Understanding voltage-controlled magnetic anisotropy effect at Co/oxide interface.

The voltage-controlled magnetic anisotropy (VCMA) effect is a key to realising high-speed, ultralow-power consumption spintronic devices. The fcc-Co-(111)-based stack is a promising candidate for the achievement of large VCMA coefficients. However, only a few studies on the fcc-Co-(111)-based stack have been reported and the VCMA effect has not been well understood. Previously, we observed a significant increase in the voltage-controlled coercivity (VCC) in the Pt/Ru/Co/CoO/TiOx structure upon post-annealing. However, the mechanism underlying this enhancement remains unclear. This study performs multiprobe analyses on this structure before and after post-annealing and discusses the origin of the VCMA effect at the Co/oxide interface. X-ray magnetic circular dichroism measurement revealed an increase in the orbital magnetic moment owing to post-annealing, accompanied by a significant increase in VCC. We speculate that the diffusion of Pt atoms into the vicinity of Co/oxide interface enhances the interfacial orbital magnetic moment and the VCMA at the interface. These results provide a guideline for designing structures to obtain a large VCMA effect in fcc-Co-(111)-based stacks.

Binding events through the mutual synchronization of spintronic nano-neurons.

The brain naturally binds events from different sources in unique concepts. It is hypothesized that this process occurs through the transient mutual synchronization of neurons located in different regions of the brain when the stimulus is presented. This mechanism of 'binding through synchronization' can be directly implemented in neural networks composed of coupled oscillators. To do so, the oscillators must be able to mutually synchronize for the range of inputs corresponding to a single class, and otherwise remain desynchronized. Here we show that the outstanding ability of spintronic nano-oscillators to mutually synchronize and the possibility to precisely control the occurrence of mutual synchronization by tuning the oscillator frequencies over wide ranges allows pattern recognition. We demonstrate experimentally on a simple task that three spintronic nano-oscillators can bind consecutive events and thus recognize and distinguish temporal sequences. This work is a step forward in the construction of neural networks that exploit the non-linear dynamic properties of their components to perform brain-inspired computations.

Large voltage-induced coercivity change in Pt/Co/CoO/amorphous TiOx structure and heavy metal insertion effect.

There is urgent need for spintronics materials exhibiting a large voltage modulation effect to fulfill the great demand for high-speed, low-power-consumption information processing systems. Fcc-Co (111)-based systems are a promising option for research on the voltage effect, on account of their large perpendicular magnetic anisotropy (PMA) and high degree of freedom in structure. Aiming to observe a large voltage effect in a fcc-Co (111)-based system at room temperature, we investigated the voltage-induced coercivity (Hc) change of perpendicularly magnetized Pt/heavy metal/Co/CoO/amorphous TiOx structures. The thin CoO layer in the structure was the result of the surface oxidation of Co. We observed a large voltage-induced Hc change of 20.2 mT by applying 2 V (0.32 V/nm) to a sample without heavy metal insertion, and an Hc change of 15.4 mT by applying 1.8 V (0.29 V/nm) to an Ir-inserted sample. The relative thick Co thickness, Co surface oxidation, and large dielectric constant of TiOx layer could be related to the large voltage-induced Hc change. Furthermore, we demonstrated the separate adjustment of Hc and a voltage-induced Hc change by utilizing both upper and lower interfaces of Co.

Giant charge-to-spin conversion in ferromagnet via spin-orbit coupling.

Converting charge current into spin current via the spin Hall effect enables efficient manipulation of magnetization by electrical current. However, its geometrical restriction is a serious obstacle to device applications because it prevents switching of perpendicular magnetization in the absence of an external field. To resolve this issue, ferromagnetic materials have attracted attentions because their time reversal asymmetry induces magnetic-dependent charge-to-spin conversion that removes this restriction. Here, we achieved a large enhancement of magnetic-dependent charge-to-spin conversion by clarifying its mechanism. Through layer thickness dependence of the conversion efficiency, we revealed a coexistence of interfacial and bulk contributions to the magnetic-dependent charge-to-spin conversion. Moreover, the interfacial contribution to charge-to-spin conversion is found to be dominant and can be controlled via interfacial band engineering. The efficiency of charge-to-spin conversion in ferromagnet was found to be an order larger than that of other materials with reduced symmetry.

Comparison on Metabolism of Estradiol and Its 17-Sulfate by Recombinant Human CYP Isoforms.

To identify the CYP isoforms involved in the production of 2-hydroxyestradiol 17-sulfate (2-OH-ES), which we assume to be an antioxidant in vivo, the 2-hydroxylation reaction of estradiol 17-sulfate (ES) by human liver microsome was investigated. As a result, it was estimated that CYP2C8 and 2C9 were largely involved in the production of 2-OH-ES. Therefore, the 2-hydroxylation kinetic analysis of ES was performed for both CYPs, and the metabolic clearance Vmax/Km (µL/nmol CYP/min) was determined. On comparing the results of ES with those of estradiol (E2), it was found that CYP2C8 was about 2.5 times higher and CYP2C9 was about 3 times higher, and ES was more likely to be a substrate for the 2-hydroxylation reaction by both CYPs. The CYP isoforms involved in A-ring hydroxylation of E2 and ES differed. From this, it was speculated that 2-OH-ES plays a different role to 2-hydroxyestradiol (2-OH-E2), which is recognized as an antioxidant in the body.

Control of the stochastic response of magnetization dynamics in spin-torque oscillator through radio-frequency magnetic fields.

Neuromorphic computing using spintronic devices, such as spin-torque oscillators (STOs), has been intensively studied for energy-efficient data processing. One of the critical issues in this application is stochasticity in magnetization dynamics, which limits the accuracy of computation. Such stochastic behavior, however, plays a key role in stochastic computing and machine learning. It is therefore important to develop methods for both suppressing and enhancing stochastic response in spintronic devices. We report on experimental investigations on control of stochastic quantity, such as the width of a distribution of transient time in magnetization dynamics in vortex-type STO. The spin-transfer effect can suppress stochasticity in transient dynamics from a non-oscillating to oscillating state, whereas an application of a radio-frequency magnetic field is effective in reducing stochasticity on the time evolution of the oscillating state.

Generation of charge current from magnetization oscillation via the inverse of voltage-controlled magnetic anisotropy effect.

It is well known that oscillating magnetization induces charge current in a circuit via Faraday's law of electromagnetic induction. New physical phenomena by which magnetization dynamics can produce charge current have gained considerable interest recently. For example, moving magnetization textures, such as domain walls, generates charge current through the spin-motive force. Here, we examine an entirely different effect, which couples magnetization and electric field at the interface between an ultrathin metallic ferromagnet and dielectric. We show that this coupling can convert magnetic energy into electrical energy. This phenomenon is the Onsager reciprocal of the voltage-controlled magnetic anisotropy effect. The effect provides a previously unexplored probe to measure the magnetization dynamics of nanomagnets.

Influence of flicker noise and nonlinearity on the frequency spectrum of spin torque nano-oscillators.

The correlation of phase fluctuations in any type of oscillator fundamentally defines its spectral shape. However, in nonlinear oscillators, such as spin torque nano-oscillators, the frequency spectrum can become particularly complex. This is specifically true when not only considering thermal but also colored 1/f flicker noise processes, which are crucial in the context of the oscillator's long term stability. In this study, we address the frequency spectrum of spin torque oscillators in the regime of large-amplitude steady oscillations experimentally and as well theoretically. We particularly take both thermal and flicker noise into account. We perform a series of measurements of the phase noise and the spectrum on spin torque vortex oscillators, notably varying the measurement time duration. Furthermore, we develop the modelling of thermal and flicker noise in Thiele equation based simulations. We also derive the complete phase variance in the framework of the nonlinear auto-oscillator theory and deduce the actual frequency spectrum. We investigate its dependence on the measurement time duration and compare with the experimental results. Long term stability is important in several of the recent applicative developments of spin torque oscillators. This study brings some insights on how to better address this issue.

Voltage-Driven Magnetization Switching Controlled by Microwave Electric Field Pumping.

We study the dynamic switching properties of a nanomagnet under microwave electric field pumping. The periodic modulation of an anisotropy field induced by microwave electric field pumping efficiently excites the uniform magnetization oscillation, allowing for precise control of magnetization switching. Accurate shaping of the pumping voltage waveform also enables us to investigate the transient reaction of magnetization to the relative phase difference of the pumping signal. We demonstrate both experimentally and theoretically the existence of a dead angle in which the uniform oscillation of magnetization is inhibited even though the microwave frequency itself satisfies the conditions of parametric excitation. Our results provide an energy-efficient way of manipulating ultrafast magnetization dynamics in nanomagnetic devices.

Role of non-linear data processing on speech recognition task in the framework of reservoir computing.

The reservoir computing neural network architecture is widely used to test hardware systems for neuromorphic computing. One of the preferred tasks for bench-marking such devices is automatic speech recognition. This task requires acoustic transformations from sound waveforms with varying amplitudes to frequency domain maps that can be seen as feature extraction techniques. Depending on the conversion method, these transformations sometimes obscure the contribution of the neuromorphic hardware to the overall speech recognition performance. Here, we quantify and separate the contributions of the acoustic transformations and the neuromorphic hardware to the speech recognition success rate. We show that the non-linearity in the acoustic transformation plays a critical role in feature extraction. We compute the gain in word success rate provided by a reservoir computing device compared to the acoustic transformation only, and show that it is an appropriate bench-mark for comparing different hardware. Finally, we experimentally and numerically quantify the impact of the different acoustic transformations for neuromorphic hardware based on magnetic nano-oscillators.

Microwave magnetic field modulation of spin torque oscillator based on perpendicular magnetic tunnel junctions.

Modulation of a microwave signal generated by the spin-torque oscillator (STO) based on a magnetic tunnel junction (MTJ) with perpendicularly magnetized free layer is investigated. Magnetic field inductive loop was created during MTJ fabrication process, which enables microwave field application during STO operation. The frequency modulation by the microwave magnetic field of up to 3 GHz is explored, showing a potential for application in high-data-rate communication technologies. Moreover, an inductive loop is used for self-synchronization of the STO signal, which after field-locking, exhibits significant improvement of the linewidth and oscillation power.

Tunnel magnetoresistance angular and bias dependence enabling tuneable wireless communication.

Spin-transfer torques (STTs) can be exploited in order to manipulate the magnetic moments of nanomagnets, thus allowing for new consumer-oriented devices to be designed. Of particular interest here are tuneable radio-frequency (RF) oscillators for wireless communication. Currently, the structure that maximizes the output power is an Fe/MgO/Fe-type magnetic tunnel junction (MTJ) with a fixed layer magnetized in the plane of the layers and a free layer magnetized perpendicular to the plane. This structure allows for most of the tunnel magnetoresistance (TMR) to be converted into output power. Here, we experimentally and theoretically demonstrate that the main mechanism sustaining steady-state precession in such structures is the angular dependence of the magnetoresistance. The TMR of such devices is known to exhibit a broken-linear dependence versus the applied bias. Our results show that the TMR bias dependence effectively quenches spin-transfer-driven precession and introduces a non-monotonic frequency dependence at high applied currents. This has an impact on devices seeking to work in the 'THz gap' due to their non-trivial TMR bias dependences.

Recent Progress in the Voltage-Controlled Magnetic Anisotropy Effect and the Challenges Faced in Developing Voltage-Torque MRAM.

The electron spin degree of freedom can provide the functionality of "nonvolatility" in electronic devices. For example, magnetoresistive random access memory (MRAM) is expected as an ideal nonvolatile working memory, with high speed response, high write endurance, and good compatibility with complementary metal-oxide-semiconductor (CMOS) technologies. However, a challenging technical issue is to reduce the operating power. With the present technology, an electrical current is required to control the direction and dynamics of the spin. This consumes high energy when compared with electric-field controlled devices, such as those that are used in the semiconductor industry. A novel approach to overcome this problem is to use the voltage-controlled magnetic anisotropy (VCMA) effect, which draws attention to the development of a new type of MRAM that is controlled by voltage (voltage-torque MRAM). This paper reviews recent progress in experimental demonstrations of the VCMA effect. First, we present an overview of the early experimental observations of the VCMA effect in all-solid state devices, and follow this with an introduction of the concept of the voltage-induced dynamic switching technique. Subsequently, we describe recent progress in understanding of physical origin of the VCMA effect. Finally, new materials research to realize a highly-efficient VCMA effect and the verification of reliable voltage-induced dynamic switching with a low write error rate are introduced, followed by a discussion of the technical challenges that will be encountered in the future development of voltage-torque MRAM.

Microwave amplification in a magnetic tunnel junction induced by heat-to-spin conversion at the nanoscale.

Heat-driven engines are hard to realize in nanoscale machines because of efficient heat dissipation1. However, in the realm of spintronics, heat has been employed successfully-for example, heat current has been converted into a spin current in a NiFe|Pt bilayer system2, and Joule heating has enabled selective writing in magnetic memory arrays3. Here, we use Joule heating in nanoscale magnetic tunnel junctions to create a giant spin torque due to a magnetic anisotropy change. Efficient conversion from heat dynamics to spin dynamics is obtained because of a large interfacial thermal resistance at an FeB|MgO interface. The heat-driven spin torque is equivalent to a voltage-controlled magnetic anisotropy4,5 of approximately 300 fJ V-1 m-1, which is more than twice the value reported in a (Co)FeB|MgO system6,7. We demonstrate an electric microwave amplification gain of 20% in a d.c. biased magnetic tunnel junction as a result of this spin torque. While electric d.c. power amplification in spintronic devices has been realized previously8, the microwave amplification was limited to relatively small amplification gains (G = radiofrequency output voltage/radiofrequency input voltage) and has never exceeded 1 (refs 9-13). A magnetic tunnel junction driven by radiofrequency spin transfer torque using ferromagnetic resonance enabled a relatively large gain of G ≈ 0.55 (ref. 12). Furthermore, radiofrequency spin waves were tuned by the spin transfer effect14,15. The heat-driven giant spin torque in the FeB|MgO16,17 magnetic tunnel junction, which shows a large magnetization precession and resistance oscillation under a d.c. bias, overcomes the above limitations and provides a gain larger than 1.

Vowel recognition with four coupled spin-torque nano-oscillators.

In recent years, artificial neural networks have become the flagship algorithm of artificial intelligence1. In these systems, neuron activation functions are static, and computing is achieved through standard arithmetic operations. By contrast, a prominent branch of neuroinspired computing embraces the dynamical nature of the brain and proposes to endow each component of a neural network with dynamical functionality, such as oscillations, and to rely on emergent physical phenomena, such as synchronization2-6, for solving complex problems with small networks7-11. This approach is especially interesting for hardware implementations, because emerging nanoelectronic devices can provide compact and energy-efficient nonlinear auto-oscillators that mimic the periodic spiking activity of biological neurons12-16. The dynamical couplings between oscillators can then be used to mediate the synaptic communication between the artificial neurons. One challenge for using nanodevices in this way is to achieve learning, which requires fine control and tuning of their coupled oscillations17; the dynamical features of nanodevices can be difficult to control and prone to noise and variability18. Here we show that the outstanding tunability of spintronic nano-oscillators-that is, the possibility of accurately controlling their frequency across a wide range, through electrical current and magnetic field-can be used to address this challenge. We successfully train a hardware network of four spin-torque nano-oscillators to recognize spoken vowels by tuning their frequencies according to an automatic real-time learning rule. We show that the high experimental recognition rates stem from the ability of these oscillators to synchronize. Our results demonstrate that non-trivial pattern classification tasks can be achieved with small hardware neural networks by endowing them with nonlinear dynamical features such as oscillations and synchronization.

Scaling up electrically synchronized spin torque oscillator networks.

Synchronized nonlinear oscillators networks are at the core of numerous families of applications including phased array wave generators and neuromorphic pattern matching systems. In these devices, stable synchronization between large numbers of nanoscale oscillators is a key issue that remains to be demonstrated. Here, we show experimentally that synchronized spin-torque oscillator networks can be scaled up. By increasing the number of synchronized oscillators up to eight, we obtain that the emitted power and the quality factor increase linearly with the number of oscillators. Even more importantly, we demonstrate that the stability of synchronization in time exceeds 1.6 milliseconds corresponding to 105 periods of oscillation. Our study demonstrates that spin-torque oscillators are suitable for applications based on synchronized networks of oscillators.

Neural-like computing with populations of superparamagnetic basis functions.

In neuroscience, population coding theory demonstrates that neural assemblies can achieve fault-tolerant information processing. Mapped to nanoelectronics, this strategy could allow for reliable computing with scaled-down, noisy, imperfect devices. Doing so requires that the population components form a set of basis functions in terms of their response functions to inputs, offering a physical substrate for computing. Such a population can be implemented with CMOS technology, but the corresponding circuits have high area or energy requirements. Here, we show that nanoscale magnetic tunnel junctions can instead be assembled to meet these requirements. We demonstrate experimentally that a population of nine junctions can implement a basis set of functions, providing the data to achieve, for example, the generation of cursive letters. We design hybrid magnetic-CMOS systems based on interlinked populations of junctions and show that they can learn to realize non-linear variability-resilient transformations with a low imprint area and low power.

Effect of MgO Underlying Layer on the Growth of GaOx Tunnel Barrier in Epitaxial Fe/GaOx/(MgO)/Fe Magnetic Tunnel Junction Structure.

We investigated the effect of a thin MgO underlying layer (~3 monoatomic layers) on the growth of GaOx tunnel barrier in Fe/GaOx/(MgO)/Fe(001) magnetic tunnel junctions. To obtain a single-crystalline barrier, an in situ annealing was conducted with the temperature being raised up to 500 °C under an O2 atmosphere. This annealing was performed after the deposition of the GaOx on the Fe(001) bottom electrode with or without the MgO(001) underlying layer. Reflection high-energy electron diffraction patterns after the annealing indicated the formation of a single-crystalline layer regardless of with or without the MgO layer. Ex situ structural studies such as transmission electron microscopy revealed that the GaOx grown on the MgO underlying layer has a cubic MgAl2O4-type spinel structure with a (001) orientation. When without MgO layer, however, a Ga-Fe-O ternary compound having the same crystal structure and orientation as the crystalline GaOx was observed. The results indicate that the MgO underlying layer effectively prevents the Fe bottom electrode from oxidation during the annealing process. Tunneling magneto-resistance effect was observed only for the sample with the MgO underlying layer, suggesting that Ga-Fe-O layer is not an effective tunnel-barrier.

Neuromorphic computing with nanoscale spintronic oscillators.

Neurons in the brain behave as nonlinear oscillators, which develop rhythmic activity and interact to process information. Taking inspiration from this behaviour to realize high-density, low-power neuromorphic computing will require very large numbers of nanoscale nonlinear oscillators. A simple estimation indicates that to fit 108 oscillators organized in a two-dimensional array inside a chip the size of a thumb, the lateral dimension of each oscillator must be smaller than one micrometre. However, nanoscale devices tend to be noisy and to lack the stability that is required to process data in a reliable way. For this reason, despite multiple theoretical proposals and several candidates, including memristive and superconducting oscillators, a proof of concept of neuromorphic computing using nanoscale oscillators has yet to be demonstrated. Here we show experimentally that a nanoscale spintronic oscillator (a magnetic tunnel junction) can be used to achieve spoken-digit recognition with an accuracy similar to that of state-of-the-art neural networks. We also determine the regime of magnetization dynamics that leads to the greatest performance. These results, combined with the ability of the spintronic oscillators to interact with each other, and their long lifetime and low energy consumption, open up a path to fast, parallel, on-chip computation based on networks of oscillators.

Voltage controlled interfacial magnetism through platinum orbits.

Electric fields at interfaces exhibit useful phenomena, such as switching functions in transistors, through electron accumulations and/or electric dipole inductions. We find one potentially unique situation in a metal-dielectric interface in which the electric field is atomically inhomogeneous because of the strong electrostatic screening effect in metals. Such electric fields enable us to access electric quadrupoles of the electron shell. Here we show, by synchrotron X-ray absorption spectroscopy, electric field induction of magnetic dipole moments in a platinum monatomic layer placed on ferromagnetic iron. Our theoretical analysis indicates that electric quadrupole induction produces magnetic dipole moments and provides a large magnetic anisotropy change. In contrast with the inability of current designs to offer ultrahigh-density memory devices using electric-field-induced spin control, our findings enable a material design showing more than ten times larger anisotropy energy change for such a use and highlight a path in electric-field control of condensed matter.