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Recently several device and circuit design techniques have been explored for applying nano-magnets and spin torque devices like spin valves and domain wall magnets in computational hardware. However, most of them have been focused on…
Researchers from Intel Corporation recently proposed "Magneto-Electric Spin Orbit (MESO)" logic as a new strategy for beyond-CMOS electronics [1]. The Intel researchers project that this concept has the potential to reduce the switching…
The field-free spin-orbit torque induced 180{\deg} reorientation of perpendicular magnetization is beneficial for the high performance magnetic memory. The antiferromagnetic material (AFM) can provide higher operation speed than the…
Recently, interest in programmable photonics integrated circuits has grown as a potential hardware framework for deep neural networks, quantum computing, and field programmable arrays (FPGAs). However, these circuits are constrained by the…
Magnetic skyrmions are promising candidates for logic-in-memory applications, intrinsically merging high density non-volatile data storage with computing capabilities, owing to their nanoscale size, fast motion, and mutual repulsions.…
Antiferromagnetic (AFM) materials are a pathway to spintronic memory and computing devices with unprecedented speed, energy efficiency, and bit density. Realizing this potential requires AFM devices with simultaneous electrical writing and…
Memory devices operating due to the fast proton transfer (PT) process are proposed by means of the first-principles calculations. Writing an information is performed using the electrostatic potential of the scanning tunneling microscopy…
Ferroelectric materials with switchable electric polarization hold great promise for a plethora of emergent applications, such as post-Moore's law nanoelectronics, beyond-Boltzmann transistors, non-volatile memories, and above-bandgap…
Charge-to-spin and spin-to-charge conversion mechanisms in high spin-orbit materials are the new frontier of memory devices. They operate via spin-orbit torque (SOT) switching of a magnetic electrode, driven by an applied charge current. In…
Spintronic devices based on antiferromagnetic (AFM) materials hold the promise of fast switching speeds and robustness against magnetic fields. Different device concepts have been predicted and experimentally demonstrated, such as…
This project explores the use of non-volatile synapses in neuromorphic computing for pattern recognition tasks through a comprehensive simulation-based approach. The main approach is through spintronic synapses, which leverage the…
In this letter, we show that Giant Spin Hall Effect (GSHE) MRAM can enable better energy- delay and voltage performance than traditional MTJ based spin torque devices at scaled nanomagnet dimensions (10-30 nm). Firstly, we derive the effect…
A superconducting loop stores persistent current without any ohmic loss, making it an ideal platform for energy efficient memories. Conventional superconducting memories use an architecture based on Josephson junctions (JJs) and have…
We present a nanomechanical device design to be used in a non-volatile mechanical memory point. The structure is composed of a suspended slender nanowire (width : 100nm, thickness 430nm length : 8 to 30$\mu$m) clamped at its both ends.…
Microelectromechanical systems (MEMS) can offer a competitive alternative for conventional technology in electrical precision measurements. This article summarises recent work in development of MEMS solutions for electrical metrology.…
The human brain achieves exceptional energy efficiency by co-locating memory and processing, yet reproducing this principle in hardware remains challenging because many neuromorphic devices require standby power, offer limited…
The increasing need to store large amounts of information with an ultra-dense, reliable, low power and low cost memory device is driving aggressive efforts to improve upon current perpendicular magnetic recording technology. However, the…
In recent years, the energy consumption of computing systems has increased and a large fraction of this energy is consumed in main memory. Towards this, researchers have proposed use of non-volatile memory, such as phase change memory…
Compute-in-memory (CiM) is a promising solution for addressing the challenges of artificial intelligence (AI) and the Internet of Things (IoT) hardware such as 'memory wall' issue. Specifically, CiM employing nonvolatile memory (NVM)…
We present a design-scheme for ultra-low power neuromorphic hardware using emerging spin-devices. We propose device models for 'neuron', based on lateral spin valves and domain wall magnets that can operate at ultra-low terminal voltage of…