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Search Publications by: Mark D. Stiles (Fed)

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Displaying 1 - 25 of 184

Large Exotic Spin Torques in Antiferromagnetic Iron Rhodium

August 29, 2022
Jonathan Gibbons, Takaaki Dohi, Vivek Amin, Fei Xue, Haowen Ren, Hanu Arava, Hilal Saglam, Yuzi Liu, John Pearson, Nadya Mason, Amanda Petford-Long, Paul M. Haney, Soho Shim, Jun-wen Xu, Mark Stiles, Eric Fullerton, Andrew Kent, Shunsuke Fukami, Axel Hoffmann
Spin torque is a promising tool for driving magnetization dynamics for novel computing techniques. These torques can be easily produced by spin-orbit effects, but for most conventional spin source materials, a high degree of crystal symmetry limits the

Quantum materials for energy-efficient neuromorphic computing: Opportunities and challenges

July 19, 2022
Axel Hoffmann, Shriram Ramanathan, Julie Grollier, Andrew Kent, Marcelo Rozenberg, Ivan Schuller, Oleg Shpyrko, Robert Dynes, Yeshaiahu Fainman, Alex Frano, Eric Fullerton, Giulia Galli, Vitaliy Lomakin, Shyue Ping Ong, Amanda K. Petford-Long, Jonathan A. Schuller, Mark Stiles, Yayoi Takamura, Yimei Zhu
Neuromorphic computing approaches become increasingly important as we address future needs for efficiently processing massive amounts of data. The unique attributes of quantum materials can help address these needs by enabling new energy-efficient device

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

July 18, 2022
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

Easy-plane spin Hall nano-oscillators as spiking neurons for neuromorphic computing

January 10, 2022
Danijela Markovic, Matthew Daniels, Pankaj Sethi, Andrew Kent, Mark Stiles, Julie Grollier
We show analytically using a macrospin approximation that easy-plane spin Hall nano-oscillators excited by a spin-current polarized perpendicularly to the easy-plane have phase dynamics analogous to that of Josephson junctions. This allows them to

Artifacts That Could Be Misinterpreted as Ballistic Magnetoresistance

October 12, 2021
William F. Egelhoff Jr., L Gan, Erik B. Svedberg, Cedric J. Powell, Alexander J. Shapiro, Robert McMichael, J Mallett, Thomas P. Moffat, Mark D. Stiles
Theoretical physics suggests that very large magnetoresistance (MR) values might be found in certain magnetic nanocontacts if a magnetic domain wall could be localized in them with a length scale that would allow conduction electrons to transit the wall

The Suppression of Orange-Peel Coupling in Magnetic Tunnel Junctions by Pre-Oxidation

October 12, 2021
William F. Egelhoff Jr., Robert McMichael, Cindi L. Dennis, Mark D. Stiles, Alexander J. Shapiro, Brian B. Maranville, Cedric J. Powell
We have have found that pre-oxidation of the bottom Co electrode in magnetic tunnel junctions (MTJs) very effectively suppresses orange-peel coupling. The result is a free layer that is much softer. Work by others has demonstrated that pre-oxidation is

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

August 19, 2021
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

Reservoir computing leveraging the transient non-linear dynamics of spin-torque nano-oscillators

August 6, 2021
Mathieu Riou, Jacob Torrejon, Flavio Abreu Araujo, Sumito Tsunegi, Guru Khalsa, Damien Querlioz, Paolo Bortolotti, Nathan Leroux, Danijela Markovic, Vincent Cros, K. Yakushiji, Akio Fukushima, Hitoshi Kubota, Shinji Yuasa, Mark D. Stiles, Julie Grollier
Present artificial intelligence algorithms require extensive computations to emulate the behavior of large neural networks, operating current computers near their limits, which leads to high energy costs. A possible solution to this problem is the

Phase-resolved electrical detection of coherently coupled magnonic devices

May 20, 2021
Yi Li, Chenbo Zhao, Vivek P. Amin, Zhizhi Zhang, Michael Vogel, Yuzan Xiong, Joseph Sklenar, Ralu Divan, John Pearson, Wei Zhang, Mark D. Stiles, Axel Hoffmann, Valentine Novosad
We demonstrate the electrical detection of a strongly coupled magnon-magnon hybrid system based on yttrium iron garnet/permalloy (YIG/Py) bilayer devices. Direct microwave current injection through the conductive Py layer drives the hybrid dynamics

Roadmap of spin-orbit torques

May 10, 2021
Qiming Shao, Li Peng, Luqiao Liu, Hyunsoo Yang, Shunsuke Fukami, Armin Razavi, Hao Wu, Kang L. Wang, Frank Freimuth, Yuriy Mokrousov, Mark D. Stiles, Satoru Emori, Axel Hoffmann, Johan Akerman, Kaushik Roy, Jian-Ping Wang, See-Hun Yang, Kevin Garello, Wei Zhang
Spin-orbit torque (SOT) is an emerging technology that enables the efficient manipulation of spintronic devices. The initial processes of interest in SOTs involved electric fields, spin- orbit coupling, conduction electron spins and magnetization. More

Topological Control of Magnetic Textures

February 25, 2021
Hanu Arava, Frank P. Barrows, Mark D. Stiles, Amanda K. Petford-Long
A micromagnetic study is carried out on the role of using topology to stabilize different magnetic textures, such as a vortex or an anti-vortex state, in a magnetic heterostructure consisting of a Permalloy disk coupled to a set of nanomagnetic bars. The

Temporal Memory with Magnetic Racetracks

December 1, 2020
Hamed Vakili, Mohammed N. Sakib, Samiran Ganguly, Mircea Stan, Matthew Daniels, Advait Madhavan, Mark D. Stiles, Avik W. Ghosh
Race logic is a relative timing code that represents information in a wavefront of digital edges on a set of wires in order to accelerate dynamic programming and machine learning algorithms. Skyrmions, bubbles, and domain walls are mobile magnetic

Interfacial spin-orbit torques

October 21, 2020
Vivek P. Amin, Paul M. Haney, Mark D. Stiles
Spin-orbit torques offer a promising mechanism to electrically control magnetization dynamics in nanoscale heterostructures. While spin-orbit torques occur predominately at interfaces, the physical mechanisms underlying these torques can originate in both

Storing and retrieving wavefronts with resistive temporal memory

October 10, 2020
Advait Madhavan, Mark D. Stiles
We extend the reach of temporal computing schemes by developing a memory for multi-channel temporal patterns or "wavefronts." This temporal memory re-purposes conventional one-transistor-one-resistor (1T1R) memristor crossbars for use in an arrival-time

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

September 15, 2020
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

Manipulation of Coupling and Magnon Transport in Magnetic Metal-Insulator Hybrid Structures

June 15, 2020
Yabin Fan, Patrick Quarterman, Joseph Finley, Jiahao Han, Pengxiang Zhang, Justin T. Hou, Mark D. Stiles, Alexander Grutter, Luqiao Liu
Ferromagnetic metals and insulators are widely used for generation, control and detection of magnon spin signals. Most magnonic structures are based primarily on either magnetic insulators or ferromagnetic metals, while heterostructures integrating both of

Streaming Batch Gradient Tracking for Neural Network Training

April 3, 2020
Siyuan Huang, Brian D. Hoskins, Matthew W. Daniels, Mark D. Stiles, Gina C. Adam
Faster and more energy efficient hardware accelerators are critical for machine learning on very large datasets. The energy cost of performing vector-matrix multiplication and repeatedly moving neural network models in and out of memory motivates a search

Coherent spin pumping in a strongly coupled magnon-magnon hybrid system

March 17, 2020
Yi Li, Wei Cao, Vivek P. Amin, Zhizhi Zhang, Jonathan Gibbons, Joseph Sklenar, John Pearson, Paul M. Haney, Mark D. Stiles, William E. Bailey, Valentine Novosad, Axel Hoffmann, Wei Zhang
We have experimentally identified coherent spin pumping acting as a dampinglike coupling in the magnon-magnon hybrid modes of permalloy/yttrium iron garnet (Py/YIG) bilayers. Using broadband ferromagnetic resonance, an ''avoided crossing" is observed well

Energy-efficient stochastic computing with superparamagnetic tunnel junctions

March 5, 2020
Matthew W. Daniels, Advait Madhavan, Philippe Talatchian, Alice Mizrahi, Mark D. Stiles
Stochastic computing has been limited by the inaccuracies introduced by correlations between the pseudorandom bitstreams used in the calculation. We hybridize a stochastic version of magnetic tunnel junctions with basic CMOS logic gates to create a

Neuromorphic Spintronics

March 2, 2020
Julie Grollier, Damien Querlioz, Kerem Camsari, Karin Everschor-Sitte, Shunsuke Fukami, Mark D. Stiles

Role of non-linear data processing on speech recognition task in the framework of reservoir computing

January 15, 2020
Flavio Abreu Araujo, Mathieu Riou, Jacob Torrejon, Sumito Tsunegi, Damien Querlioz, K. Yakushiji, Akio Fukushima, Hitoshi Kubota, Shinji Yuasa, Mark D. Stiles, Julie Grollier
The reservoir computing neural network architecture is widely used to test hardware systems for neuromorphic computing. One of the preferred tasks for bench-marking such devices is automatic speech recognition (ASR). However, this task requires acoustic

Temporal pattern recognition with delayed feedback spin-torque nano-oscillators

August 23, 2019
Mathieu Riou, Jacob Torrejon, B. Garitaine, Flavio Abreu Araujo, Paolo Bortolotti, Vincent Cros, Sumito Tsunegi, K. Yakushiji, Akio Fukushima, Hitoshi Kubota, Shinji Yuasa, Damien Querlioz, Mark D. Stiles, Julie Grollier
The recent demonstration of neuromorphic computing with spin-torque nano-oscillators has opened a path to energy efficient data processing. The success of this demonstration hinged on the intrinsic short-term memory of the oscillators. In this study, we