Plasmon-mediated chemical reactions have attracted intensive research interest as a means of achieving desirable reaction yields and selectivity. The energetic charge carriers and elevated local temperature induced by the nonradiative decay of surface plasmons are thought to be responsible for improving reaction outcomes. This study reports that the plasmoelectric potential is another key contributor in plasmon-mediated electrochemistry. Additionally, we disclose a convenient and reliable method for quantifying the specific contributions of the plasmoelectric potential, hot electrons, and photothermal heating to the electroreduction of oxygen at the plasmonic Ag electrode, revealing that the plasmoelectric potential is the dominating nonthermal factor under short-wavelength illumination and moderate electrode bias. This work elucidates novel mechanistic understandings of plasmon-mediated electrochemistry, facilitating high-performance plasmonic electrocatalyst design optimization.

AbstractIn an optical Pancharatnam-Berry (PB) phase metasurface, each sub-wavelength dielectric structure of varied spatial orientation can be treated as a point source with the same amplitude yet varied relative phase. In this work, we introduce an optimized genetic algorithm (GA) method for the synthesis of one-dimensional (1D) PB phase-controlled dielectric metasurfaces by seeking for optimized phase profile solutions, which differs from previously reported amplitude-controlled GA method only applicable to generate transverse optical modes with plasmonic metasurfaces. The GA–optimized phase profiles can be readily used to construct dielectric metasurfaces with improved functionalities. The loop of phase-controlled GA consists of initialization, random mutation, screened evolution, and duplication. Here random mutation is realized by changing the phase of each unit cell, and this process should be efficient to obtain enough mutations to drive the whole GA process under supervision of appropriate mutation boundary. A well-chosen fitness function ensures the right direction of screened evolution, and the duplication process guarantees an equilibrated number of generated light patterns. Importantly, we optimize the GA loop by introducing a multi-step hierarchical mutation process to break local optimum limits. We demonstrate the validity of our optimized GA method by generating longitudinal optical modes (i. e., non-diffractive light sheets) with 1D PB phase dielectric metasurfaces having non-analytical counter-intuitive phase profiles. The produced large-area, long-distance light sheets could be used for realizing high-speed, low-noise light-sheet microscopy. Additionally, a simplified 3D light pattern generated by a 2D PB phase metasurface further reveals the potential of our optimized GA method for manipulating truly 3D light fields.

Lead-free perovskite quantum dots (QDs) have been widely investigated for optoelectronic devices because of their excellent electrical and optical properties. However, optoelectronic devices based on such lead-free perovskites still have much lower performance than those made of Pb-based counterparts. Herein, we developed a lead-free photodetector with an enhanced broadband spectral response ranging from 300 to 630 nm. By balancing plasmonic near-field enhancement and surface energy quenching through precisely controlling the thickness of Al 2 O 3 spacer between the CsSnBr 3 QDs and silver nanoparticle membrane, the photodetector with 5 nm thick Al 2 O 3 experiences a maximum photocurrent enhancement of 6.5-fold at 410 nm, with a responsivity of 62.3 mA/W and detectivity of 4.27 × 10 11 Jones. Moreover, its photocurrent shows a negligible decrease after 100 cycles of bending, which is ascribed to the tension-offset induced by the self-assembled nanoparticle membrane. The proposed plasmonic membrane enhancement provides a great potential for high-performance perovskite optoelectronic devices.

Polymeric coatings with randomly distributed dielectric nanoparticles have attracted intensive attention in the passive daytime radiative cooling application. Here, we propose a modified Monte–Carlo method for investigating the spectral response and cooling performance of polymer coating with gradient‐dispersed nanoparticles. Using this method, we carry out a quantitative analysis on the solar reflectance, infrared emittance and cooling power of four categories of gradient structures. It is shown that the gradient profile of particle distribution at the near‐surface region has a significant influence on the overall performance of the coatings. Compared to a randomly distributed structure, the downward size‐gradient structure exhibits superiority in both solar reflectance and cooling power. The presented gradient design, also applicable to porous structures, provides an effective and universal strategy for significantly improving the cooling performance of radiative cooling coatings.

Light-sheet fluorescence microscopy (LSFM), sectioning biological samples by illuminating a thin slice of fluorescently labelled live cells or tissues typically with a Bessel beam, requires dithering the beam to form a two-dimensional (2D) light sheet. It usually suffers from severe phototoxicity and low signal-to-noise ratio (SNR) mainly caused by the side-lobe illumination generating unfavorable bio-fluorescence from the adjacent tissues. Here, the first proof-of-concept experimental implementation of genetic algorithm (GA) generated metalens is provided to address the above challenges. It is shown that a dithering-free 2D light sheet produced by a GaN-based metalens with GA-generated prism-like yet non-analytical phase profile, can significantly suppress the side-lobe intensity of the resultant light sheet down to 7.3% of the main lobe intensity and also extends its depth of focus up to 4 mm, surpassing the latest results reported in the literature. When applied under two-photon excitation, the light sheet exhibits an enhanced axial resolution and SNR. These results demonstrate the feasibility of applying artificial intelligence generated metalens in addressing some special issues encountered by conventional analytical design approaches, and the metalens device produced here could find an important role in fast-LSFM-based large-scale bioimaging applications without mechanical dithering.

Since its first observation in 2014, plasmoelectric potential (PEP) has drawn a great deal of research interest in all-metal optoelectronics and photochemistry. As an optical thermodynamic phenomenon induced by the electron number dependent equilibrium temperature in plasmonic nanostructures, the early theoretical model developed for calculating PEP is only applicable to Mie-resonant nanostructures, such as a gold nanosphere on a conductive indium tin oxide (ITO) substrate, where the transfer efficiency of hot electrons from gold to ITO can be analytically determined. Without the presence of the substrate, the temperature increase on the gold nanosphere induced by plasmonic absorption was calculated on the basis of thermal radiation in vacuum, which probably over-estimates the actual temperature increase in comparison to realistic experimental conditions. Here, we propose an equilibrium-thermodynamics computational method to quantify the actual efficiency of plasmon-induced electron transfer between a non-Mie-resonant metallic nanostructure and a conductive substrate and hence determine the resultant plasmoelectric potential. With a less than 2.5% relative error in predicting the steady-state temperature of a Mie-resonant nanoparticle in vacuum, and a more strict evaluation of the plasmonic local heating induced temperature increase in a single plasmonic nanostructure or an array of such structures under continuous-wave illumination (CWI), our generalized method provides a robust and accurate approach for quantifying PEP in various plasmonic-particle (array)-on-film nanocavities.

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