PIPages
Labs

Julius De Rojas

Oklahoma State University, OK·Physics

Magnetic devices are fast and use little energy, but once built, most of them can only do one fixed job. Computing hardware that learns and adapts, such as neuromorphic chips that mimic the brain, needs materials whose behavior can be reprogrammed after fabrication.

Fields

Physics

Materials Science

Engineering

Topics

magnonics

spin waves

magnons

Grants
1 known grant, through Jul 2029

What they work on

  1. Establish how voltage-driven migration of oxygen and lithium ions (magneto-ionics) changes spin-wave behavior in magnetic thin films, producing large changes that persist without power, measured with Brillouin light scattering and ferromagnetic resonance.
  2. Establish fast, reversible control of spin waves by straining magnetic layers with piezoelectric materials that deform under voltage, in magnetoelectric heterostructures (stacked layers that couple electricity and magnetism).
  3. Integrate ionic and strain control in patterned magnetic nanostructures to build adaptive magnonic devices with multiple states and neuromorphic, brain-like functionality, guided by micromagnetic simulations.
  4. Determine how ion motion and strain alter magnetic anisotropy, exchange interactions and spin-orbit coupling, combining synchrotron x-ray measurements with density functional theory and machine learning.

More about the research

This project proposes magnetic metamaterials, which are engineered structured materials, that are retuned with voltage rather than with power-hungry currents or magnetic fields. These materials carry information as spin waves, ripples in the alignment of electron spins known as magnons.

Why it matters

Adaptive magnetic materials controlled by low-power electric fields could support future neuromorphic computing, edge computing and reconfigurable radio-frequency systems. Because these materials are compatible with existing semiconductor technology, design principles from this work could help chip and device engineers build faster, lower-energy hardware that adapts to changing computing demands.

Known grants

From NIH and NSF research grants. Labs often have other funding we can't see.

Dual-Mode Control of Magnonic Metamaterials for Neuromorphic Computing

NSF · Aug 2026 – Jul 2029

Closest labs

Joseph Sklenar

Wayne State University, MI·Physics

Synthesize synthetic antiferromagnets by sputter deposition, varying the number of ferromagnetic layers and the non-magnetic spacer material, to excite magnons (spin waves) and create magnon-magnon interactions.

Dmytro Bozhko

University of Colorado Colorado Springs, CO·Physics·Early-career

Observe and compare magnon Bose-Einstein condensate dynamics in 3D, quasi-2D and quasi-1D ferromagnetic structures, using nanofabricated samples and Brillouin light scattering spectroscopy, to find the critical sizes that support a condensate.

Jian Liu

University of Tennessee-Knoxville, TN·Physics·Early-career

Grow atomically thin iridium oxide layers by in-situ-monitored pulsed-laser deposition, designed so that spin-orbit coupling tilts the spins while overall spin symmetry is kept.

The school

Oklahoma State University: 15 labs on PI Pages, $254M a year on research, 238 research doctorates a year.

More about Oklahoma State University

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