Training soft magnetoelastic nanoparticle sheets

Ideal materials for reconfigurable mechanical microstructures would be manipulable by external fields, and would be trainable into a particular state once the external field were released. Our experiments use ~10nm thick membranes of self-assembled superparamagnetic nanoparticles. The membranes' thinness and inherently soft elastic properties allow micron-scale deflections, which we track and image with high-resolution confocal microscopy. Under typical conditions, the membrane's deflection is elastic, so that membranes deflected by a magnetic field recover their initial neutral configuration when the field is released. However, by subjecting them to heating while deflected in the field, we can cause them to retain their deflected configuration once the field is released, with reduced flexibility in the new state. Later subjecting them to an excess of humidity, we can cause them to recover their initial neutral configuration as well as their initial flexibility. We use molecular dynamics simulations of the nanoparticle sheets to predict the deflected configuration in various applied magnetic fields, and to understand the general magnetoelasticity of this system. Combining magnetism and soft elasticity with training effects in this way, magnetoelastic nanoparticle membranes are thus a promising platform for reconfigurable mechanical microstructures.