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Search Publications by: Jabez J McClelland (Fed)

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Displaying 1 - 25 of 139

Measurement-driven Langevin modeling of superparamagnetic tunnel junctions

July 23, 2024
Author(s)
Liam Pocher, Temitayo Adeyeye, Sidra Gibeault, Philippe Talatchian, Ursula Ebels, Daniel Lathrop, Jabez J. McClelland, Mark Stiles, Advait Madhavan, Matthew Daniels
Superparamagnetic tunnel junctions are important devices for a range of emerging technologies, but most existing compact models capture only their mean switching rates. Capturing qualitatively accurate analog dynamics of these devices will be important as

Measurement-driven neural-network training for integrated magnetic tunnel junction arrays

May 14, 2024
Author(s)
William Borders, Advait Madhavan, Matthew Daniels, Vasileia Georgiou, Martin Lueker-Boden, Tiffany Santos, Patrick Braganca, Mark Stiles, Jabez J. McClelland, Brian Hoskins
The increasing scale of neural networks needed to support more complex applications has led to an increasing requirement for area- and energy-efficient hardware. One route to meeting the budget for these applications is to circumvent the von Neumann

Programmable electrical coupling between stochastic magnetic tunnel junctions

March 29, 2024
Author(s)
Sidra Gibeault, Temitayo Adeyeye, Liam Pocher, Daniel Lathrop, Matthew Daniels, Mark Stiles, Jabez J. McClelland, William Borders, Jason Ryan, Philippe Talatchian, Ursula Ebels, Advait Madhavan
Superparamagnetic tunnel junctions (SMTJs) are promising sources of randomness for compact and energy efficient implementations of various probabilistic computing techniques. When augmented with electronic circuits, the random telegraph fluctuations of the

Experimental demonstration of a robust training method for strongly defective neuromorphic hardware

December 11, 2023
Author(s)
William Borders, Advait Madhavan, Matthew Daniels, Vasileia Georgiou, Martin Lueker-Boden, Tiffany Santos, Patrick Braganca, Mark Stiles, Jabez J. McClelland, Brian Hoskins
Neural networks are increasing in scale and sophistication, catalyzing the need for efficient hardware. An inevitability when transferring neural networks to hardware is that non-idealities impact performance. Hardware-aware training, where non-idealities

Neural networks three ways: unlocking novel computing schemes using magnetic tunnel junction stochasticity

September 28, 2023
Author(s)
Matthew Daniels, William Borders, Nitin Prasad, Advait Madhavan, Sidra Gibeault, Temitayo Adeyeye, Liam Pocher, Lei Wan, Michael Tran, Jordan Katine, Daniel Lathrop, Brian Hoskins, Tiffany Santos, Patrick Braganca, Mark Stiles, Jabez J. McClelland
Due to their interesting physical properties, myriad operational regimes, small size, and industrial fabrication maturity, magnetic tunnel junctions are uniquely suited for unlocking novel computing schemes for in-hardware neuromorphic computing. In this

Magnetic tunnel junction-based crossbars: improving neural network performance by reducing the impact of non-idealities

July 13, 2023
Author(s)
William Borders, Nitin Prasad, Brian Hoskins, Advait Madhavan, Matthew Daniels, Vasileia Gerogiou, Tiffany Santos, Patrick Braganca, Mark Stiles, Jabez J. McClelland
Increasingly higher demand in chip area and power consumption for more sophisticated artificial neural networks has catalyzed efforts to develop architectures, circuits, and devices that perform like the human brain. However, many novel device technologies

Characterization of Noise in CMOS Ring Oscillators at Cryogenic Temperatures

July 12, 2023
Author(s)
Prashansa Mukim, Pragya Shrestha, Advait Madhavan, Nitin Prasad, Jason Campbell, Forrest Brewer, Mark Stiles, Jabez J. McClelland
Allan deviation provides a means to characterize the time-dependence of noise in oscillators and potentially identify the source characteristics. Measurements on a 130nm, 7-stage ring oscillator show that the Allan deviation declines from 300K to 150K as

Implementation of a Binary Neural Network on a Passive Array of Magnetic Tunnel Junctions

July 18, 2022
Author(s)
Jonathan Goodwill, Nitin Prasad, Brian Hoskins, Matthew Daniels, Advait Madhavan, Lei Wan, Tiffany Santos, Michael Tran, Jordan Katine, Patrick Braganca, Mark Stiles, Jabez J. McClelland
The increasing scale of neural networks and their growing application space have produced a demand for more energy and memory efficient artificial-intelligence-specific hardware. Avenues to mitigate the main issue, the von Neumann bottleneck, include in

Spatially Resolved Potential and Li-Ion Distributions Reveal Performance-Limiting Regions in Solid-State Batteries

October 19, 2021
Author(s)
Elliot Fuller, Evgheni Strelcov, Jamie Weaver, Michael Swift, Joshua Sugar, Andrei Kolmakov, Nikolai Zhitenev, Jabez J. McClelland, Yue Qi, Joseph Dura, Alec Talin
The performance of solid-state electrochemical systems is intimately tied to the potential and lithium distributions across electrolyte–electrode junctions that give rise to interface impedance. Here, we combine two operando methods, Kelvin probe force

Mutual control of stochastic switching for two electrically coupled superparamagnetic tunnel junctions

August 19, 2021
Author(s)
Philippe Talatchian, Matthew Daniels, Advait Madhavan, Matthew Pufall, Emilie Jue, William Rippard, Jabez J. McClelland, Mark Stiles
Superparamagnetic tunnel junctions (SMTJs) are promising sources for the randomness required by some compact and energy-efficient computing schemes. Coupling them gives rise to collective behavior that could be useful for cognitive computing. We use a

Impact ionization-induced bistability in CMOS transistors at cryogenic temperatures for capacitorless memory applications

July 29, 2021
Author(s)
Alexander Zaslavsky, Curt A. Richter, Pragya Shrestha, Brian Hoskins, Son Le, Advait Madhavan, Jabez J. McClelland
Cryogenic operation of complementary metal oxide semiconductor (CMOS) silicon transistors is crucial for quantum information science, but it brings deviations from standard transistor operation. Here we report on sharp current jumps and stable hysteretic

A System for Validating Resistive Neural Network Prototypes

July 27, 2021
Author(s)
Brian Hoskins, Mitchell Fream, Matthew Daniels, Jonathan Goodwill, Advait Madhavan, Jabez J. McClelland, Osama Yousuf, Gina C. Adam, Wen Ma, Muqing Liu, Rasmus Madsen, Martin Lueker-Boden
Building prototypes of heterogeneous hardware systems based on emerging electronic, magnetic, and photonic devices is an increasingly important area of research. On the face of it, the novel implementation of these systems, especially for online learning

Magneto-optical trapping using planar optics

January 29, 2021
Author(s)
William McGehee, Wenqi Zhu, Daniel Barker, Daron Westly, Alexander Yulaev, Nikolai Klimov, Amit Agrawal, Stephen Eckel, Vladimir Aksyuk, Jabez J. McClelland
Laser-cooled atoms are a key component of many calibration-free measurement platforms— including clocks, gyroscopes, and gravimeters—and are a promising technology for quantum networking and quantum computing. The optics and vacuum hardware required to

Transport dynamics in a high-brightness magneto-optical-trap Li ion source

September 15, 2020
Author(s)
Jamie Gardner, William R. McGehee, Mark D. Stiles, Jabez J. McClelland
Laser-cooled gases offer an alternative to tip-based methods for generating high brightness ions for focused ion beam applications. These sources produce ions by photoionization of ultracold neutral atoms, where the narrow velocity distribution associated

Streaming Batch Eigenupdates for Hardware Neural Networks

August 6, 2019
Author(s)
Brian D. Hoskins, Matthew W. Daniels, Siyuan Huang, Advait Madhavan, Gina C. Adam, Nikolai B. Zhitenev, Jabez J. McClelland, Mark D. Stiles
Neuromorphic networks based on nanodevices, such as metal oxide memristors, phase change memories, and flash memory cells, have generated considerable interest for their increased energy efficiency and density in comparison to graphics processing units

Engineered Sulfur-MoS2-Graphene Heterostructure Cathodes for Diagnostics of Nanoscale Electrochemical Processes in High Energy Density Li-S Batteries

August 5, 2019
Author(s)
Vladimir P. Oleshko, William R. McGehee, Saya Takeuchi, Siyuan Zhang, Andrei A. Kolmakov, Jabez J. McClelland, Christopher L. Soles
Lithium-sulfur (Li-S) batteries have recently attracted enormous attention because of high theoretical specific energy (2600 Wh kg-1) and high specific capacity (1672 mAhg-1), as well as the low cost, natural abundance, and nontoxicity of elemental sulfur

Direct-write Lithiation of Silicon Using a Focused Ion Beam of Li+

July 8, 2019
Author(s)
William R. McGehee, Evgheni Strelcov, Vladimir P. Oleshko, Christopher L. Soles, Nikolai B. Zhitenev, Jabez J. McClelland
Electrochemical processes that govern the performance of lithium ion batteries involve numerous parallel reactions and interfacial phenomena that complicate the microscopic understanding of these systems. As a new way to study the behavior of ion transport

Spontaneous current constriction in threshold switching devices

April 9, 2019
Author(s)
Jonathan Goodwill, Georg Ramer, Dasheng Li, Brian Hoskins, Georges Pavlidis, Jabez J. McClelland, Andrea Centrone, James A. Bain, Marek Skowronski
Threshold switching devices exhibit extremely non-linear current-voltage characteristics, which are of increasing importance for a number of applications including solid-state memories and neuromorphic circuits. It has been proposed that such non-linear

Characterization of a high-brightness, laser-cooled Li+ ion source

February 20, 2019
Author(s)
Jamie R. Gardner, William R. McGehee, Jabez J. McClelland
Ion sources based on laser cooling have recently provided new pathways to high-resolution microscopy, ion milling, and ion implantation. Here, we present the design and detailed characterization of Li-7 magneto-optical trap ion source (MOTIS) with a peak

Defect Evolution of Ion-Exposed Single-Wall Carbon Nanotubes

January 3, 2019
Author(s)
Jana Kalbacova, Elias J. Garratt, Raul D. Rodriguez, Angela R. Hight Walker, Kevin A. Twedt, Jeffrey Fagan, Teresa I. Madeira, Jabez J. McClelland, Babak Nikoobakht, Dietrich R. Zahn
A systematic evaluation of defects is essential to understand and engineer device properties and applications. Raman spectroscopy is employed for the characterization of carbon nanomaterials in particular to quantitatively evaluate defects from the

Stateful characterization of resistive switching TiO2 with electron beam induced currents

December 7, 2017
Author(s)
Brian D. Hoskins, Gina C. Adam, Evgheni Strelcov, Nikolai B. Zhitenev, Andrei A. Kolmakov, Dmitri B. Strukov, Jabez J. McClelland
Metal oxide resistive switches have become increasingly important as possible artificial synapses in next generation neuromorphic networks. Nevertheless, there is still no codified set of tools for studying fundamental properties of the devices. To this

High-brightness Cs focused ion beam from a cold-atomic-beam ion source

May 2, 2017
Author(s)
Adam V. Steele, Andrew Schwarzkopf, Jabez J. McClelland, Brenton Knuffman
We present measurements of focal spot size and brightness in a focused ion beam system utilizing a laser-cooled atomic beam source of Cs ions. Spot sizes as small as (2.1 ± 0.2) nm (one standard deviation) and brightness values as high as (1.3 ± 0.1) x 107