Magnons, or spin waves, hold the potential to enable a new generation of highly energy-efficient spintronic devices. For that, however, the way that they propagate in ferrimagnetic and antiferromagnetic insulators needs to be thoroughly understood.
With the help of scanning NV magnetometry, a group of researchers led by Prof. Tianxiang Nan (Tsinghua University), recently uncovered a surprising new facet of magnon spin diffusion. Contrary to the predictions by state-of-art models of the interactions between magnons and static domain walls, they found that magnons barely feel the presence of 180-degree domain walls.
For their study, the researchers injected a spin current into a MgAl0,5Fe1,5O4 (MAFO) ferrimagnetic insulator thin film and detected the resulting spin currents following their propagation over paths ranging from 0.4 to 4.2 μm. Nan and his team expected the total spin current carried by the magnons to decay to zero as the spin waves passed through the stripe-like distribution of magnetic domains in their sample. Remarkably, however, they observed the opposite: the spin transmission signals decayed by less than 5% in samples with near-zero applied external magnetic fields compared to completely saturated magnetic samples. They noticed that this insensitivity would remain even after crossing a path up to 5 times the average domain size.
Central to the study was an accurate characterization of the magnetic domains in the MAFO thin film appearing at near-zero applied magnetic field. The researchers quantitatively characterized their sample using Qnami’s ProteusQ, the only tool capable of imaging its magnetic textures with such high accuracy. Based on the stray magnetic fields measurements, they infer the underlying magnetization using the AI-based method developed by researchers from University of Basel together with Qnami.
While these surprising findings reveal new gaps in our understanding of magnon spin diffusion across domain walls, they highlight the value of combining scanning NV magnetometry and AI-based tools for the development and characterization of emerging spintronic systems.
Read more about this study in the Nature Communications paper published in April 2023.