3,256 research outputs found

    Macromagnetic simulation for reservoir computing utilizing spin dynamics in magnetic tunnel junctions

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    The figures-of-merit for reservoir computing (RC), using spintronics devices called magnetic tunnel junctions (MTJs), are evaluated. RC is a type of recurrent neural network. The input information is stored in certain parts of the reservoir, and computation can be performed by optimizing a linear transform matrix for the output. While all the network characteristics should be controlled in a general recurrent neural network, such optimization is not necessary for RC. The reservoir only has to possess a non-linear response with memory effect. In this paper, macromagnetic simulation is conducted for the spin-dynamics in MTJs, for reservoir computing. It is determined that the MTJ-system possesses the memory effect and non-linearity required for RC. With RC using 5-7 MTJs, high performance can be obtained, similar to an echo-state network with 20-30 nodes, even if there are no magnetic and/or electrical interactions between the magnetizations

    Ultra-Fast Ferrimagnetic All Spin Logic Device

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    All spin logic device (ASLD) blazes an alternative path for realizing ultra-low power computing in the Post-Moore era. However, initial device structure relying on ferromagnetic input/output and spin transfer torque (STT) driven magnetization switching degrades its performance and even hinders its realization. In this paper, we propose an ASLD based on rare-earth (RE)-transition-metal (TM) ferromagnetic alloy that can achieve an ultra-high frequency up to terahertz. The spin orbit torque (SOT) induced fast precession near the spin angular momentum compensated point is investigated through the macrospin model. Combining the non-local spin current diffusing from the input to the output, a deterministic picosecond switching can be realized without any external magnetic field. Our results show that ASLD has the potential to exceed the performance of mainstream computing

    Experimental demonstration of a Josephson magnetic memory cell with a programmable \pi-junction

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    We experimentally demonstrate the operation of a Josephson magnetic random access memory unit cell, built with a Ni_80Fe_20/Cu/Ni pseudo spin-valve Josephson junction with Nb electrodes and an integrated readout SQUID in a fully planarized Nb fabrication process. We show that the parallel and anti-parallel memory states of the spin-valve can be mapped onto a junction equilibrium phase of either zero or pi by appropriate choice of the ferromagnet thicknesses, and that the magnetic Josephson junction can be written to either a zero-junction or pi-junction state by application of write fields of approximately 5 mT. This work represents a first step towards a scalable, dense, and power-efficient cryogenic memory for superconducting high-performance digital computing.Comment: 5 pages, 5 figures, accepted by IEEE Magnetics Letter

    Circuit Theory for SPICE of Spintronic Integrated Circuits

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    We present a theoretical and a numerical formalism for analysis and design of spintronic integrated circuits (SPINICs). The formalism encompasses a generalized circuit theory for spintronic integrated circuits based on nanomagnetic dynamics and spin transport. We propose an extension to the Modified Nodal Analysis technique for the analysis of spin circuits based on the recently developed spin conduction matrices. We demonstrate the applicability of the framework using an example spin logic circuit described using spin Netlists.Comment: 14 pages, 11 figures; added fig. 2; added citations; modified title to emphasize SPICE; Results unchange

    Fast magneto-ionic switching of interface anisotropy using yttria-stabilized zirconia gate oxide

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    Voltage control of interfacial magnetism has been greatly highlighted in spintronics research for many years, as it might enable ultra-low power technologies. Among few suggested approaches, magneto-ionic control of magnetism has demonstrated large modulation of magnetic anisotropy. Moreover, the recent demonstration of magneto-ionic devices using hydrogen ions presented relatively fast magnetization toggle switching, tsw ~ 100 ms, at room temperature. However, the operation speed may need to be significantly improved to be used for modern electronic devices. Here, we demonstrate that the speed of proton-induced magnetization toggle switching largely depends on proton-conducting oxides. We achieve ~1 ms reliable (> 103 cycles) switching using yttria-stabilized zirconia (YSZ), which is ~ 100 times faster than the state-of-the-art magneto-ionic devices reported to date at room temperature. Our results suggest further engineering of the proton-conducting materials could bring substantial improvement that may enable new low-power computing scheme based on magneto-ionics.Comment: 19 pages, 3 figures - published in Nano Letter

    A hands-on laboratory and computational experience for nanoscale materials, devices and systems education for electronics, spintronics and optoelectronics

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    To enhance the undergraduate and graduate engineering education for nanoscale materials, devices and systems, we report a multi-disciplinary course based on the integration of theory, hands-on laboratory and hands-on computation into a single curriculum. The hands-on laboratory modules span various dimensionalities of nanomaterials as well as applications in logic, memory, and energy harvesting. In the hands-on computational exercises, students simulate the material and the device characteristics, and in some cases, design the experimental process flow to fabricate and characterize the devices and systems. Such a course not only grooms the students for multi-disciplinary collaborative activities in nanoscience and nanoengineering, but also prepares them well for future academic or industrial pursuit in this area.Comment: 13 pages, 5 figures and 1 tabl

    Spintronics based Stochastic Computing for Efficient Bayesian Inference System

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    Bayesian inference is an effective approach for solving statistical learning problems especially with uncertainty and incompleteness. However, inference efficiencies are physically limited by the bottlenecks of conventional computing platforms. In this paper, an emerging Bayesian inference system is proposed by exploiting spintronics based stochastic computing. A stochastic bitstream generator is realized as the kernel components by leveraging the inherent randomness of spintronics devices. The proposed system is evaluated by typical applications of data fusion and Bayesian belief networks. Simulation results indicate that the proposed approach could achieve significant improvement on inference efficiencies in terms of power consumption and inference speed.Comment: accepted by ASPDAC 2018 conferenc

    Perspective: Ultrafast magnetism and THz spintronics

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    This year the discovery of femtosecond demagnetization by laser pulses is 20 years old. For the first time this milestone work by Bigot and coworkers gave insight in a very direct way into the time scales of microscopic interactions that connect the spin and electron system. While intense discussions in the field were fueled by the complexity of the processes in the past, it now became evident that it is a puzzle of many different parts. Rather than giving an overview that has been presented in previous reviews on ultrafast processes in ferromagnets, this perspective will show that with our current depth of knowledge the first real applications are on their way: THz spintronics and all-optical spin manipulation are becoming more and more feasible. The aim of this perspective is to point out where we can connect the different puzzle pieces of understanding gathered over 20 years to develop novel applications. based on many observations in a large number of experiments. Differences in the theoretical models arise from the localized and delocalized nature of ferromagnetism. Transport effects are intrinsically non-local in spintronic devices and at interfaces. We review the need for multiscale modeling to address processes starting from electronic excitation of the spin system on the picometer length scale and sub-femtosecond time scale, to spin wave generation, and towards the modeling of ultrafast phase transitions that altogether determine the response time of the ferromagnetic system. Today, our current understanding gives rise to the first real applications of ultrafast spin physics for ultrafast magnetism control: THz spintronic devices. This makes the field of ultrafast spin-dynamics an emerging topic open for many researchers right now.Comment: 24 pages, 11 figures, revie

    p-Bits for Probabilistic Spin Logic

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    We introduce the concept of a probabilistic or p-bit, intermediate between the standard bits of digital electronics and the emerging q-bits of quantum computing. We show that low barrier magnets or LBM's provide a natural physical representation for p-bits and can be built either from perpendicular magnets (PMA) designed to be close to the in-plane transition or from circular in-plane magnets (IMA). Magnetic tunnel junctions (MTJ) built using LBM's as free layers can be combined with standard NMOS transistors to provide three-terminal building blocks for large scale probabilistic circuits that can be designed to perform useful functions. Interestingly, this three-terminal unit looks just like the 1T/MTJ device used in embedded MRAM technology, with only one difference: the use of an LBM for the MTJ free layer. We hope that the concept of p-bits and p-circuits will help open up new application spaces for this emerging technology. However, a p-bit need not involve an MTJ, any fluctuating resistor could be combined with a transistor to implement it, while completely digital implementations using conventional CMOS technology are also possible. The p-bit also provides a conceptual bridge between two active but disjoint fields of research, namely stochastic machine learning and quantum computing. First, there are the applications that are based on the similarity of a p-bit to the binary stochastic neuron (BSN), a well-known concept in machine learning. Three-terminal p-bits could provide an efficient hardware accelerator for the BSN. Second, there are the applications that are based on the p-bit being like a poor man's q-bit. Initial demonstrations based on full SPICE simulations show that several optimization problems including quantum annealing are amenable to p-bit implementations which can be scaled up at room temperature using existing technology

    High-Resolution X-Ray Studies of the Direct Spin Contact of EuO with Silicon

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    Ferromagnetic semiconductor europium monoxide (EuO) is believed to be an effective spin injector when directly integrated with silicon. Injection through spin-selective ohmic contact requires superb structural quality of the interface EuO/Si. Recent breakthrough in manufacturing free-of-buffer-layer EuO/Si junctions calls for structural studies of the interface between the semiconductors. Ex situ high-resolution X-ray diffraction and reflectivity accompanied by in situ reflection high-energy electron diffraction reveal direct coupling at the interface. A combined analysis of XRD and XRR data provides a common structural model. The structural quality of the EuO/Si spin contact by far exceeds that of previous reports and thus makes a step forward to the ultimate goals of spintronics
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