We consider the design of nanostructured materials for thermal homeostasis, or the ability to maintain a temperature within a fixed range despite externally varying heat input. Our design uses nano- and microstructured phase-change materials to achieve a sharp change in thermal emission at a particular phase-transition temperature. We use electromagnetic simulations to calculate the thermal infrared absorption spectra for metal and insulator phases of the phase-change material. The results indicate a large increase in thermal emission at the phase transition. We then use numerical simulations of the heat equation to show that the sharp change in emission results in thermal homeostasis. For a varying external heat source, the material experiences much smaller temperature fluctuations than an unstructured or bulk material.
Our experiments have used arrayed traps in the near field of a photonic crystal to selectively capture nanoparticles by size. The photonic crystal is designed to support a guided resonance mode, and the incident laser is tuned to the resonance wavelength. Each hole of the photonic crystal acts as a trapping site.
In this work, we use simulations of particle dynamics to determine the optimal experimental conditions for size selection. We include the effects of optical forces, fluid flow, and Brownian motion and explicitly track the trajectories of particles near an array of trapping sites. We study the effects of varying chamber height, flow rate, and particle concentration on size selectivity and trapping yield. We further present photonic crystal designs for selectively trapping smaller or larger particles out of mixed-particle solutions.
Brownian ratchets are of fundamental interest in fields from statistical physics to molecular motors. The realization of Brownian ratchets in engineered systems opens up the potential to harness thermal energy for directed motion, with applications in transport and sorting of nanoparticles. Implementations based on optical traps provide a high degree of tunability along with precise spatiotemporal control. Near-field optical methods provide particular flexibility and ease of on-chip integration with other microfluidic components. Here, we demonstrate the first all-optical, near-field Brownian ratchet. Our approach uses an asymmetrically patterned photonic crystal and yields an ultra-stable trap stiffness of 253.6 pN/nm-W, 100x greater than conventional optical tweezers. By modulating the laser power, optical ratcheting with transport speed of ~1 micron/s can be achieved, allowing a variety of dynamical lab-on-a-chip applications. The resulting transport speed matches well with the theoretical prediction.
Optical trapping serves as a powerful tool for the manipulation of matter on the nanoscale and ultra-precise measurement of weak forces. However, the applicability of these tools is limited by the available laser power and trap efficiency. We utilized the strong confinement of light in a slot-graphite photonic crystal to develop high-efficiency parallel trapping over a large area. The stiffness is several orders of magnitude higher than conventional optical tweezers and two orders of magnitude higher than our previously demonstrated on-chip, near field traps. We demonstrate the ability to trap both dielectric and metallic nanoparticles of sub-micron size. We find that the growth kinetics of nanoparticle arrays on the slot-graphite template depends on particle size. Smaller particles diffuse more, more readily occupying the available trap sites and inhibiting the trapping of larger particles. Smaller particles also sink more into the holes in the photonic crystal, resulting in stronger mechanical confinement and a deeper potential well. We use these differences to selectively trap one type of particle out of a binary colloidal mixture, creating an efficient optical sieve. This technique has rich potential in the fields of trace analysis, optical diagnostics, and enrichment and sorting of microscopic entities and molecules.