In a breakthrough for spintronics and electron microscopy, researchers at the U.S. Department of Energy's Brookhaven National Laboratory have achieved the first real-time nanoscale imaging of spin waves. Published in *Nature Materials* on January 27, 2025, the study details a novel technique combining electron microscopy with microwave technology to observe spin wave behavior with unparalleled spatial and temporal resolution.
"Our imaging setup is truly innovative, allowing us to directly observe spin-wave behavior with both an unparalleled high spatial and temporal resolution," said Chuhang Liu, lead author and Ph.D. student at Stony Brook University. This advancement addresses a significant challenge in magnonics, a subset of spintronics, which requires effective imaging of spin waves at the nanoscale to advance energy-efficient microelectronics and information processing technologies.
The team created and stabilized a unique topological magnetic structure in permalloy thin films, exciting spins using radio frequency signals. This allowed them to observe the generation, propagation, reflection, and interference of spin waves, revealing that these waves preferentially form at anti-vortices and are associated with the oscillatory motion of specific domain walls. These insights are crucial for understanding energy-efficient signal processing.
This achievement builds on Brookhaven's two-decade history of spin structure imaging using the U.S.'s first dedicated Lorentz transmission electron microscope (LTEM). The integration of a microwave-frequency-mediated ultrafast electron pulser, initially developed in partnership with Euclid Techlabs, LLC, enabled the capture of spin wave dynamics at picosecond speeds. "Our work opens a new frontier in electron microscopy, offering an unprecedented nanoscale view of magnon dynamics," said Brookhaven physicist Yimei Zhu.
The development is particularly significant for neuromorphic computing, which aims to replicate the energy efficiency and parallel processing capabilities of the human brain. The electrical triggering method used in this study mirrors the electric-spike-based signaling found in biological synapses, making it essential for mimicking neural network behavior in artificial systems. This research bridges the gap between fundamental research and practical applications in wireless technologies and quantum computing.