Electromagnetics & micromagnetics
High-performance computational methods for electromagnetic fields, micromagnetic dynamics, and their coupling to realistic material and device models.
Modeling electromagnetics and magnetization in next-generation materials and devices.
We develop high-performance computational methods for realistic systems involving electromagnetics, magnetization dynamics and statics, spintronics, elastics, heat transport, mechanical motion, and coherent X-ray imaging.
Our work combines physical modeling, numerical methods, and parallel computing to study materials and devices whose behavior cannot be captured by a single isolated mechanism.
High-performance computational methods for electromagnetic fields, micromagnetic dynamics, and their coupling to realistic material and device models.
Computational methods for real-time three-dimensional coherent X-ray diffraction imaging and reconstruction of magnetic textures.
Magnetic and ferroelectric memory and recording systems, including MRAM, FeRAM, PMR, HAMR, and ferroelectric recording.
Spin-wave–phonon propagation and coupling among spin-transfer-torque and spin-orbit-torque oscillators.
Neural-network-enhanced EEG event recognition for device control, including integration with virtual-reality systems.
Selected visuals from the lab’s simulations and modeling work, including electromagnetic scattering, microstructure-resolved magnetics, and dynamic field visualization.
The movie gives visitors an immediate view of the lab’s simulation workflow and three-dimensional field visualization.
Selected journal articles from the lab’s recent work in high-performance computation, spin dynamics, coherent imaging, and topological magnetic systems.
F. M. Shapira, V. Lomakin, A. Boag, and A. Natan.
Open publicationF. Ai, J. Duan, and V. Lomakin.
Open publicationF. Ai and V. Lomakin.
View in publication listC. Liu, F. Ai, S. Reisbick, V. Lomakin, and Y. Zhu.
View in publication listConferences, student research, leadership, and degree milestones from the lab community.
The 37th Magnetic Recording Conference brought three days of discussion on solid-state magnetic memory, storage architectures for AI, and recording beyond 3 Tbit/in².
Edith Elias and Diego Munos completed and presented a project on neural-network-based real-time EEG event detection.
Vitaliy Lomakin began serving as Director of the Center for Memory and Recording Research at UC San Diego.
Dr. Ai defended work on high-performance computational techniques for X-ray imaging and micromagnetic analysis of periodic arrays.