Advancing High Sensitivity Hybrid Magnonic Sensors
ECE Assistant Professor Xufeng Zhang, in collaboration with Wei Zhang from the University of North Carolina at Chapel Hill, was awarded a $655K NSF grant for “Hybrid Active Magnonic Magnetometry with Enhanced Resolution (HAMMER).”
Abstract Source: NSF
Magnetic sensors underpin technologies essential to modern life, from navigation and medical diagnostics to resource exploration and national security. Emerging applications place ever-greater demands on these sensors: brain-computer interfaces must detect the vanishingly faint magnetic signals produced by neural activity—roughly a billionth of the strength of the Earth’s magnetic field—and geophysical instruments must map weak magnetic signatures deep below the Earth’s surface. Meeting these needs requires extreme sensitivity together with stability and portability. Today’s most sensitive magnetometers achieve such performance only by relying on large, low-temperature cooling or delicate optical systems, which raise cost and prevent widespread accessibility, while compact alternatives fall well short on sensitivity. This project develops a new class of solid-state magnetic sensor that aims to bridge this gap between sensitivity and practicality, delivering very high sensitivity in a compact package that operates in the ambient without low temperature or complex optics. The sensor encodes the magnetic field into the frequency of an oscillating signal generated within a magnetic material, an approach that is naturally robust against noise and well suited to miniaturization and eventual integration onto a single chip. This project will provide interdisciplinary research and training opportunities for graduate and undergraduate students in the emerging areas of sensing technology, and will engage students across K-12 and high school through hands-on magnetism demonstrations, laboratory field trips, and a summer research program, broadening participation and strengthening the science and engineering workforce pipeline.
This project advances the ferrimagnetic oscillator magnetometer, a device that senses magnetic fields through the field-dependent frequency of magnons—collective spin excitations—in the low-loss magnetic material yttrium iron garnet. The sensitivity of such an oscillator is governed by two competing quantities: the field-to-frequency conversion coefficient and the oscillator phase noise. Conventional designs are constrained on the first by the fixed gyromagnetic ratio (an intrinsic material property) and on the second by the phase noise inherent to microwave circuits. The research overcomes both constraints through three integrated efforts. The first engineers a coupled oscillator between magnons and a low-loss resonator with tailored spectral characters; the resulting spectral response can increase the conversion coefficient by more than an order of magnitude, surpassing the gyromagnetic limit. The second embeds a magnetic sensing element into an optoelectronic oscillator, whose long optical-fiber delay lines provide exceptionally low phase noise, using both radio-frequency and magneto-optical coupling of the material. The third integrates these advances into a unified prototype, benchmarks it against calibrated magnetic fields, and applies it to a timely on-chip demonstration: detecting and spatially mapping, with micrometer-scale resolution, the weak evanescent magnetic fields at the chip surface due to acoustic vibrations. The intellectual significance lies in extending hybrid-magnonic physics—cavity magnonics and optoelectronic oscillation—into the active self-oscillation regime for sensing, establishing a route to on-demand engineering of a sensor’s field-to-frequency response. The work targets sensitivity in the femtotesla-per-root-hertz range at room temperature, rivaling state-of-the-art sensors and establishing a scalable, energy-efficient platform for applications spanning neuroimaging, navigation, and geophysical mapping.