66 citations · 248 across the 30 of their papers we have counts for
30 papers
Nanodiamond Sensing of Stray Fields during Domain Reversal
Kin On Ho, Hamza Abudayyeh, Andrew Perez +6
Quantitative measurement of nanoscale stray magnetic fields during domain reversal is important for understanding and optimizing magnetic memory and logic devices. Yet, achieving h…
Evaluation of Wafer-Scale SOT-MRAM for Analog Crossbar Array Applications
Samuel Liu, Chen-Yu Hu, Ming-Yuan Song +2
Analog crossbar arrays consisting of emerging memory devices can greatly alleviate the computational strain required by vector matrix multiplications for neural network application…
Skin Controlled Electronic and Neuromorphic Tattoos
Dmitry Kireev, Nandu Koripally, Samuel Liu +10
Wearable human activity sensors developed in the past decade show a distinct trend of becoming thinner and more imperceptible while retaining their electrical qualities, with graph…
Impact of external magnetic fields on STT-MRAM
Bernard Dieny, Sanjeev Aggarwal, Vinayak Bharat Naik +15
This application note discusses the working principle of spin-transfer torque magnetoresistive random access memory (STT-MRAM) and the impact that magnetic fields can have on STT-M…
Kinematic Model of Magnetic Domain Wall Motion for Fast, High-Accuracy Simulations
Kristi Doleh, Leonard Humphrey, Chandler M. Linseisen +8
Domain wall (DW) devices have garnered recent interest for diverse applications including memory, logic, and neuromorphic primitives; fast, accurate device models are therefore imp…
Domain Wall Magnetic Tunnel Junction Reliable Integrate and Fire Neuron
Can Cui1, Sam Liu, Jaesuk Kwon +1
In spiking neural networks, neuron dynamics are described by the biologically realistic integrate-and-fire model that captures membrane potential accumulation and above-threshold f…
Tunable Spike-Timing-Dependent Plasticity in Magnetic Skyrmion Manipulation Chambers
Zulfidin Khodzhaev, Jean Anne C. Incorvia
Magnetic skyrmions, as scalable and non-volatile spin textures, can dynamically interact with fields and currents, making them promising for unconventional computing. This paper pr…
Magnetic Tunnel Junction Random Number Generators Applied to Dynamically Tuned Probability Trees Driven by Spin Orbit Torque
Andrew Maicke, Jared Arzate, Samuel Liu +7
Perpendicular magnetic tunnel junction (pMTJ)-based true-random number generators (RNG) can consume orders of magnitude less energy per bit than CMOS pseudo-RNG. Here, we numerical…
Graphene-Based Artificial Dendrites for Bio-Inspired Learning in Spiking Neuromorphic Systems
Samuel Liu, Deji Akinwande, Dmitry Kireev +1
Analog neuromorphic computing systems emulate the parallelism and connectivity of the human brain, promising greater expressivity and energy efficiency compared to digital systems.…
Cascaded Logic Gates Based on High-Performance Ambipolar Dual-Gate WSe2 Thin Film Transistors
Xintong Li, Peng Zhou, Xuan Hu +6
Ambipolar dual-gate transistors based on two-dimensional (2D) materials, such as graphene, carbon nanotubes, black phosphorus, and certain transition metal dichalcogenides (TMDs),…
Stochastic Domain Wall-Magnetic Tunnel Junction Artificial Neurons for Noise-Resilient Spiking Neural Networks
Thomas Leonard, Samuel Liu, Harrison Jin +1
The spatiotemporal nature of neuronal behavior in spiking neural networks (SNNs) make SNNs promising for edge applications that require high energy efficiency. To realize SNNs in h…
Parallel Matrix Multiplication Using Voltage Controlled Magnetic Anisotropy Domain Wall Logic
Nicholas Zogbi, Samuel Liu, Christopher H. Bennett +4
The domain wall-magnetic tunnel junction (DW-MTJ) is a versatile device that can simultaneously store data and perform computations. These three-terminal devices are promising for…
Probabilistic Neural Circuits leveraging AI-Enhanced Codesign for Random Number Generation
Suma G. Cardwell, Catherine D. Schuman, J. Darby Smith +7
Stochasticity is ubiquitous in the world around us. However, our predominant computing paradigm is deterministic. Random number generation (RNG) can be a computationally inefficien…
Random Bitstream Generation using Voltage-Controlled Magnetic Anisotropy and Spin Orbit Torque Magnetic Tunnel Junctions
Samuel Liu, Jaesuk Kwon, Paul W. Bessler +6
Probabilistic computing using random number generators (RNGs) can leverage the inherent stochasticity of nanodevices for system-level benefits. The magnetic tunnel junction (MTJ) h…
Logical and Physical Reversibility of Conservative Skyrmion Logic
Xuan Hu, Benjamin W. Walker, Felipe García-Sánchez +6
Magnetic skyrmions are nanoscale whirls of magnetism that can be propagated with electrical currents. The repulsion between skyrmions inspires their use for reversible computing ba…
Metaplastic and Energy-Efficient Biocompatible Graphene Artificial Synaptic Transistors for Enhanced Accuracy Neuromorphic Computing
Dmitry Kireev, Samuel Liu, Harrison Jin +4
CMOS-based computing systems that employ the von Neumann architecture are relatively limited when it comes to parallel data storage and processing. In contrast, the human brain is…
All Electrical Control and Temperature Dependence of the Spin and Valley Hall Effect in Monolayer WSe2 Transistors
Xintong Li, Zhida Liu, Yihan Liu +4
Heavy metal-based two-dimensional van der Waals materials have a large, coupled spin and valley Hall effect (SVHE) that has potential use in spintronics and valleytronics. Optical…
Shape-Dependent Multi-Weight Magnetic Artificial Synapses for Neuromorphic Computing
Thomas Leonard, Samuel Liu, Mahshid Alamdar +8
In neuromorphic computing, artificial synapses provide a multi-weight conductance state that is set based on inputs from neurons, analogous to the brain. Additional properties of t…
High-Speed CMOS-Free Purely Spintronic Asynchronous Recurrent Neural Network
Pranav O. Mathews, Christian B. Duffee, Abel Thayil +8
Neuromorphic computing systems overcome the limitations of traditional von Neumann computing architectures. These computing systems can be further improved upon by using emerging t…
Skyrmion Logic Clocked via Voltage Controlled Magnetic Anisotropy
Benjamin W. Walker, Can Cui, Felipe Garcia-Sanchez +3
Magnetic skyrmions are exciting candidates for energy-efficient computing due to their non-volatility, detectability,and mobility. A recent proposal within the paradigm of reversib…
Controllable reset behavior in domain wall-magnetic tunnel junction artificial neurons for task-adaptable computation
Samuel Liu, Christopher H. Bennett, Joseph S. Friedman +3
Neuromorphic computing with spintronic devices has been of interest due to the limitations of CMOS-driven von Neumann computing. Domain wall-magnetic tunnel junction (DW-MTJ) devic…
Domain Wall Leaky Integrate-and-Fire Neurons with Shape-Based Configurable Activation Functions
Wesley H. Brigner, Naimul Hassan, Xuan Hu +7
Complementary metal oxide semiconductor (CMOS) devices display volatile characteristics, and are not well suited for analog applications such as neuromorphic computing. Spintronic…
Domain Wall-Magnetic Tunnel Junction Spin Orbit Torque Devices and Circuits for In-Memory Computing
Mahshid Alamdar, Thomas Leonard, Can Cui +8
There are pressing problems with traditional computing, especially for accomplishing data-intensive and real-time tasks, that motivate the development of in-memory computing device…
Adaptive cognition implemented with a context-aware and flexible neuron for next-generation artificial intelligence
Priyamvada Jadaun, Can Cui, Sam Liu +1
Neuromorphic computing mimics the organizational principles of the brain in its quest to replicate the brain's intellectual abilities. An impressive ability of the brain is its ada…