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Single-element detectors (SEDs) with a room temperature extended short-wave infrared (eSWIR) photoresponse were fabricated with branched nanorods of HgTe. Nanorods with high aspect (length/width) ratios were obtained by using stoichiometric excesses of Hg (i.e., [Hg]/[Te] molar ratios greater than one) and relatively low reaction temperatures, as low as room temperature. The size-tunable optical cutoff wavelengths of the detectors ranged from 2 to 3.5 μm, with specific detectivities as high as 2.4 × 10^11 Jones. The devices retained their responsivity for more than a year. Branched nanorods of HgTe are promising materials for IR photodetectors and imagers. 

We report a data-parsimonious machine learning model for short-term forecasting of solar irradiance. The model follows the convolutional neural network – long-short term memory architecture. Its inputs include sky camera images that are reduced to scalar features to meet data transmission constraints. The model focuses on predicting the deviation of irradiance from the persistence of cloudiness (POC) model. Inspired by control theory, a noise signal input is used to capture the presence of unknown and/or unmeasured input variables and is shown to improve model predictions, often considerably. Five years of data from the NREL Solar Radiation Research Laboratory were used to create three rolling train-validate sets and determine the best representations for time, the optimal span of input measurements, and the most impactful model input data (features). For the chosen validation data, the model achieves a mean absolute error of 74.29 W/m2 over a time horizon of up to two hours, compared to a baseline 134.35 W/m2 using the POC model. 

Optically resonant particles are key building blocks of many nanophotonic devices such as optical antennas and metasurfaces. Because the functionalities of such devices are largely determined by the optical properties of individual resonators, extending the attainable responses from a given particle is highly desirable. Practically, this is usually achieved by introducing an asymmetric dielectric environment. However, commonly used simple substrates have limited influences on the optical properties of the particles atop. Here, we show that the multipolar scattering of silicon microspheres can be effectively modified by placing the particles on a dielectric-covered mirror, which tunes the coupling between the Mie resonances of microspheres and the standing waves and waveguide modes in the dielectric spacer. This tunability allows selective excitation, enhancement, suppression, and even elimination of the multipolar resonances and enables scattering at extended wavelengths, providing transformative opportunities in controlling light–matter interactions for various applications. We further demonstrate with experiments the detection of molecular fingerprints by single-particle mid-infrared spectroscopy and with simulations strong optical repulsive forces that could elevate the particles from a substrate. 

Rational manipulation and assembly of discrete colloidal particles into architected superstructures have enabled several applications in materials science and nanotechnology. Optical manipulation techniques, typically operated in fluid media, facilitate the precise arrangement of colloidal particles into superstructures by using focused laser beams. However, as the optical energy is turned off, the inherent Brownian motion of the particles in fluid media impedes the retention and reconfiguration of such superstructures. Overcoming this fundamental limitation, we present on-demand, three-dimensional (3D) optical manipulation of colloidal particles in a phase-change solid medium made of surfactant bilayers. Unlike liquid crystal media, the lack of fluid flow within the bilayer media enables the assembly and retention of colloids for diverse spatial configurations. By utilizing the optically controlled temperature-dependent interactions between the particles and their surrounding media, we experimentally exhibit the holonomic microscale control of diverse particles for repeatable, reconfigurable, and controlled colloidal arrangements in 3D. Finally, we demonstrate tunable light–matter interactions between the particles and 2D materials by successfully manipulating and retaining these particles at fixed distances from the 2D material layers. Our experimental results demonstrate that the particles can be retained for over 120 days without any change in their relative positions or degradation in the bilayers. With the capability of arranging particles in 3D configurations with long-term stability, our platform pushes the frontiers of optical manipulation for distinct applications such as metamaterial fabrication, information storage, and security. 

Abstract An extremely rapid process for self‐assembling well‐ordered, nano, and microparticle monolayers via a novel aerosolized method is presented. The novel technique can reach monolayer self‐assembly rates as high as 268 cm²min⁻¹from a single aerosolizing source and methods to reach faster monolayer self‐assembly rates are outlined. A new physical mechanism describing the self‐assembly process is presented and new insights enabling high‐efficiency nanoparticle monolayer self‐assembly are developed. In addition, well‐ordered monolayer arrays from particles of various sizes, surface functionality, and materials are fabricated. This new technique enables a 93× increase in monolayer self‐assembly rates compared to the current state of the art and has the potential to provide an extremely low‐cost option for submicron nanomanufacturing.