Advancing nanoscale magnetic devices for neuromorphic computing and sensing applications by combining precision fabrication, time-resolved microscopy, and multi-physics modelling. Our work bridges fundamental spin dynamics with practical hardware implementations.
We design and characterize nanomagnetic devices that leverage spintronic phenomena for energy-efficient information processing. By tailoring magnetic anisotropy and coupling at the nanoscale, we create devices capable of analog computation, pattern recognition, and signal transduction.
Our laboratory integrates advanced thin-film deposition, electron-beam lithography, and focused ion-beam modification to engineer magnetic tunnel junctions (MTJs) and hybrid magnonic architectures. Time-resolved magneto-optical Kerr effect (TR-MOKE) microscopy and microwave spectroscopy provide deep insight into device dynamics.
These efforts deliver application-ready building blocks for neuromorphic accelerators and reconfigurable RF front-ends, while establishing best practices for robust spintronic integration with CMOS platforms.
Demonstrated reservoir computing prototypes using coupled spin-wave conduits and MTJs for ultra-low-power signal processing.
Established a measurement pipeline that combines TR-MOKE, BLS, and electrical probing to correlate nanoscale material properties with device-level performance metrics.
Engineered magnetic field sensors that maintain accuracy after ion irradiation, enabling deployment in aerospace and quantum instrumentation environments.
Integrated spin-wave buses with CMOS-compatible readout to create multi-modal interconnects for adaptive systems-on-chip.
Fabricating MTJ stacks with engineered free layers and synthetic antiferromagnets to achieve tunable oscillation frequencies and robust readout contrast.
Utilizing TR-MOKE and scanning NV magnetometry for picosecond-to-nanosecond visualization of magnetization dynamics in operational devices.
Performing micromagnetic simulations and compact modelling to co-optimize device geometry, material stacks, and neuromorphic workloads.
Implementing spiking neuron primitives, synaptic weighting, and reservoir dynamics directly in hardware for real-time inference at microwatt power budgets.
Deploying tunable magnonic filters and phase shifters that respond dynamically to mission constraints in communication payloads.
Leveraging magnetic nano-oscillators and Hall sensors for high-bandwidth detection of minute magnetic signatures in biomedical and navigation contexts.
This work demonstrates focused-ion-beam (FIB) writing as a maskless technique for spin-wave optical devices, showing magnonic versions of lenses, gratings, and Fourier-domain processors.
Exploration of spin-wave devices for neuromorphic computing applications.
Embedding learning algorithms directly into nanomagnetic networks to enable autonomous sensor calibration and adaptive control.
Stacking magnetic devices across multiple layers for volumetric computing and enhanced connectivity.
Qualifying nanomagnetic sensors and logic for extreme environments spanning space missions to nuclear facilities.
Coupling spintronic elements with superconducting qubits and photonic links for multi-physics quantum systems.