when executing repeated tasks. In this study, we demonstrate that this behavior can be implemented in DW-MTJ artificial neurons via three alternative mechanisms: shape anisotropy, magnetic field, and current-driven soft reset. Using micromagnetics and analytical device modeling to classify the Optdigits handwritten digit dataset, we show that edgy-relaxed behavior improves both classification accuracy and classification rate for ordered datasets while sacrificing little to no accuracy for a randomized dataset. This work establishes methods by which artificial spintronic neurons can be flexibly adapted to datasets.
We use three-terminal magnetic tunnel junctions (MTJs) designed for field-free switching by spin-orbit torques (SOTs) to systematically study the impact of dual voltage pulses on the switching performances. We show that the concurrent action of an SOT pulse and an MTJ bias pulse allows for reducing the critical switching energy below the level typical of spin transfer torque while preserving the ability to switch the MTJ on the sub-ns time scale. By performing dc and real-time electrical measurements, we discriminate and quantify three effects arising from the MTJ bias: the voltage-controlled change of the perpendicular magnetic anisotropy, current-induced heating, and the spin transfer torque. The experimental results are supported by micromagnetic modeling. We observe that, depending on the pulse duration and the MTJ diameter, different effects take a lead in assisting the SOTs in the magnetization reversal process. Finally, we present a compact model that allows for evaluating the impact of each effect due to the MTJ bias on the critical switching parameters. Our results provide input to optimize the switching of three-terminal devices as a function of time, size, and material parameters.
The thermal spin-transfer torque (TSTT) is an effect to switch the magnetic free layer in a magnetic tunnel junction by a temperature gradient only. We present ab initio calculations of the TSTT. In particular, we discuss the influence of magnetic layer composition by considering $text{Fe}_text{x}text{Co}_{text{1-x}}$ alloys. Further, we compare the TSTT to the bias voltage driven STT and discuss the requirements for a possible thermal switching. For example, only for very thin barriers of 3 monolayers MgO a thermal switching is imaginable. However, even for such a thin barrier the TSTT is still too small for switching at the moment and further optimization is needed. In particular, the TSTT strongly depends on the composition of the ferromagentic layer. In our current study it turns out that at the chosen thickness of the ferromagnetic layer pure Fe gives the highest thermal spin-transfer torque.
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