Turns out thin film magnetic materials with in-plane magnetic anisotropy could be useful solutions to communicate to space vehicles. Check out our new publication with Andrew Maicke and Leopoldo Hernandez, Ph.D.

pubs.aip.org/aip/jap/arti...

#technology #engineering #future #science #utaustin

Graphene In-Sensor Compute Device for Plant Hydration Monitoring Analog sensing devices that exhibit artificial synaptic behavior offer a promising path toward scalable and energy-efficient environmental sensing. In this work, we report graphene-based, leaf-gated i...

Check out our latest publication on developing graphene-leaf devices that can monitor plant hydration while providing neural network in-sensor compute capabilities!

pubs.acs.org/doi/10.1021/...

#neuromorphic #computing #tech #nanotech #ai #graphene #physics #engineeringeducation #utaustin

LEAD: Literature Enhanced Ab Initio Discovery of Nitride Dusting Layers for Enhanced Tunnel Magnetoresistance and Lower Resistance Magnetic Tunnel Junctions Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance-area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanc...

New publication carried out by undergraduate Sabiq Islam in collaboration with Shehrin Sayed and TSMC!

advanced.onlinelibrary.wiley.com/doi/10.1002/...

#computing #nanotech #ai #spintronics #engineering #future #science #technology #research #physics #engineeringeducation #utaustin #education

KXAN local news coverage on our work with Artur M. Pinto!

www.kxan.com/news/science...

Proud of our three talks last week at #MMM2025:

Harrison Jin, Sam Liu, and Sabiq Islam!

High‐Rate Deposition and Characterization Study of CoZrO Films for On‐Chip Power Applications This study introduces a high-rate reactive sputtering process for CoZrO films, aimed at large-scale production of on-chip magnetic components compatible with complementary metal oxide semiconductor (...

Check out our just-published work on high-rate deposition and characterization of CoZrO for on-chip power!

advanced.onlinelibrary.wiley.com/doi/abs/10.1...

#neuromorphic #computing #tech #technology #nanotech #nanotechnology #ai #artificialintelligence #spintronics #electricalengineering

Voltage-controlled skyrmion manipulation chambers for neuromorphic computing Voltage-controlled magnetic skyrmion manipulation has emerged as a promising approach for designing high-density and low-power magnetic devices. This …

Zulfidin (Bobojon) Khodzhaev wrote a comprehensive review on voltage-controlled skyrmions in chambers for neuromorphic computing, you can check it out here:

www.sciencedirect.com/science/arti...

#neuromorphic #computing #tech #technology #nanotech #ai #spintronics #electricalengineering

Magnets Emulate Neurons for Next-Generation Computing In the quest to develop new computing tech — electronics that can think like the human brain — researchers from The University of Texas have made breakthroughs.

See the work of INC Lab students and alumni Can Cui, Thomas Leonard, Nicholas Zogbi, and Sam Liu highlighted in UT Cockrell School of Engineering’s article, “Magnets Emulate Neurons for Next-Generation Computing!”

cockrell.utexas.edu/news/archive...

Congratulations to Sam Liu for receiving the Ben Streetman Senior Award “For Outstanding Research by a Graduate Student in Electronic and Photonic Materials and Devices."

Shape Anisotropy-Dependent Leaking in Magnetic Neurons for Bio-Mimetic Neuromorphic Computing Spiking neural networks seek to emulate biological computation through interconnected artificial neuron and synapse devices. Spintronic neurons can leverage magnetization physics to mimic biological n...

We have an exciting paper just published on leaky, integrate, and fire (LIF) artificial neurons using magnetic domain walls, read out by magnetic tunnel junctions (MTJs)!

Click on the link below to read!

pubs.acs.org/doi/10.1021/...

#neuromorphic #computing #tech #utaustin

Spintronic Artificial Neurons Showing Integrate-and-Fire Behavior with Reliable Cycling Operation The rich dynamics of magnetic materials makes them promising candidates for neural networks that, like the brain, take advantage of dynamical behaviors to efficiently compute. Here, we experimentally show that integrate-and-fire neurons can be achieved using a magnetic nanodevice consisting of a domain wall racetrack and magnetic tunnel junctions in a way that has reliable, continuous operation over many cycles. We demonstrate the domain propagation in the domain wall racetrack (integration), reading using a magnetic tunnel junction (fire), and reset as the domain is ejected from the racetrack with over 100 continuous cycles. Both the pulse amplitude and pulse number encoding are shown. By simulating a spiking neural network task, we benchmark the performance of the devices against an ideal leaky, integrate-and-fire neuron, showing that the spintronic neuron can match the performance of the ideal. These results achieve demonstration of reliable integrated-fire reset in domain wall-magnetic tunnel junction-based neuron devices for neuromorphic computing.

Our paper on magnetic domain wall based integrate-and-fire neurons is now published in Nano Letters! The lead Ph.D. student is Can Cui with co-authors Sam Liu and Jaesuk Kwon (Ph.D). Click on the link below to read it!

pubs.acs.org/doi/full/10....

#neuromorphic #computing #tech #nanotech