Magnetic Tunnel Junctions Research Articles

Conceptional proposal of a microwave-only quantum magnetic head by phase-induced tunneling magnetoresistance effects and of a 3-dimensional multilayer platter

Tunneling magnetoresistance effects result in a high-performance magnetic head, enabling a high magnetic domain density in a platter. This conventional method of using magnetic flux to read or write is close to the magnetic domain density limit. Herein, we propose a conceptional method for developing a magnetic head by controlling phase-induced tunneling magnetoresistance effects. The developed magnetic head can be read out in units of 1 qubit. However, because recording data per BEC qubit is difficult due to thermal fluctuations, we evaluated the robustness of the method and concluded that it is robust to bit flips. Our method does not use a magnetic field for reading or writing, further suggesting that one may use a microwave instead. This is a distinguishing feature, allowing further integration of the magnetic domain density in a platter.

Skyrmion-mediated nonvolatile ternary memory

Multistate memory systems have the ability to store and process more data in the same physical space as binary memory systems, making them a potential alternative to existing binary memory systems. In the past, it has been demonstrated that voltage-controlled magnetic anisotropy (VCMA) based writing is highly energy-efficient compared to other writing methods used in non-volatile nano-magnetic binary memory systems. In this study, we introduce a new, VCMA-based and skyrmion-mediated non-volatile ternary memory system using a perpendicular magnetic tunnel junction (p-MTJ) in the presence of room temperature thermal perturbation. We have also shown that ternary states {− 1, 0, + 1} can be implemented with three magnetoresistance values obtained from a p-MTJ corresponding to ferromagnetic up, down, and skyrmion state, with 99% switching probability in the presence of room temperature thermal noise in an energy-efficient way, requiring ~ 2 fJ energy on an average for each switching operation. Additionally, we show that our proposed ternary memory demonstrates an improvement in area and energy by at least 2X and ~ 104X respectively, compared to state-of-the-art spin-transfer torque (STT)-based non-volatile magnetic multistate memories. Furthermore, these three states can be potentially utilized for energy-efficient, high-density in-memory quantized deep neural network implementation.

Experimental demonstration of magnetic tunnel junction-based computational random-access memory

The conventional computing paradigm struggles to fulfill the rapidly growing demands from emerging applications, especially those for machine intelligence because much of the power and energy is consumed by constant data transfers between logic and memory modules. A new paradigm, called “computational random-access memory (CRAM),” has emerged to address this fundamental limitation. CRAM performs logic operations directly using the memory cells themselves, without having the data ever leave the memory. The energy and performance benefits of CRAM for both conventional and emerging applications have been well established by prior numerical studies. However, there is a lack of experimental demonstration and study of CRAM to evaluate its computational accuracy, which is a realistic and application-critical metric for its technological feasibility and competitiveness. In this work, a CRAM array based on magnetic tunnel junctions (MTJs) is experimentally demonstrated. First, basic memory operations, as well as 2-, 3-, and 5-input logic operations, are studied. Then, a 1-bit full adder with two different designs is demonstrated. Based on the experimental results, a suite of models has been developed to characterize the accuracy of CRAM computation. Scalar addition, multiplication, and matrix multiplication, which are essential building blocks for many conventional and machine intelligence applications, are evaluated and show promising accuracy performance. With the confirmation of MTJ-based CRAM’s accuracy, there is a strong case that this technology will have a significant impact on power- and energy-demanding applications of machine intelligence.

High tunneling magneto-resistance ratio in Co2FeAl Heusler alloy and WSe2 2D material tunnel barrier-based magnetic tunnel junctions

This paper presents a Magnetic Tunnel Junction (MTJ) based on Co2FeAl Heusler alloy and 2D material WSe2 with an enhanced tunnelling magneto-resistance (TMR). Our study is inspired by recent investigations of 2D materials and Heusler alloys. By employing static Density Functional Theory (DFT) simulations coupled with Non-Equilibrium Green’s Function (NEGF) transport models, we evaluate conductance properties in Co2FeAl/WSe2/Co2FeAl MTJ. The half metallicity of Co2FeAl and quantum confinement properties of WSe2 are compatible, which enhances the TMR of MTJ.

Multilevel magnetoresistance states in La0.7Sr0.3MnO3/BaTiO3/La0.7Sr0.3MnO3 heterostructure grown on MgO

Magnetic tunnel junction (MTJ) is one of the cornerstones of modern information technologies. Bringing MTJ's operation beyond the conventional binary regime, enabled by tunneling magnetoresistance (TMR) effect, is highly promising for prospective memory technologies and neuromorphic hardware development. In this paper, we demonstrate multilevel magnetoresistance states in an all-perovskite-oxide La0.7Sr0.3MnO3 (LSMO)/BaTiO3/LSMO heterostructure grown on MgO substrates. Unlike traditional TMR, we observe four distinct regions of increased magnetoresistance, which result in three magnetic field-induced resistance states in total. We show that the observed phenomenon arises from the low-field magnetoresistance effect, which occurs in the two epitaxial LSMO layers, independently and at different values of the magnetic field. The effect is well simulated by a model based on the presence of structural defects and non-uniform deformations in the LSMO layers, induced by the large lattice mismatch of the LSMO with the MgO substrate. We believe that our findings contribute to the understanding of complex magnetoresistance effects in MTJs and can be taken into consideration for the design of multi-bit memory cells or neuromorphic devices.

Unipolar spin diodes and unipolar spin switches by Spin-Transfer torque in doped graphether

Spin switches are a fundamental component in the majority of spintronic devices, and have found extensive application in data storage, logical data manipulation, and signal processing. An essential aspect of constructing a spin switch is determining a stable two-dimensional material, which is easy to control and produce. Theoretical studies have shown that graphether is particularly promising due to its exceptionally high melting point and outstanding air stability. The band structure can be modified by doping, making it an important material for spin switch applications. In this paper, we have calculated the electromagnetic properties of doped graphether by first principles. Then we select a modified graphether with P-type and N-type doping configurations to construct magnetic tunnel junctions (MTJ). The results show that the MTJ exhibits perfect highly efficient spin switch as a result of spin reversal induced by spin-transfer torque (STT). In addition, our designed MTJ shows a remarkable rectification effect and spin filtering effect (SFE). According to our calculations, the modified graphether materials also show promise as two-dimensional spintronics materials.

Half-Metallic Transport and Spin-Polarized Tunneling through the van der Waals Ferromagnet Fe4GeTe2.

We examine the coherent spin-dependent transport properties of the van der Waals (vdW) ferromagnet Fe4GeTe2 using density functional theory combined with the nonequilibrium Green's function method. Our findings reveal that the conductance perpendicular to the layers is half-metallic, meaning that it is almost entirely spin-polarized. This property persists from the bulk to a single layer, even under significant bias voltages and with spin-orbit coupling. Additionally, using dynamical mean field theory for quantum transport, we demonstrate that electron correlations are important for magnetic properties but minimally impact the conductance, preserving almost perfect spin-polarization. Motivated by these results, we then study the tunnel magnetoresistance (TMR) in a magnetic tunnel junction consisting of two Fe4GeTe2 layers with the vdW gap acting as an insulating barrier. We predict a TMR ratio of ∼500%, which can be further enhanced by increasing the number of Fe4GeTe2 layers in the junction.

Quantum Transport through a Quantum Dot Coupled to Majorana Nanowire and Two Ferromagnets with Noncollinear Magnetizations.

We study the electron tunneling (ET) and local Andreev reflection (AR) processes in a quantum dot (QD) coupled to the left and right ferromagnetic leads with noncollinear ferromagnetisms. In particular, we consider that the QD is also side-coupled to a nanowire hosting Majorana bound states (MBSs) at its ends. Our results show that when one mode of the MBSs is coupled simultaneously to both spin-up and spin-down electrons on the QD, the height of the central peak is different from that if the MBS is coupled to only one spin component electrons. The ET and AR conductances, which are mediated by the dot-MBS hybridization, strongly depend on the angle between the left and right magnetic moments in the leads. Interaction between the QD and the MBSs will result in sign change of the angle-dependent tunnel magnetoresistance. This is very different from the case when the QD is coupled to regular fermonic mode, and can be used for detecting the existence of MBSs, a current challenge in condensed matter physics under extensive investigations.

Domain wall and magnetic tunnel junction hybrid for on-chip learning in UNet architecture

We present a spintronic device based hardware implementation of UNet for segmentation tasks. Our approach involves designing hardware for convolution, deconvolution, rectified activation function (ReLU), and max pooling layers of the UNet architecture. We designed the convolution and deconvolution layers of the network using the synaptic behavior of the domain wall MTJ. We also construct the ReLU and max pooling functions of the network utilizing the spin hall driven orthogonal current injected MTJ. To incorporate the diverse physics of spin-transport, magnetization dynamics, and CMOS elements in our UNet design, we employ a hybrid simulation setup that couples micromagnetic simulation, non-equilibrium Green’s function, and SPICE simulation along with network implementation. We evaluate our UNet design on the CamVid dataset and achieve segmentation accuracies of 83.71% on test data, on par with the software implementation with 821 mJ of energy consumption for on-chip training over 150 epochs. We further demonstrate nearly one order of magnitude (10×) improvement in the energy requirement of the network using unstable ferromagnet (Δ = 4.58) over the stable ferromagnet (Δ = 45) based ReLU and max pooling functions while maintaining similar accuracy. The hybrid architecture comprising domain wall MTJ and unstable FM-based MTJ leads to an on-chip energy consumption of 85.79 mJ during training, with a testing energy cost of 1.55 µJ.

Multistate magnetic tunnel junction based on a single two-dimensional van der Waals antiferromagnet

Multistate magnetic tunnel junction based on a single two-dimensional van der Waals antiferromagnet

First-principles study of the structure, magnetism, and electronic properties of the all-Heusler alloy Co2MnGe/CoTiMnGe(100) heterojunction.

Based on first-principles calculations in the density functional theory, we systematically investigated the possible interface structure, magnetism, and electronic properties of the all-Heusler alloy Co2MnGe/CoTiMnGe(100) heterojunction. The calculation indicated that the Co2MnGe Heusler alloy is a half-metal with a magnetic moment of 4.97μB. CoTiMnGe is a narrow-band gap semiconductor and may act as an ultra-sensitive photocatalyst. We cannot find an "ideal" spin-polarization of 100% in CoCo termination and MnGe termination. Due to the interface interaction, the direct magnetic hybridization or indirect RKKY exchange will be weakened, leading to an increase in the atomic magnetic moment of the interfacial layer. For eight possible heterojunction structures, the half-metallic gaps in the Co2MnGe bulk have been destroyed by the inevitable interface states. The spin-polarization value of 94.31% in the CoCo-TiGe-B heterojunction revealed that it is the most stable structure. It is feasible to search for high-performance magnetic tunnel junction by artificially constructing suitable all-Heusler alloy heterojunctions.

Voltage-insensitive stochastic magnetic tunnel junctions with double free layers

Stochastic magnetic tunnel junction (s-MTJ) is a promising component of probabilistic bit (p-bit), which plays a pivotal role in probabilistic computers. For a standard cell structure of the p-bit, s-MTJ is desired to be insensitive to voltage across the junction over several hundred millivolts. In conventional s-MTJs with a reference layer having a fixed magnetization direction, however, the stochastic output significantly varies with the voltage due to spin-transfer torque (STT) acting on the stochastic free layer. In this work, we study a s-MTJ with a “double-free-layer” design theoretically proposed earlier, in which the fixed reference layer of the conventional structure is replaced by another stochastic free layer, effectively mitigating the influence of STT on the stochastic output. We show that the key device property characterized by the ratio of relaxation times between the high- and low-resistance states is one to two orders of magnitude less sensitive to bias voltage variations compared to conventional s-MTJs when the top and bottom free layers are designed to possess the same effective thickness. This work opens a pathway for reliable, nanosecond-operation, high-output, and scalable spintronics-based p-bits.

Chirality-Induced Memristor of Chiral Nanostructured Half-Metallic Fe3O4 Films.

Spintronic memristors, which combine the nonvolatile characteristics of memristors with the scalability of a spin-transfer torque device, are expected to play a crucial role in advancing quantitative information processing. This field commonly relies on magnetic tunnel junctions, domain wall motion, and spin waves. Here, the discovery of chirality-induced memristor behavior in chiral nanostructured Fe3O4 films (CNFFs) is reported. These CNFFs are grown on fluorine tin oxide (FTO) substrates using enantiomeric glutamic acid (Glu) as symmetry-breaking agents and consist of arrays of oriented twisted nanofibers. At 100 K, the L-CNFF exhibits memristor behavior as a pinched hysteresis loop in the I-V curve, while the D-CNFF exhibits semiconductor behavior with constant electrical resistance. The intrinsic spin polarization of half-metallic Fe3O4 and the chirality-induced spin selectivity (CISS) are speculated to contribute to the memristor in one handedness of the chiral structure. These findings present a novel spinristor that combines the functions of a memristor and a spin-filter based on chiral structures, which may promote the development of spintronic devices.

Voltage-Driven Fluorine Motion for Novel Organic Spintronic Memristor.

Integrating tunneling magnetoresistance (TMR) effect in memristors is a long-term aspiration because it allows to realize multifunctional devices, such as multi-state memory and tunable plasticity for synaptic function. However, the reported TMR in different multiferroic tunnel junctions is limited to 100%. This work demonstrates a giant TMR of -266% in La0.6Sr0.4MnO3(LSMO)/poly(vinylidene fluoride)(PVDF)/Co memristor with thin organic barrier. Different from the ferroelectricity-based memristors, this work discovers that the voltage-driven florine (F) motion in the junction generates a huge reversible resistivity change up to 106% with nanosecond (ns) timescale. Removing F from PVDF layer suppresses the dipole field in the tunneling barrier, thereby significantly enhances the TMR. Furthermore, the TMR can be tuned by different polarizing voltage due to the strong modification of spin-polarization at the LSMO/PVDF interface upon F doping. Combining of high TMR in the organic memristor paves the way to develop high-performance multifunctional devices for storage and neuromorphic applications.

Mixed etching-oxidation process to enhance the performance of spin-transfer torque MRAM for high-performance computing

Spin-transfer torque magnetic random access memory (MRAM) devices have considerable potential for high-performance computing applications; however, progress in this field has been hindered by difficulties in etching the magnetic tunnel junction (MTJ). One notable issue is electrical shorting caused by the accumulation of etching by-products on MTJ surfaces. Attempts to resolve these issues led to the development of step-MTJs, in which etching does not proceed beyond the MgO barrier; however, the resulting devices suffer from poor scalability and unpredictable shunting paths due to asymmetric electrode structures. This paper outlines the fabrication of pillar-shaped MTJs via a four-step etching process involving reactive-ion etching, ion-beam etching, oxygen exposure, and ion-trimming. The respective steps can be cross-tuned to optimize the shape of the pillars, prevent sidewall redeposition, and remove undesired shunting paths in order to enhance MTJ performance. In experiments, the proposed pillar-MTJs outperformed step-MTJs in key metrics, including tunneling magnetoresistance, coercivity, and switching efficiency. The proposed pillar-MTJs also enable the fabrication of MRAM cells with smaller cell sizes than spin–orbit torque devices and require no external field differing from voltage-controlled magnetic anisotropy devices.

An Extensive Review of MR Sensors with Design and Characteristic Evaluation of Three-layered TMR Sensor

Abstract: The reliability and efficacy of sensor-based automated systems have improved due to the proliferation of electric vehicles, renewable sources, and integrated systems in power industries extensively. This has been accomplished by increasing the power density and decreasing the volume of the system. Background: Mathematical estimation and comparative analysis of the physical factors result in massive usage of operational matrices measured using sensors. Magnetic field sensors, used in industries and biomedical applications, have a high level of precision in the evaluation of measurements. In order to extract the measured parameters such as sensitivity, accuracy, operating cost, the linear range of operation, and power utilisation, these sensors adhere to the physical constraints during their nominal working conditions. The characteristics of the aforementioned sensors are enumerated in detail in this article. Objective: This objective is highly focused on providing a comprehensive overview of classification and the properties of Hall-Effect, anisotropic magnetoresistive (AMR), giant magnetoresistive (GMR), and tunnelling magnetoresistive (TMR) sensors. The dissertation on its properties concludes that TMR is more reliable and sensitive in variable operating conditions. Methods: The methods for selecting the sensors for an application are confined to voltage fluctuations and sensitivity. A three-layered TMR sensor with two magnetic layers and an insulator in between is proposed as a significant advancement compared to the literature. The micromagnetic simulation is carried out at room temperature for a three-layered TMR made up of neodymium alloy, magnesium oxide, and cobalt platinum alloy. Conclusion: Based on the studies executed, it is determined that TMR is more sensitive than both conventional and MR sensors. The proposed schematic claims that the higher free layer thickness offers maximum sensitivity with 77% negative magnetoresistance. The reduced coercivity of 1.9Oe is achieved in this combination at a specified temperature range.

The 68th annual conference on magnetism and magnetic materials

The 2023 Conference on Magnetism and Magnetic Materials (MMM) was held from October 30–November 3 at the Dallas Hyatt Regency, at the base of the iconic Reunion Tower. There, 703 on-site attendees from 37 different countries discussed cutting-edge research in fundamental and applied magnetism, made new connections, and met old friends and colleagues at one of the first primarily in-person conferences in our field since the major disruptions of the pandemic era. The format of the conference was primarily in-person, with supporting online content that included recordings of the most popular programs and presentations, made available after the conference (including all symposia, the tutorial, and selected other special content). All presenters had the option to contribute online content, as did 96 participants who did not travel to the venue and elected to present virtual posters. Attendees enjoyed a vibrant celebration of the magnetism research community that included a Texas-sized welcome reception, tutorials on machine learning in magnetism, seven symposia, a lively exhibit hall that hosted poster sessions and bierstuben, a full roster of special events, coffee breaks to facilitate active scientific discussions, and of course, excellent technical presentations. These technical presentations, organized into 45 oral sessions, 23 in-person poster sessions, and 17 virtual poster sessions, were selected by a Program Committee of 57 members, capably coordinated by three Program Chairs: Hendrik Ohldag (ALS-LBNL), Karin Leistner (TU Chemnitz), and Takahiro Moriyama (Nagoya University). These three Program Chairs worked seamlessly and tirelessly over many months to make the central mission of MMM a huge success. The Program Committee selected seven symposia from nominations provided by the magnetism community: “Frontier Topics in Antiferromagnetism: Altermagnetism and Topology,” “Rare Earth Spintronics,” “Recent Advances in Cavity Magnonics,” “Emerging Topics in Magnetic Tunnel Junctions: Altermagnetism, Probabilistic Computing and Energy Efficient Switching,” “Orbitronics: From Orbital Currents Created by Charge Currents to Creation by Light or RF Excitation,” “Imaging Magnetic Textures at the Nanoscale,” and finally “Magnetization Dynamics in Two-Dimensional van der Waals Magnets.” These symposia highlighted a wide range of exciting new areas for magnetism, and were part of a total of 101 invited talks, 28% of which were presented by women. The contributed program was selected by the Program Committee from more than 900 submitted abstracts.

Thermal optimization of two-terminal SOT-MRAM

While magnetoresistive random-access memory (MRAM) stands out as a leading candidate for embedded nonvolatile memory and last-level cache applications, its endurance is compromised by substantial self-heating due to the high programming current density. The effect of self-heating on the endurance of the magnetic tunnel junction (MTJ) has primarily been studied in spin-transfer torque (STT)-MRAM. Here, we analyze the transient temperature response of two-terminal spin–orbit torque (SOT)-MRAM with a 1 ns switching current pulse using electro-thermal simulations. We estimate a peak temperature range of 350–450 °C in 40 nm diameter MTJs, underscoring the critical need for thermal management to improve endurance. We suggest several thermal engineering strategies to reduce the peak temperature by up to 120 °C in such devices, which could improve their endurance by at least a factor of 1000× at 0.75 V operating voltage. These results suggest that two-terminal SOT-MRAM could significantly outperform conventional STT-MRAM in terms of endurance, substantially benefiting from thermal engineering. These insights are pivotal for thermal optimization strategies in the development of MRAM technologies.

2-D Analytical Modeling of the Magnetic Tunnel Junctions Including Multidomain Effects: Predictive Insights and Design Optimization

2-D Analytical Modeling of the Magnetic Tunnel Junctions Including Multidomain Effects: Predictive Insights and Design Optimization

Arbitrary Modulation of Average Dwell Time in Discrete-Time Markov Chains Based on Tunneling Magnetoresistance Effect

Arbitrary Modulation of Average Dwell Time in Discrete-Time Markov Chains Based on Tunneling Magnetoresistance Effect