The recent discovery that a spin-polarized electrical current can apply a large torque to a ferromagnet, through direct transfer of spin angular momentum, offers the possibility of manipulating magnetic-device elements without applying cumbersome magnetic fields. However, a central question remains unresolved: what type of magnetic motions can be generated by this torque? Theory predicts that spin transfer may be able to drive a nanomagnet into types of oscillatory magnetic modes not attainable with magnetic fields alone, but existing measurement techniques have provided only indirect evidence for dynamical states. The nature of the possible motions has not been determined. Here we demonstrate a technique that allows direct electrical measurements of microwave-frequency dynamics in individual nanomagnets, propelled by a d.c. spin-polarized current. We show that spin transfer can produce several different types of magnetic excitation. Although there is no mechanical motion, a simple magnetic-multilayer structure acts like a nanoscale motor; it converts energy from a d.c. electrical current into high-frequency magnetic rotations that might be applied in new devices including microwave sources and resonators.

Microwave Oscillations of a Nanomagnet Driven by a DC Spin-Polarized Current

Magnetic devices are a leading contender for the implementation of memory and logic technologies that are non-volatile, that can scale to high density and high speed, and that do not wear out. However, widespread application of magnetic memory and logic devices will require the development of efficient mechanisms for reorienting their magnetization using the least possible current and power. There has been considerable recent progress in this effort; in particular, it has been discovered that spin–orbit interactions in heavy-metal/ferromagnet bilayers can produce strong current-driven torques on the magnetic layer, via the spin Hall effect in the heavy metal or the Rashba–Edelstein effect in the ferromagnet. In the search for materials to provide even more efficient spin–orbit-induced torques, some proposals have suggested topological insulators, which possess a surface state in which the effects of spin–orbit coupling are maximal in the sense that an electron’s spin orientation is fixed relative to its propagation direction. Here we report experiments showing that charge current flowing in-plane in a thin film of the topological insulator bismuth selenide (Bi2Se3) at room temperature can indeed exert a strong spin-transfer torque on an adjacent ferromagnetic permalloy (Ni81Fe19) thin film, with a direction consistent with that expected from the topological surface state. We find that the strength of the torque per unit charge current density in Bi2Se3 is greater than for any source of spin-transfer torque measured so far, even for non-ideal topological insulator films in which the surface states coexist with bulk conduction. Our data suggest that topological insulators could enable very efficient electrical manipulation of magnetic materials at room temperature, for memory and logic applications.

/pdf/spin-transfer-torque-generated-by-a-topological-insulator-168lc3m65h.pdf

Spin-transfer torque generated by a topological insulator

By showing that there is no any memristor in the integer-order Hindmarsh–Rose (H–R) model, the slow ion channel is remodeled by a fractional-order memristor, where the fractional-order derivative is related to the memory effect and the decay rate of the ion current. Then a fractional-order memristive (FOM) H–R model without equilibrium is proposed. Due to a small parameter, the FOM H–R model is a fast–slow system which can be taken as the small perturbation system of the fast subsystem. By Lyapunov direct method, the boundedness of the fast subsystem is proved. With the help of the boundedness and stability of the fast system, the hidden dynamics of the FOM H–R model is discussed. As the small parameter is fixed, it is shown that the membrane potential of the FOM H–R model limits to a quiescent state as the fractional order is less than 0.5 and limits to a periodic spiking as the fractional order is greater than 0.5 less than 1. Without the constraint of the small parameter, the periodic and chaotic bursting appears in the FOM H–R model, which implies the small parameter makes the membrane potential activity simpler. It can be drawn a conclusion that the ion current with the slow decay rate can inhibit the neurons.

Hidden dynamics in a fractional-order memristive Hindmarsh–Rose model

Spin structures of nanoscale magnetic dots are the subject of increasing scientific effort, as the confinement of spins imposed by the geometrical restrictions makes these structures comparable to some internal characteristic length scales of the magnet. For a vortex (a ferromagnetic dot with a curling magnetic structure), a spot of perpendicular magnetization has been theoretically predicted to exist at the center of the vortex. Experimental evidence for this magnetization spot is provided by magnetic force microscopy imaging of circular dots of permalloy (Ni(80)Fe(20)) 0.3 to 1 micrometer in diameter and 50 nanometers thick.

/pdf/magnetic-vortex-core-observation-in-circular-dots-of-s2r5hs6bft.pdf

Magnetic Vortex Core Observation in Circular Dots of Permalloy (SOLID STATE CHEMISTRY-Artificial Lattice Allolys)

A four-dimensional memristive system is constructed using a novel ideal memristor with cosine memductance. Due to the special memductance nonlinearity, this memristive system has a line equilibrium set (0, 0, 0, δ) located along the coordinate of the inner state variable of the memristor, whose stability is periodically varied with a change of δ. Nonlinear and one-dimensional initial offset boosting behaviors, which are triggered by not only the initial condition of the memristor but also other two initial conditions, are numerically uncovered. Specifically, a wide variety of coexisting attractors with different positions and topological structures are revealed along the boosting route. Finally, circuit simulations are performed by Power SIMulation (PSIM) to confirm the unique dynamical features.

Periodically varied initial offset boosting behaviors in a memristive system with cosine memductance

Neuromorphic computing systems are promising alternatives in the fields of pattern recognition, image processing, etc. especially when conventional von Neumann architectures face several bottlenecks. Memristors play vital roles in neuromorphic computing systems and are usually used as synaptic devices. Memristive spiking neural networks (MSNNs) are considered to be more efficient and biologically plausible than other systems due to their spike-based working mechanism. In contrast to previous SNNs with complex architectures, we propose a hardware-friendly architecture and an unsupervised spike-timing dependent plasticity (STDP) learning method for MSNNs in this paper. The architecture, which is friendly to hardware implementation, includes an input layer, a feature learning layer and a voting circuit. To reduce hardware complexity, some constraints are enforced: the proposed architecture has no lateral inhibition and is purely feedforward; it uses the voting circuit as a classifier and does not use additional classifiers; all neurons can generate at most one spike and do not need to consider firing rates and refractory periods; all neurons have the same fixed threshold voltage for classification. The presented unsupervised STDP learning method is time-dependent and uses no homeostatic mechanism. The MNIST dataset is used to demonstrate our proposed architecture and learning method. Simulation results show that our proposed architecture with the learning method achieves a classification accuracy of 94.6%, which outperforms other unsupervised SNNs that use time-based encoding schemes.

/pdf/memristive-spiking-neural-networks-trained-with-unsupervised-307mf4b9bx.pdf

Memristive Spiking Neural Networks Trained with Unsupervised STDP

Spin-torque nano-oscillators based on radial vortex in the presence of interface Dzyaloshinskii-Moriya interaction

The intrinsic stochasticity of resistance switching process is one of the holdblocks for using memristor as a fundamental element in the next-generation nonvolatile memory. However, such a weakness can be used as an asset for generating the random bits, which is valuable in a hardware security system. In this work, a forming-free electronic bipolar Pt/Ti/Ta2O5/Pt memristor is successfully fabricated to investigate the merits of generating random bits in such a device. The resistance switching mechanism of the fabricated device is ascribed to the electric field conducted electrons trapping/de-trapping in the deep-energy-level traps produced by the "oxygen grabbing" process. The stochasticity of the electrons trapping/de-trapping governs the random distribution of the set/reset switching voltages of the device, making a single memristor act as a random bit in which the resistance of the device represents information and the applied voltage pulse serves as the triggering signal. The physical implementation of such a random process provides a method of generating the random bits based on memristors in hardware security applications.

A method of generating random bits by using electronic bipolar memristor

Voltage manipulation of desired magnetization orientation in multiferroic heterostructures

In situ control of radial vortex polarity at room temperature utilizing perpendicular magnetic field pulse

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