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Creators/Authors contains: "Shen, Sheng"

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  1. Free, publicly-accessible full text available December 1, 2026
  2. Nanoantennas and their arrays (metasurfaces) provide a versatile platform for controlling the coherence of thermal emission. Conventional designs rely on global heating, which impedes emission efficiency and on-chip integration. In this work, we propose an electrically driven metasurface composed of a Yagi-Uda nanoantenna array interconnected by S-shaped electrode wires, which enables the concurrent manipulation of thermal emission spectrally and directionally. A direct simulation approach based on the Wiener-chaos expansion method is employed for quantitative analysis. Our metasurface device exhibits a narrowband emission with high directivity, which is one order higher than that of a single nanorod antenna case. The modeling framework established in this work opens a promising route for realizing coherent mid-infrared emission by metasurfaces. 
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  3. Abstract Understanding how climate affects trait composition within a biological assemblage is critical for assessing and eventually mitigating climate change impacts on the assemblage and its ecological functioning. While body size is a fundamental trait of animals as it affects many aspects of species' biology and ecology, it remains unclear through what mechanisms temperature and its variability influence within‐assemblage body size variation.This study aims to understand how temperature and its variability shape body size variations in animal assemblages and potentially affect assemblages' vulnerability to climate change. Using >5300 individuals of 680 macromoth species collected from 13 assemblages along a ca. 3000 m elevational gradient in Taiwan, we examined (1) the strength of environmental filtering and niche partitioning in determining the intra‐ and inter‐specific size variations within an assemblage, and (2) the effects of mean temperature and the daily and seasonal temperature variabilities on the strength of the two processes.We found that the body size composition was strongly affected by temperature and its seasonality via both processes. High temperature seasonality enhanced niche partitioning, causing within‐population size convergence. In contrast, low mean temperature and low seasonality both enhanced environmental filtering, causing within‐assemblage size convergence. However, while low temperature restricted the lower size limit within an assemblage, low seasonality restricted both lower and upper size limits.This study indicates an overlooked but important role of temperature seasonality in shaping intra‐ and inter‐specific size variations in moth assemblages through both environmental filtering and niche partitioning. With rising temperatures and amplifying seasonality around the globe, potentially weakened filtering forces may increase the size variation within assemblages, reinforcing the assemblage‐level resilience. Nevertheless, enhanced niche partitioning may limit size variation within populations, which may increase the population‐level vulnerability to environmental changes. This study improves the mechanistic understanding of the climatic effects on trait composition in animal assemblages and provides essential information for biodiversity conservation under climate change. Read the freePlain Language Summaryfor this article on the Journal blog. 
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  4. Plasmonic metasurfaces with adjustable optical responses can be achieved through phase change materials (PCMs) with high optical contrast. However, the on–off behavior of the phase change process results in the binary response of photonic devices, limiting the applications to the two-stage modulation. In this work, we propose a reconfigurable metasurface emitter based on a gold nanorod array on a VO2 thin film for achieving continuously tunable narrowband thermal emission. The electrode line connecting the center of each nanorod not only enables emission excitation electrically but also activates the phase transition of VO2 beneath the array layer due to Joule heating. The change in the dielectric environment due to the VO2 phase transition results in the modulation of emissivity from the plasmonic metasurfaces. The device performances regarding critical geometrical parameters are analyzed based on a fully coupled electro-thermo-optical finite element model. This new metasurface structure extends the binary nature of PCM based modulations to continuous reconfigurability and provides new possibilities toward smart metasurface emitters, reflectors, and other nanophotonic devices. 
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  5. Abstract Synaptic devices with tunable weight hold great promise in enabling non-von Neumann architecture for energy efficient computing. However, conventional metal-insulator-metal based two-terminal memristors share the same physical channel for both programming and reading, therefore the programming power consumption is dependent on the synaptic resistance states and can be particularly high when the memristor is in the low resistance states. Three terminal synaptic transistors, on the other hand, allow synchronous programming and reading and have been shown to possess excellent reliability. Here we present a binary oxide based three-terminal MoS2synaptic device, in which the channel conductance can be modulated by interfacial charges generated at the oxide interface driven by Maxwell-Wagner instability. The binary oxide stack serves both as an interfacial charge host and gate dielectrics. Both excitatory and inhibitory behaviors are experimentally realized, and the presynaptic potential polarity can be effectively controlled by engineering the oxide stacking sequence, which is a unique feature compared with existing charge-trap based synaptic devices and provides a new tuning knob for controlling synaptic device characteristics. By adopting a three-terminal transistor structure, the programming channel and reading channel are physically separated and the programming power consumption can be kept constantly low (∼50 pW) across a wide dynamic range of 105. This work demonstrates a complementary metal oxide semiconductor compatible approach to build power efficient synaptic devices for artificial intelligence applications. 
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