57 research outputs found

    Efficient metal halide perovskite light-emitting diodes with significantly improved light extraction on nanophotonic substrates.

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    Metal halide perovskite has emerged as a promising material for light-emitting diodes. In the past, the performance of devices has been improved mainly by optimizing the active and charge injection layers. However, the large refractive index difference among different materials limits the overall light extraction. Herein, we fabricate efficient methylammonium lead bromide light-emitting diodes on nanophotonic substrates with an optimal device external quantum efficiency of 17.5% which is around twice of the record for the planar device based on this material system. Furthermore, optical modelling shows that a high light extraction efficiency of 73.6% can be achieved as a result of a two-step light extraction process involving nanodome light couplers and nanowire optical antennas on the nanophotonic substrate. These results suggest that utilization of nanophotonic structures can be an effective approach to achieve high performance perovskite light-emitting diodes

    Adaptive Routing Forwarding Strategy Based on Neural Network Algorithm

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    With the profound changes in global digital media, the focus of Internet users has gradually shifted to how to quickly obtain information without paying attention to where the information is stored. However, the current TCP/IP network protocol architecture cannot adapt to the rapid development of today#39s content applications. In order to adapt to the changes in the Internet, information-centric networking (ICN)has received extensive attention. Besides, the optimization of the user service request scheduling problem is the core issue affecting the performance of the ICN , and it is one of the hot research topics in the ICN network. To solve this problem, this paper proposes an adaptive routing forwarding strategy based on neural network algorithm. Through the modeling of the classic architecture named data networking (NDN) network delay model of ICN network, a neural network algorithm is used to delay prediction, and a forwarding strategy mechanism based on predict delay is designed to innovate in the NDN. The interface information Stat is added to the forwarding information base (FIB) of the network component to implement the dynamic selection of the forwarding routing. In addition, routing dynamic self-adaptation adjustment mechanism and fault rerouting function are designed in consideration of the situation of route congestion and interruption. Simulation results show that this strategy effectively reduces network delay and improves network performance

    Compound dietary fiber and high-grade protein diet improves glycemic control and ameliorates diabetes and its comorbidities through remodeling the gut microbiota in mice

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    Dietary intervention with a low glycemic index and full nutritional support is emerging as an effective strategy for diabetes management. Here, we found that the treatment of a novel compound dietary fiber and high-grade protein diet (CFP) improved glycemic control and insulin resistance in streptozotocin-induced diabetic mice, with a similar effect to liraglutide. In addition, CFP treatment ameliorated diabetes-related metabolic syndromes, such as hyperlipidemia, hepatic lipid accumulation and adipogenesis, systemic inflammation, and diabetes-related kidney damage. These results were greatly associated with enhanced gut barrier function and altered gut microbiota composition and function, especially those bacteria, microbial functions, and metabolites related to amino acid metabolism. Importantly, no adverse effect of CFP was found in our study, and CFP exerted a wider arrange of protection against diabetes than liraglutide. Thereby, fortification with balanced dietary fiber and high-grade protein, like CFP, might be an effective strategy for the management and treatment of diabetes

    Roadmap on perovskite light-emitting diodes

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    In recent years, the field of metal-halide perovskite emitters has rapidly emerged as a new community in solid-state lighting. Their exceptional optoelectronic properties have contributed to the rapid rise in external quantum efficiencies (EQEs) in perovskite light-emitting diodes (PeLEDs) from <1% (in 2014) to over 30% (in 2023) across a wide range of wavelengths. However, several challenges still hinder their commercialization, including the relatively low EQEs of blue/white devices, limited EQEs in large-area devices, poor device stability, as well as the toxicity of the easily accessible lead components and the solvents used in the synthesis and processing of PeLEDs. This roadmap addresses the current and future challenges in PeLEDs across fundamental and applied research areas, by sharing the community’s perspectives. This work will provide the field with practical guidelines to advance PeLED development and facilitate more rapid commercialization

    Roadmap on Perovskite Light-Emitting Diodes

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    In recent years, the field of metal-halide perovskite emitters has rapidly emerged as a new community in solid-state lighting. Their exceptional optoelectronic properties have contributed to the rapid rise in external quantum efficiencies (EQEs) in perovskite light-emitting diodes (PeLEDs) from <1% (in 2014) to approaching 30% (in 2023) across a wide range of wavelengths. However, several challenges still hinder their commercialization, including the relatively low EQEs of blue/white devices, limited EQEs in large-area devices, poor device stability, as well as the toxicity of the easily accessible lead components and the solvents used in the synthesis and processing of PeLEDs. This roadmap addresses the current and future challenges in PeLEDs across fundamental and applied research areas, by sharing the community's perspectives. This work will provide the field with practical guidelines to advance PeLED development and facilitate more rapid commercialization.Comment: 103 pages, 29 figures. This is the version of the article before peer review or editing, as submitted by an author to Journal of Physics: Photonics. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from i

    Efficient photon management with nanostructures for photovoltaics

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    Efficient photon management schemes are crucial for improving the energy conversion efficiency of photovoltaic devices; they can lead potentially to reduced material usage and cost for these devices. In this review, photon trapping mechanisms are discussed briefly in the beginning, followed by a summary of recent progress on a number of major categories of nanostructures with intriguing photon management properties. Specifically, nanostructures including nanowires, nanopillars, nanopyramids, nanocones, nanospikes, and so forth, have been reviewed comprehensively with materials including Si, Ge, CdS, CIGS, ZnO, etc. It is found that these materials with diverse configurations have tunable photon management properties, namely, optical reflectance, transmittance and absorption. Investigations on these nanostructures have not only shed light on the fundamental interplay between photons and materials at the nanometer scale, but also suggested a potential pathway for a new generation of photovoltaic devices
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