Jayasimha Atulasimha, Ph.D.

Engineering Foundation Professor, Department of Mechanical and Nuclear Engineering | VCU College of Engineering

Richmond, VA, UNITED STATES

Professor Atulasimha researches nanomagnetic/spintronic memory and neuromorphic computing devices.

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Links (1)

Magnetism, Magnetic Materials & Magnetic Devices Lab

Biography

Jayasimha Atulasimha is a Qimonda Professor of Mechanical and Nuclear
Engineering with a courtesy appointment in Electrical and Computer Engineering at the Virginia
Commonwealth University. He has authored or coauthored ~80 journal publications on
magnetostrictive materials, magnetization dynamics, spintronics and nanomagnetic computing.
His current research interests include nanomagnetism, spintronics, multiferroics, nanomagnetic
memory and neuromorphic computing devices. He is a fellow of the ASME, an IEEE Senior
Member and current chair for the TC on Spintronics, IEEE Nanotechnology Council.

Industry Expertise (2)

Research

Education/Learning

Areas of Expertise (5)

Spintronics and Nanomagnetism

Exploratory neuromorphic devices

Straintronics: Strian mediated electric field control of magnetism

Electric field (VCMA) control of skyrmions

Magnetic and multiferroic materials

Accomplishments (4)

Fellow of ASME (professional)

American Society of Mechanical Engineers

Senior Member of IEEE (professional)

Institute of Electrical and Electronics Engineers

NSF CAREER Award (professional)

National Science Foundation

Presidential Research Incentive Program Award (professional)

Awarded by Virginia Commonwealth University

Education (3)

University of Maryland: Ph.D., Aerospace Engineering 2006

University of Maryland: M.S., Aerospace Engineering 2003

Indian Institute of Technology - Madras: B.S., Mechanical Engineering 2001

Media Appearances (4)

Study reveals magnetic process that can lead to more energy-efficient memory in computers

Science Daily from original material published by VCU online

2020-06-30

Press for our article published in Nature Electronics, 2020

Engineering researchers develop a process that could make big data and cloud storage more energy efficient Read more at: https://phys.org/news/2016-11-big-cloud-storage-energy-efficient.html#jCp

Phys.org online

2016-11-30

"When you look at the energy reduction that this affords, it's a major change," said Jayasimha Atulasimha, Ph.D., Qimonda associate professor in the Department of Mechanical and Nuclear Engineering. "This has the potential to significantly reduce the energy consumption in switching non-volatile magnetic memory devices." Read more at: https://phys.org/news/2016-11-big-cloud-storage-energy-efficient.html#jCp

'Straintronic spin neuron' may greatly improve neural computing

Phys.org

2015-07-08

"Researchers have proposed a new type of artificial neuron called a 'straintronic spin neuron' that could serve as the basic unit of artificial neural networks—systems modeled on human brains that have the ability to compute, learn, and adapt. Compared to previous designs, the new artificial neuron is potentially orders of magnitude more energy-efficient, more robust against thermal degradation, and fires at a faster rate. The researchers, Ayan K. Biswas, Professor Jayasimha Atulasimha, and Professor Supriyo Bandyopadhyay at Virginia Commonwealth University in Richmond, have published a paper on the straintronic spin neuron in a recent issue of Nanotechnology..."

Researchers aim for energy-harvesting CPUs

EE Times online

2011-09-01

According to Bandyopadhyay and Jayasimha Atulasimha, an assistant professor of mechanical and nuclear engineering in the VCU School of Engineering who serves as co-principal investigator on the project, this research could lead to a type of digital computing system ideal for medical devices such as processors implanted in an epileptic patient’s brain that monitor brain signals to warn of impending seizures...

Selected Articles (5)

Creation and annihilation of non-volatile fixed magnetic skyrmions using voltage control of magnetic anisotropy

Nature Electronics

Dhritiman Bhattacharya, Seyed Armin Razavi, Hao Wu, Bingqian Dai, Kang L. Wang & Jayasimha Atulasimha

2020-06-29

Magnetic skyrmions are topological spin textures that could be used to create magnetic memory and logic devices. Such devices typically rely on current-controlled motion of skyrmions, but using skyrmions that are fixed in space could lead to more compact and energy-efficient devices. Here we report the manipulation of fixed magnetic skyrmions using voltage-controlled magnetic anisotropy. We show that skyrmions can be stabilized in antiferromagnet/ferromagnet/oxide heterostructure films without any external magnetic field due to an exchange bias field. The isolated skyrmions are annihilated or formed by applying voltage pulses that increase or decrease the perpendicular magnetic anisotropy, respectively. We also show that skyrmions can be created from chiral domains by increasing the perpendicular magnetic anisotropy of the system. Our experimental findings are corroborated using micromagnetic simulations.

Voltage control of domain walls in magnetic nanowires for energy-efficient neuromorphic devices

IOP Nanotechnology

Md Ali Azam, Dhritiman Bhattacharya, Damien Querlioz, Caroline A Ross and Jayasimha Atulasimha

2020-01-16

An energy-efficient voltage-controlled domain wall (DW) device for implementing an artificial neuron and synapse is analyzed using micromagnetic modeling in the presence of room temperature thermal noise. By controlling the DW motion utilizing spin transfer or spin–orbit torques in association with voltage generated strain control of perpendicular magnetic anisotropy in the presence of Dzyaloshinskii–Moriya interaction, different positions of the DW are realized in the free layer of a magnetic tunnel junction to program different synaptic weights. The feasibility of scaling of such devices is assessed in the presence of thermal perturbations that compromise controllability. Additionally, an artificial neuron can be realized by combining this DW device with a CMOS buffer. This provides a possible pathway to realize energy-efficient voltage-controlled nanomagnetic deep neural networks that can learn in real time.

Skyrmion-Mediated Voltage-Controlled Switching of Ferromagnets for Reliable and Energy-Efficient Two-Terminal Memory

ACS Appl. Mater. Interfaces

Dhritiman Bhattacharya and Jayasimha Atulasimha

2018-04-27

We propose a two-terminal nanomagnetic memory element based on magnetization reversal of a perpendicularly magnetized nanomagnet employing a unipolar voltage pulse that modifies the perpendicular anisotropy of the system. Our work demonstrates that the presence of Dzyaloshinskii–Moriya interaction can create an alternative route for magnetization reversal that obviates the need for utilizing precessional magnetization dynamics as well as a bias magnetic field that are employed in traditional voltage control of magnetic anisotropy (VCMA)-based switching of perpendicular magnetization. We show with extensive micromagnetic simulation, in the presence of thermal noise, that the proposed skyrmion-mediated VCMA switching mechanism is robust at room temperature leading to extremely low error switching while also being potentially 1–2 orders of magnitude more energy efficient than state-of-the-art spin transfer torque-based switching.

Experimental Clocking of Nanomagnets with Strain for Ultralow Power Boolean Logic

Nano Letters

Noel D'Souza, Mohammad Salehi Fashami, Supriyo Bandyopadhyay, Jayasimha Atulasimha

2016-01-08

Nanomagnetic implementations of Boolean logic have attracted attention because of their nonvolatility and the potential for unprecedented overall energy-efficiency. Unfortunately, the large dissipative losses that occur when nanomagnets are switched with a magnetic field or spin-transfer-torque severely compromise the energy-efficiency. Recently, there have been experimental reports of utilizing the Spin Hall effect for switching magnets, and theoretical proposals for strain induced switching of single-domain magnetostrictive nanomagnets, that might reduce the dissipative losses significantly. Here, we experimentally demonstrate, for the first time that strain-induced switching of single-domain magnetostrictive nanomagnets of lateral dimensions ∼200 nm fabricated on a piezoelectric substrate can implement a nanomagnetic Boolean NOT gate and steer bit information unidirectionally in dipole-coupled nanomagnet chains. On the basis of the experimental results with bulk PMN–PT substrates, we estimate that the energy dissipation for logic operations in a reasonably scaled system using thin films will be a mere ∼1 aJ/bit.

Acoustic-Wave-Induced Magnetization Switching of Magnetostrictive Nanomagnets from Single-Domain to Nonvolatile Vortex States

Nano Letters

Vimal Sampath, Noel D'Souza, Dhritiman Bhattacharya, Gary M. Atkinson, Supriyo Bandyopadhyay & Jayasimha Atulasimha

2016-08-26

We report experimental manipulation of the magnetic states of elliptical cobalt magnetostrictive nanomagnets (with nominal dimensions of ∼340 nm × 270 nm × 12 nm) delineated on bulk 128° Y-cut lithium niobate with acoustic waves (AWs) launched from interdigitated electrodes. Isolated nanomagnets (no dipole interaction with any other nanomagnet) that are initially magnetized with a magnetic field to a single-domain state with the magnetization aligned along the major axis of the ellipse are driven into a vortex state by acoustic waves that modulate the stress anisotropy of these nanomagnets. The nanomagnets remain in the vortex state until they are reset by a strong magnetic field to the initial single-domain state, making the vortex state nonvolatile. This phenomenon is modeled and explained using a micromagnetic framework and could lead to the development of extremely energy efficient magnetization switching methodologies for low-power computing applications.