Non-Hermitian physics for optical manipulation uncovers inherent instability of large clusters

Intense light traps and binds small particles, offering unique control to the microscopic world. With incoming illumination and radiative losses, optical forces are inherently nonconservative, thus non-Hermitian. Contrary to conventional systems, the operator governing time evolution is real and asymmetric (i.e., non-Hermitian), which inevitably yield complex eigenvalues when driven beyond the exceptional points, where light pumps in energy that eventually “melts” the light-bound structures. Surprisingly, unstable complex eigenvalues are prevalent for clusters with ~10 or more particles, and in the many-particle limit, their presence is inevitable. As such, optical forces alone fail to bind a large cluster. Our conclusion does not contradict with the observation of large optically-bound cluster in a fluid, where the ambient damping can take away the excess energy and restore the stability. The non-Hermitian theory overturns the understanding of optical trapping and binding, and unveils the critical role played by non-Hermiticity and exceptional points, paving the way for large-scale manipulation.

Modeling Brownian Microparticle Trajectories in Lab-on-a-Chip Devices with Time Varying Dielectrophoretic or Optical Forces

Lab-on-a-chip (LOC) devices capable of manipulating micro/nano-sized samples have spurred advances in biotechnology and chemistry. Designing and analyzing new and more advanced LOCs require accurate modeling and simulation of sample/particle dynamics inside such devices. In this work, we present a generalized computational physics model to simulate particle/sample trajectories under the influence of dielectrophoretic or optical forces inside LOC devices. The model takes into account time varying applied forces, Brownian motion, fluid flow, collision mechanics, and hindered diffusion caused by hydrodynamic interactions. We develop a numerical solver incorporating the aforementioned physics and use it to simulate two example cases: first, an optical trapping experiment, and second, a dielectrophoretic cell sorter device. In both cases, the numerical results are found to be consistent with experimental observations, thus proving the generality of the model. The numerical solver can simulate time evolution of the positions and velocities of an arbitrarily large number of particles simultaneously. This allows us to characterize and optimize a wide range of LOCs. The developed numerical solver is made freely available through a GitHub repository so that researchers can use it to develop and simulate new designs.

Optical Trapping, Sensing, and Imaging by Photonic Nanojets

The optical trapping, sensing, and imaging of nanostructures and biological samples are research hotspots in the fields of biomedicine and nanophotonics. However, because of the diffraction limit of light, traditional optical tweezers and microscopy are difficult to use to trap and observe objects smaller than 200 nm. Near-field scanning probes, metamaterial superlenses, and photonic crystals have been designed to overcome the diffraction limit, and thus are used for nanoscale optical trapping, sensing, and imaging. Additionally, photonic nanojets that are simply generated by dielectric microspheres can break the diffraction limit and enhance optical forces, detection signals, and imaging resolution. In this review, we summarize the current types of microsphere lenses, as well as their principles and applications in nano-optical trapping, signal enhancement, and super-resolution imaging, with particular attention paid to research progress in photonic nanojets for the trapping, sensing, and imaging of biological cells and tissues.