Speaker
Description
Magnetic nanobeads, whose dimensions match those of biological agents, show great promise as wirelessly controlled microrobots in fluid environments. Particle tracking experiments reveal that their motion departs from classical diffusion, influenced by interrelated confinement, dipolar interactions, and temperature, affecting magnetic actuation. Our results underscore the challenges of achieving precise control under low-intensity magnetic fields, with responsiveness strongly modulated by particle size, magnetic moment, field strength, and effective temperature. These parameters collectively determine whether nanobeads exhibit enhanced diffusion, directional propulsion, or constrained motion. A central challenge remained in maintaining particles either independent or assembled into chains of tunable length, enabling more versatile magnetic steering and manipulation. To address this, we establish direct correlations between bead size, morphology, and field-dependent magnetic moment, offering a fundamental framework and a potential dataset for future machine learning approaches, for a magnetically actuated robotic control.
