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Study on surface discharge of nonlinear conductive epoxy resin/SrTiO3 composites in 80–300 K temperature zone

high voltage 2024年第1期9卷 117-126页

作者： Yunqi Xing Bin Wang Mingyang Wang Jiakai Chi Peng Jia Rongjin Huang State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of TechnologyTianjinChina Key Laboratory of Electormagnetic Field and Electrical Apparatus Reliability of Hebei Province Hebei University of TechnologyTianjinChina Key Laboratory of Special Machine and high voltage Apparatus(Ministry of Education) Shenyang University of TechnologyShenyangChina State Grid Tianjin high voltage Company TianjinChina China Energy Engineering Group Tianjin Electric Power Design institute Co. Ltd.TianjinChina CAS Key Laboratory of Cryogenics Technical Institute of Physics and ChemistryBeijingChina

Bisphenol F epoxy resin(EP)is often used in terminal current lead insulation of superconducting equipment because of its good insulation performance,high mechanical strength,good toughness at cryogenic temperatures,and resistance to cold shock and heat shock.However,due to the wide temperature range of 80–300 K and the strong electric field,the EP-N_(2)interface is prone to surface flashover,resulting in terminal insulation failure.To improve the reliability of the current lead insulation,non-linear conductive EP/strontium titanate(SrTiO_(3))composites were prepared by modification with nano filling.The changes of dielectric,surface discharge,flashover,and trap distribution characteristics of composite materials were studied,and the mechanism of SrTiO_(3)on the surface flashover of composite materials was analysed.The results show that the conductivity of the composite increases with the rise of SrTiO_(3)filling content,and the amplitude of improvement is greater under the strong electric field,showing a more significant non-linearity.The composite has a lower trap energy level and a greater number of shallow traps compared to pure EP,which accelerates surface charge detrapping and reduces charge accumulation,effectively enhancing the discharge and surface flashover voltage of the composite.

关键词： composites composite insulation

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Recess-free enhancement-mode AlGaN/GaN RF HEMTs on Si substrate

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Journal of Semiconductors 2024年第6期45卷 81-86页

作者： Tiantian Luan Sen Huang Guanjun Jing Jie Fan Haibo Yin Xinguo Gao Sheng Zhang Ke Wei Yankui Li Qimeng Jiang Xinhua Wang Bin Hou Ling Yang Xiaohua Ma Xinyu Liu high-Frequency high-voltage Device and Integrated Circuits R&D Center Institute of Microelectronics of Chinese Academy of SciencesBe i-jing 100029China School of integrated Circuits University of Chinese Academy of SciencesBeijing 100049China Faculty of integrated Circuits Xidian UniversityXi’an 710071China

Enhancement-mode(E-mode)GaN-on-Si radio-frequency(RF)high-electron-mobility transistors(HEMTs)were fabri-cated on an ultrathin-barrier(UTB)AlGaN(<6 nm)/GaN heterostructure featuring a naturally depleted 2-D electron g... 详细信息

Enhancement-mode(E-mode)GaN-on-Si radio-frequency(RF)high-electron-mobility transistors(HEMTs)were fabri-cated on an ultrathin-barrier(UTB)AlGaN(high threshold voltage(VTH)of+1.1 V with good uniformity.A maxi-mum current/power gain cut-off frequency(fT/fMAX)of 31.3/99.6 GHz with a power added efficiency(PAE)of 52.47%and an out-put power density(Pout)of 1.0 W/mm at 3.5 GHz were achieved on the fabricated E-mode HEMTs with 1-μm gate and Au-free ohmic contact.

关键词： AlGaN/GaN heterostructure ultrathin-barrier enhancement-mode radio-frequency power added efficiency silicon substrate

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highly efficient 1D p-Te/2D n-Bi_(2)Te_(3) heterojunction self-driven broadband photodetector

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Nano Research 2024年第3期17卷 1864-1874页

作者： Chenchen Zhao Dongbo Wang Jiamu Cao Zhi Zeng Bingke Zhang Jingwen Pan Donghao Liu Sihang Liu Shujie Jiao Tianyuan Chen Gang Liu Xuan Fang Liancheng Zhao Jinzhong Wang School of Materials Science and Engineering Harbin Institute of TechnologyHarbin 150001China School of Astronautics Harbin Institute of TechnologyHarbin 150001China Center for high Pressure Science and technology Advanced Research Shanghai 201203China State Key Laboratory of high Power Semiconductor Lasers Changchun University of Science and TechnologyChangchun 130022China

Broadband photodetectors with self-driven functions have attracted intensive scientific interest due to their low energy consumption and high optical gain.However,high-performance broadband self-driven photodetectors are still a significant challenge due to the complex fabrication processes,environmental toxicity,high production costs of traditional 3D semiconductor materials and sharply raised contact resistance,severe interfacial recombination of 2D materials and 2D/3D mixed dimension heterojunction.Here,1D p-Te/2D n-Bi_(2)Te_(3) heterojunctions are constructed by the simple and low-cost hydrothermal method.1D p-Te/2D n-Bi_(2)Te_(3) devices are applied in photoelectrochemical(PEC)photodetectors,with their high performance attributed to the good interfacial contacts reducing interface recombination.The device demonstrated a broad wavelength range(365–850 nm)with an Iph/Idark as high as 377.45.The R_(i),D^(*),and external quantum efficiency(EQE)values of the device were as high as 12.07 mA/W,5.87×10^(10) Jones,and 41.05%,respectively,which were significantly better than the performance of the prepared Bi_(2)Te_(3) and Te devices.A comparison of the freshly fabricated device and the device after 30 days showed that 1D p-Te/2D n-Bi_(2)Te_(3) had excellent stability with only 18.08%decay of photocurrent.It is anticipated that this work will provide new emerging material for future design and preparation of a high-performance self-driven broadband photodetector.

关键词： topological insulating states interfacial recombination self-driven 1D p-Te/2D n-Bi_(2)Te_(3) photodetector

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Nanophononic metamaterials induced proximity effect in heat flux regulation

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Frontiers of physics 2024年第2期19卷 149-156页

作者： Jian Zhang Haochun Zhang Gang Zhang School of Energy Science and Engineering Harbin Institute of TechnologyHarbin 150001China institute of high Performance Computing Agency for ScienceTechnology and Research(A*STAR)Singapore 138632Singapore

Recent studies have shown that the construction of nanophononic metamaterials can reduce thermal conductivity without affecting electrical properties,making them promising in many fields of application,such as energy conversion and thermal management.However,although extensive studies have been carried out on thermal conductivity reduction in nanophononic metamaterials,the local heat flux characteristic is still unclear.In this work,we construct a heat flux regulator which includes a silicon nanofilm with silicon pillars.The regulator has remarkable heat flux regulation ability,and various impacts on the regulation ability are explored.Surprisingly,even in the region without nanopillars,the local heat current is still lower than that in pristine silicon nanofilms,reduced by the neighboring nanopillars through the thermal proximity effect.We combine the analysis of the phonon participation ratio with the intensity of localized phonon modes to provide a clear explanation.Our findings not only provide insights into the mechanisms of heat flux regulation by nanophononic metamaterials,but also will open up new research directions to control local heat flux for a broad range of applications,including heat management,thermoelectric energy conversion,thermal cloak,and thermal concentrator.

关键词： nanophononic metamaterials proximity effect

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Bioinspired sensing-memory-computing integrated vision systems: biomimetic mechanisms, design principles, and applications

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Science China(Information Sciences) 2024年第5期67卷 5-27页

作者： Yujie HUANG Yinlong TAN Yan KANG Yabo CHEN Yuhua TANG Tian JIANG institute for Quantum Information and State Key Laboratory of high Performance Computing College of Computer National University of Defense Technology College of Advanced Interdisciplinary Studies National University of Defense Technology institute for Quantum Science and technology College of ScienceNational University of Defense Technology

With the explosion of sensory data in the Internet of Things(Io T) era, conventional machine vision systems are becoming increasingly difficult to meet the requirements of high efficiency, low energy consumption, and low latency due to their inherent shortcomings of separate sensing, memory, and computing units. Inspired by the retina and neuromorphic computing, the sensing-memory-computing integrated vision system(SMCVS) that features low power consumption, low latency, and high parallelism has been considered a promising technology to surpass the von Neumann architecture and realize strong artificial intelligence.Meanwhile, novel materials like two-dimensional semiconductors and quantum dots with novel optoelectronic performance provide hardware carriers for implementing integrated sensing-memory-computing architectures,attracting considerable attention. This paper reviews the recent research progress in bioinspired vision systems in terms of biomimetic mechanisms, design principles, computational architectures, and applications.Firstly, the biomimetic mechanisms are illustrated to guide the design of high-performance artificial visual perception systems. Then the research progress of optoelectronic-synapse-based bioinspired vision systems in the device principles and applications including image filtering, color recognition, visual adaptation, and motion detection are summarized. Finally, the challenges and future developing directions of the SMCVS are provided regarding bionic application, architecture design, and device fabrication.

关键词： sensing-memory-computing architecture neuromorphic computing retinomorphic device image recognition visual system

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Robust multi-sensor image matching based on normalized self-similarity region descriptor

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Chinese Journal of Aeronautics 2024年第1期37卷 271-286页

作者： Xuecong LIU Xichao TENG Jing LUO Zhang LI Qifeng YU Yijie BIAN College of Aerospace Science and Engineering National University of Defense TechnologyChangsha 410073China high-Tech institute Qingzhou 262500China

Multi-modal image matching is crucial in aerospace applications because it can fully exploit the complementary and valuable information contained in the amount and diversity of remote sensing images.However,it remains a challenging task due to significant non-linear radiometric,geometric differences,and noise across different sensors.To improve the performance of heterologous image matching,this paper proposes a normalized self-similarity region descriptor to extract consistent structural information.We first construct the pointwise self-similarity region descriptor based on the Euclidean distance between adjacent image blocks to reflect the structural properties of multi-modal images.Then,a linear normalization approach is used to form Modality Independent Region Descriptor(MIRD),which can effectively distinguish structural features such as points,lines,corners,and flat between multi-modal images.To further improve the matching accuracy,the included angle cosine similarity metric is adopted to exploit the directional vector information of multi-dimensional feature descriptors.The experimental results show that the proposed MIRD has better matching accuracy and robustness for various multi-modal image matching than the state-of-the-art methods.MIRD can effectively extract consistent geometric structure features and suppress the influence of SAR speckle noise using non-local neighboring image blocks operation,effectively applied to various multi-modal image matching.

关键词： Remote sensing Multi-modal image matching Template matching Feature descriptor Similarity metric Synthetic Aperture Radar(SAR)

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Review of 2D Bi2X3（X=S,Se,Te）:from preparation to photodetector

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Rare Metals 2024年第6期43卷 2349-2370页

作者： Zhi Zeng Dong-Bo Wang Xuan Fang Jia-Mu Cao Bing-Ke Zhang Jing-Wen Pan Dong-Hao Liu Si-Hang Liu Shu-Jie Jiao Tian-Yuan Chen Gang Liu Lian-Cheng Zhao Jin-Zhong Wang Department of Optoelectronic Information Science School of Materials Science and EngineeringHarbin Institute of Technology Changchun University Science and technology School of PhysicsThe State Key Laboratory of High Power Semiconductor Lasers School of Astronautics Harbin Institute of Technology Center for high Pressure Science and technology Advanced Research

Detector has become an indispensable part of human beings.The increasing demand for photodetectors with high performance has promoted the research of novel materials.At the same time,with the development of rising material system,two-dimensional（2D） materials attract a lot of attention,while the suitable option for fabricating photodetector is still limited.The prospering of bismuth chalcogenides injected new vitality for material field,thereinto,the unique topological insulator characteristics make the research on bismuth selenide（Bi2Se3） and bismuth telluride（Bi2Te3） intriguing.2D Bi2X3also exhibits unique features among various 2D materials,of which,the adjustable narrow energy band gap and polarization-sensitive photocurrent contribute to the promising application of high performance and broadband photodetector.In this review,from a bottom-up perspective,we summarize fundamental properties,synthesis method,photodetector performance of 2D Bi2X3based on the previous study,which provide an overall perspective of 2D Bi2X3.Wherein,the section of the photodetector is specifically discu ssed with regard to pure Bi2X3photodetector and heterojunction photodetector.A brief summary and outlook were also explored in the end.

关键词： Bi 2 X 3 Preparation 2D Photodetector

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Solid-state atomic hydrogen as a broad-spectrum RONS scavenger for accelerated diabetic wound healing

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National Science Review 2024年第2期11卷 196-206页

作者： Man Luo Qin Wang Gang Zhao Wei Jiang Cici Zeng Qingao Zhang Ruyu Yang Wang Dong Yunxi Zhao Guozhen Zhang Jun Jiang Yucai Wang Qing Zhu Key Laboratory of Precision and Intelligent Chemistry School of Chemistry and Materials Science University of Science and Technology of China Department of Radiology The First Affiliated Hospital of University of Science and Technology of China Division of Life Sciences and Medicine University of Science and Technology of China Shenzhen Senior high School institute of Intelligent Innovation Henan Academy of Sciences

Hydrogen therapy shows great promise as a versatile treatment method for diseases associated with the overexpression of reactive oxygen and nitrogen species（RONS）. However, developing an advanced hydrogen therapy platform that integrates controllable hydrogen release, efficient RONS elimination, and biodegradability remains a giant technical challenge. In this study, we demonstrate for the first time that the tungsten bronze phase H0.53WO3（HWO） is an exceptionally ideal hydrogen carrier, with salient features including temperature-dependent highly-reductive atomic hydrogen release and broad-spectrum RONS scavenging capability distinct from that of molecular hydrogen. Moreover, its unique p H-responsive biodegradability ensures post-therapeutic clearance at pathological sites. Treatment with HWO of diabetic wounds in an animal model indicates that the solid-state atomic H promotes vascular formation by activating M2-type macrophage polarization and anti-inflammatory cytokine production, resulting in acceleration of chronic wound healing. Our findings significantly expand the basic categories of hydrogen therapeutic materials and pave the way for investigating more physical forms of hydrogen species as efficient RONS scavengers for clinical disease treatment.

关键词： atomic hydrogen RONS scavenger inflammatory regulation diabetic wound healing hydrogen therapy

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Deep Guided Attention Network for Joint Denoising and Demosaicing in Real Image

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Chinese Journal of Electronics 2024年第1期33卷 303-312页

作者： Tao ZHANG Ying FU Jun ZHANG School of Computer Science and technology Beijing Institute of Technology Advanced Reasearch institute of Multidisciplinary Science Beijing Institute of Technology

Denoising(DN) and demosaicing(DM) are the first crucial stages in the image signal processing pipeline. Recently, researches pay more attention to solve DN and DM in a joint manner, which is an extremely undetermined inverse problem. Existing deep learning methods learn the desired prior on synthetic dataset, which limits the generalization of learned network to the real world data. Moreover, existing methods mainly focus on the raw data property of high green information sampling rate for DM, but occasionally exploit the high intensity and signalto-noise(SNR) of green channel. In this work, a deep guided attention network(DGAN) is presented for real image joint DN and DM(JDD), which considers both high SNR and high sampling rate of green information for DN and DM, respectively. To ease the training and fully exploit the data property of green channel, we first train DN and DM sub-networks sequentially and then learn them jointly, which can alleviate the error accumulation. Besides, in order to support the real image JDD, we collect paired raw clean RGB and noisy mosaic images to conduct a realistic dataset. The experimental results on real JDD dataset show the presented approach performs better than the state-of-the-art methods, in terms of both quantitative metrics and qualitative visualization.

关键词： Image denoising Image demosaicing Joint processing Guided attention Paired real dataset

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Towards full-stack deep learning-empowered data processing pipeline for synchrotron tomography experiments

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The Innovation 2024年第1期5卷 127-138页

作者： Zhen Zhang Chun Li Wenhui Wang Zheng Dong Gongfa Liu Yuhui Dong Yi Zhang National Synchrotron Radiation Laboratory University of Science and Technology of ChinaHefei 230029China Beijing Synchrotron Radiation Facility Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China

Synchrotron tomography experiments are transitioning into multifunctional,cross-scale,and dynamic characterizations,enabled by new-generation synchrotron light sources and fast developments in beamline instrumentation.However,with the spatial and temporal resolving power entering a new era,this transition generates vast amounts of data,which imposes a significant burden on the data processing end.Today,as a highly accurate and efficient data processing method,deep learning shows great potential to address the big data challenge being encountered at future synchrotron beamlines.In this review,we discuss recent advances employing deep learning at different stages of the synchrotron tomography data processing pipeline.We also highlight how applications in other data-intensive fields,such as medical imaging and electron tomography,can be migrated to synchrotron tomography.Finally,we provide our thoughts on possible challenges and opportunities as well as the outlook,envisioning selected deep learning methods,curated big models,and customized learning strategies,all through an intelligent scheduling solution.

关键词： processing pipeline outlook

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