Topology optimized plasmonic metasurfaces for optical trapping of nanoparticles

Abstract

Smart metasurfaces capable of employing the momentum of light for manipulating nanoparticles hold the key to potential applications in science and nanotechnology. This article proposes a density-based topology optimization framework for optimizing plasmonic metasurfaces for nanoparticles optical trapping. The Maxwell stress tensor (MST) is employed to compute the optical force exerted on nanoparticles of different sizes and types. The metasurfaces' topologies are optimized to maximize the gradient (attractive) force on such nanoparticles subject to normally incident monochromatic excitation. Designs based on free-form optimization are investigated first, then manufacturing constraints are imposed to provide easy-to-manufacture planar designs. The results show that the topology of the optimized metasurfaces depends on the nanoparticle size and material, with a higher trapping stiffness associated with small nanoparticles. The optimized metasurfaces could offer selective mass trapping of nanoparticles for applications in biosensing, microfabrication, or assembly of quantum systems.