Analysis of optical near-field energy transfer by stochastic model unifying architectural dependencies

We theoretically and experimentally demonstrate energy transfer mediated by optical near-field interactions in a multi-layer InAs quantum dot (QD) structure composed of a single layer of larger dots and N layers of smaller ones. We construct a stochastic model in which optical near-field interactions that follow a Yukawa potential, QD size fluctuations, and temperature-dependent energy level broadening are unified, enabling us to examine device-architecture-dependent energy transfer efficiencies. The model results are consistent with the experiments. This study provides an insight into optical energy transfer involving inherent disorders in materials and paves the way to systematic design principles of nanophotonic devices that will allow optimized performance and the realization of designated functions

Brightening of excitons in carbon nanotubes on dimensionality modification

Despite the attractive one-dimensional characteristics of carbon nanotubes, their typically low luminescence quantum yield, restricted because of their one-dimensional nature, has limited the performance of nanotube-based light-emitting devices. Here, we report the striking brightening of excitons (bound electron–hole pairs) in carbon nanotubes through an artificial modification of their effective dimensionality from one dimension to zero dimensions. Exciton dynamics in carbon nanotubes with luminescent, local zero-dimension-like states generated by oxygen doping were studied as model systems. We found that the luminescence quantum yield of the excitons confined in the zero-dimension-like states can be more than at least one order larger (~18%) than that of the intrinsic one-dimensional excitons (typically ~1%), not only because of the reduced non-radiative decay pathways but also due to an enhanced radiative recombination probability beyond that of intrinsic one-dimensional excitons. Our findings are extendable to the realization of future nanoscale photonic devices including a near-infrared single-photon emitter operable at room temperature

Nano-artifact metrics based on random collapse of resist

Artifact metrics is an information security technology that uses the intrinsic characteristics of a physical object for authentication and clone resistance. Here, we demonstrate nano-artifact metrics based on silicon nanostructures formed via an array of resist pillars that randomly collapse when exposed to electron-beam lithography. The proposed technique uses conventional and scalable lithography processes, and because of the random collapse of resist, the resultant structure has extremely fine-scale morphology with a minimum dimension below 10 nm, which is less than the resolution of current lithography capabilities. By evaluating false match, false non-match and clone-resistance rates, we clarify that the nanostructured patterns based on resist collapse satisfy the requirements for high-performance security applications

Decision making based on optical excitation transfer via near-field interactions between quantum dots

Optical near-field interactions between nanostructured matter, such as quantum dots, result in unidirectional optical excitation transfer when energy dissipation is induced. This results in versatile spatiotemporal dynamics of the optical excitation, which can be controlled by engineering the dissipation processes and exploited to realize intelligent capabilities such as solution searching and decision making. Here we experimentally demonstrate the ability to solve a decision making problem on the basis of optical excitation transfer via near-field interactions by using colloidal quantum dots of different sizes, formed on a geometry-controlled substrate. We characterize the energy transfer behavior due to multiple control light patterns and experimentally demonstrate the ability to solve the multi-armed bandit problem. Our work makes a decisive step towards the practical design of nanophotonic systems capable of efficient decision making, one of the most important intellectual attributes of the human brain