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Abstract Iron-based nanotubes are promising candidates for high performance electromagnetic wave absorbing fillers due to their high aspect ratio, light weight, high axial permeability and high saturation magnetization. Furthermore, the introduction of carbon can improve dielectric loss and block the agglomeration of iron nanotubes. Here, Fe@C composite nanotubes were prepared by introducing carbon onto the surface of precursor α-FeOOH’ fibers followed by hydrogen-thermal annealing. We find that Fe@C composite nanotubes retain the one-dimensional nanostructure of the precursor throughout the annealing. The well-developed lattice and nanostructure of Fe@C nanotubes endow high saturation magnetization, high anisotropy, suppressed eddy current effect and cross-particle exchange coupling as well, and thus contribute to an enhanced permeability. Coatings with Fe@C as fillers achieve a reflection loss of up to −69.34 dB at 3.37 GHz at the matching thickness of 3.97 mm. The Fe@C composite nanotubes developed here are a promising candidate for high performance electromagnetic wave absorbing fillers.

FeSiAl alloys with a composition of Fe-9.6Si-5.4Al, also known as Sendust alloys, present the unique potential to exhibit efficient electromagnetic wave absorption (EMA) in the P-band. However, the electromagnetic properties of this type of alloy are highly sensitive to the shape, microstructure, and microchemistry, which then inspire the current research. The evolution of the microstructure/microchemistry of FeSiAl particles was systematically revealed in a single particle scale for the first time, and the resulting influence on the electromagnetic properties was investigated. Recrystallization occurs in the annealing process on FeSiAl particles and the oxide films on the surface evolve evidently when annealed in 5%H2/Ar or air, which can conduce improved electromagnetic properties. The FeSiAl particles annealed in 5%H2/Ar present efficient EMA in the P-L band while those in air contribute to high reflection loss. This work indicates the feasibility of achieving a high and adjustable EMA efficiency in the P-L band through microstructure and microchemistry tailoring.

Abstract Neuro-inspired vision systems hold great promise to address the growing demands of mass data processing for edge computing, a distributed framework that brings computation and data storage closer to the sources of data. In addition to the capability of static image sensing and processing, the hardware implementation of a neuro-inspired vision system also requires the fulfilment of detecting and recognizing moving targets. Here, we demonstrated a neuro-inspired optical sensor based on two-dimensional NbS2/MoS2 hybrid films, which featured remarkable photo-induced conductance plasticity and low electrical energy consumption. A neuro-inspired optical sensor array with 10 × 10 NbS2/MoS2 phototransistors enabled highly integrated functions of sensing, memory, and contrast enhancement capabilities for static images, which benefits convolutional neural network (CNN) with a high image recognition accuracy. More importantly, in-sensor trajectory registration of moving light spots was experimentally implemented such that the post-processing could yield a high restoration accuracy. Our neuro-inspired optical sensor array could provide a fascinating platform for the implementation of high-performance artificial vision systems.

Objective Analyze the current situation, hotspots and development trends of sarcopenia animal model to provide research direction and basic information for sarcopenia animal model research.Methods English literature of research on animal models of sarcopenia was retrieved from the Web of Science core data (WOS) set from 1900-01-01 to 2022-12-31. Chinese literature related to animal models of sarcopenia was retrieved from CNKI database between 1915 and 2022. The bibliometric analysis software VOSviewer was used to explore the countries, orgonizations, authors, hotspots and frontier directions in these studies.Results A total of 2 819 articles on animal models of sarcopenia were retrieved from WOS core database. The first paper was published in 1995. The United States has the largest number of animal model studies of sarcopenia with 1 105 articles. The institution with the most published articles is the University of Florida in the United States, with 69 articles. The University of Hong Kong has the highest number of publications in China, with 20 articles. American author Van Remmen H, with 50 publications, is the author of the most articles. The journal with the largest number of articles published on animal models of sarcopenia is the American journal called FASEB Journal, with 196 articles. In total, 423 articles on animal models of sarcopenia were retrieved from the CNKI database. Author LI Zhuyi has published 19 articles, and is the author of the most articles in China. The keyword co-occurrence clustering analysis of WOS literature search found that the research focus on animal model of sarcopenia can be summarized as the correlation between sarcopenia and metabolism, cytology and regenerative medicine of sarcopenia animal models, the study of sarcopenia animal models in bone, muscle, nerve and exercise therapy. The retrieval results of CNKI database revealed that the most extensive research was about on the model of denervated sarcopenia, and researches on the effects of Chinese medicine on sarcopenia were also widely reported. Through reading the full articles or abstracts of the literature, the animal models of sacopenia mainly include natural aging model, genetic modification model, high-fat diet induction model, disuse model, hormone induction model and complex sarcopenia models of other diseases.Conclusion In recent years, the study on animal model of sarcopenia has become a hotspot at home and abroad.The bibliometric analysis provides a basis for the research of animal models of sarcopenia in terms of research direction, hotspots, model animal selection, animal model making, and domestic and international communication and cooperation.