Functional Manipulation of Nonspherical Nanoparticles with Cascaded Reconfigurable Modules

Abstract

Selective nanoparticle sorting is essential for applications requiring monodisperse distributions, yet conventional methods lack adaptability for shape-based separation. This study introduces a reconfigurable optical manipulation technique that dynamically sorts spherical and non-spherical nanoparticles using cascaded modules based on evanescent fields. Optical forces were calculated using the Discrete Dipole Approximation (DDA) method, enabling the modeling of various particle shapes and accurately capturing rotational and translational movements. Two cascaded strategies are proposed: the first approach enables fluid-assisted filtration by selectively trapping spherical particles while allowing non-spherical ones to be carried away by the flow. The second strategy first induces the rotational alignment of particles and then employs a trapping mechanism that selectively retains specific geometries, enabling the separation of spherical and non-spherical nanoparticles. Unlike traditional approaches, this method enables high-precision, shape-selective separation without external flow modifications. The results demonstrate unprecedented control and efficiency in nanoparticle sorting, offering a scalable, high-throughput solution for microfluidic and optofluidic applications.