Related papers: Straintronic spin-neuron
Antiferromagnetic (AFM) spintronics has emerged as a subfield of spintronics, where an AFM N\'eel vector is used as a state variable. Efficient electric control and detection of the N\'eel vector are critical for spintronic applications.…
We propose that a spin Hall effect driven magnetic tunnel junction device can be engineered to provide a continuous change in the resistance across it when injected with orthogonal spin currents. Using this concept, we develop a hybrid…
Spintronics, or spin electronics, involves the study of active control and manipulation of spin degrees of freedom in solid-state systems. This article reviews the current status of this subject, including both recent advances and…
We present spin transfer switching results for MgO based magnetic tunneling junctions (MTJs)with large tunneling magnetoresistance (TMR) ratio of up to 150% and low intrinsic switching current density of 2-3 x 10 MA/cm2. The switching data…
Intracortical brain-machine interfaces demand low-latency, energy-efficient solutions for neural decoding. Spiking Neural Networks (SNNs) deployed on neuromorphic hardware have demonstrated remarkable efficiency in neural decoding by…
We suggest a consistent microscopic theory of spin injection from a ferromagnet (FM) into a semiconductor (S). It describes tunneling and emission of electrons through modified FM-S Schottky barrier with an ultrathin heavily doped…
Angular momentum transport in magnetic multilayered structures plays a central role in spintronic physics and devices. The angular momentum currents or spin currents are carried by either quasi-particles such as electrons and magnons, or by…
In spiking neural networks, neuron dynamics are described by the biologically realistic integrate-and-fire model that captures membrane potential accumulation and above-threshold firing behaviors. Among the hardware implementations of…
We demonstrate the reduction of critical spin-transfer torque (STT) switching currents in Co-Fe-B/MgO based magnetic tunnel junctions (MTJ) with perpendicular magnetization anisotropy (PMA). The junctions yield tunnel magnetoresistance…
We propose spin transfer torque--magnetoresistive random access memory (STT-MRAM) based on magneto-resistance and spin transfer torque physics of band-pass spin filtering. Utilizing the electronic analogs of optical phenomena such as…
Voltage-driven spin transfer torque in a magnetic tunnel junction comprising magnetic insulating electrodes is studied theoretically. In contrast with the conventional magnetic tunnel junctions comprising transition metal ferromagnets, the…
Recent studies on the magneto-transport properties of topological insulators (TI) have attracted great attention due to the rich spin-orbit physics and promising applications in spintronic devices. Particularly the strongly spin-moment…
Spiking neural networks (SNNs) are promising for edge sensing due to their event-driven computation and temporal filtering capability. However, standard leaky integrate-and-fire (LIF) neurons communicate only through binary spikes, which…
Magnetic tunnel junctions (MTJs) based on ferromagnets are canonical devices in spintronics, with wide-ranging applications in data storage, computing, and sensing. They simultaneously exhibit mechanisms for electrical detection of magnetic…
The notion of a spin field effect transistor, where transistor action is realized by manipulating the spin degree of freedom of charge carriers instead of the charge degree of freedom, has captivated researchers for at least three decades.…
Due to the fundamental limit to reducing power consumption of running deep learning models on von-Neumann architecture, research on neuromorphic computing systems based on low-power spiking neural networks using analog neurons is in the…
The primary impediment to continued improvement of traditional charge-based electronic devices in accordance with Moore's law is the excessive energy dissipation that takes place in the devices during switching of bits. One very promising…
Recently there has been increasing activity to build dedicated Ising Machines to accelerate the solution of combinatorial optimization problems by expressing these problems as a ground-state search of the Ising model. A common theme of such…
Spin transfer - the transfer of angular momentum from spin-polarized electrical current to magnetic materials - has been extensively researched as an efficient mechanism for the electronic manipulation of the static and dynamic states in…
The next wave of on-device AI will likely require energy-efficient deep neural networks. Brain-inspired spiking neural networks (SNN) has been identified to be a promising candidate. Doing away with the need for multipliers significantly…