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Multifunctional light-field modulation based on hybrid nonlinear metasurfaces

Chinese Physics B 2023年第10期32卷 73-89页

作者：钱树航王凯杨加兴关超龙华陆培祥 Wuhan National Laboratory for Optoelectronics and School of Physics Huazhong University of Science and TechnologyWuhan 430074China School of Electronic and Information Engineering Hubei University of Science and TechnologyXianning 437100China Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of TechnologyWuhan 430205China

The generation characteristics of nonlinear optical signals and their multi-dimensional modulation at micro-nano scale have become a prominent research area in nanophotonics,and also the key to developing various novel nonlinear photonics *** recent years,the demand for higher nonlinear conversion efficiency and device integration has led to the rapid progress of hybrid nonlinear metasurfaces composed of nanostructures and nonlinear *** a joint platform of stable wavefront modulation,nonlinear metasurface and efficient frequency conversion,hybrid nonlinear metasurfaces offer a splendid opportunity for developing the next-generation of multipurpose flat-optics *** article provides a comprehensive review of recent advances in hybrid nonlinear metasurfaces for light-field *** advantages of hybrid systems are discussed from the perspectives of multifunctional light-field modulation,valleytronic modulation,and quantum ***,the remaining challenges of hybrid metasurfaces are summarized and future developments are also prospected.

关键词： light-field modulation hybrid metasurfaces nonlinear optics two-dimensional materials

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Interfacial engineering for efficient and stable two-terminal perovskite-based tandem solar cells

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Rare Metals 2024年第11期43卷 5573-5624页

作者： Ying Li Di-Sheng Yao Fei Long Guo-Zhen Zhang Feng Yu Guangxi Key Laboratory of Optical and Electronic Material and Devices School of Materials Science and EngineeringGuilin University of TechnologyGuilin 541004China Guangxi Key Laboratory of Optical and Electronic Material and Devices School of Materials Science and EngineeringCollaborative Innovation Center for Exploration of Nonferrous Metal Deposits and Efficient Utilization of ResourcesGuilin University of TechnologyGuilin 541004China School of Chemistry and Materials Science Nanjing University of Information Science and TechnologyNanjing 210044China

Two-terminal(2T)tandem solar cells(TSCs)are optically and electrically connected by two subcells with complementary bandgaps,which are designed to overcome the Shockley-Queisser(S-Q)limit of singlejunction solar ***-inorganic hybrid perovskites are ideal light-absorbing materials for 2T TSCs due to their tunable bandgaps,low-temperature solution-based processing,and excellent light absorption ***,2T perovskite-based TSCs(PTSCs)have aroused widespread interest among the photovoltaic *** present,the key to obtaining efficient and stable 2T PTSCs is establishing efficient interfaces and layers with good photoelectric properties and high compatibility of *** particular,interfacial engineering based on effective recombination layers(RCLs)and buffers has a prominent effect on achieving enhanced power conversion efficiency(PCE)of 2T PTSCs with improved operational *** this article,the current frontier issues of 2T PTSCs including different device structures and properties are reviewed in detail to analyze their merits,demerits and solutions to overcome ***,the component engineering,interface engineering and theoretical PCE analysis for designing 2T PTSCs proposed by material simulations are ***,the scalability of interfacial passivation from single-junction perovskite solar cells to 2T PTSCs is evaluated,and the function mechanisms of RCLs and buffers are also summarized and analyzed ***,the challenges faced by 2T PTSCs are pointed out,and their developme nt directions are *** article aims to provide viable guidance for realizing practical manufacturing technologies for the commercialization of 2T PTSCs.

关键词： Two-terminal tandem solar cells Organic-inorganic perovskites Passivation interfaces Recombination layers and buffers Efficiency and stability

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Energy-Efficient Relay Selection and Power Allocation Optimization for Lifetime Maximization in Underwater Acoustic Sensor Networks

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IEEE Sensors Journal 2025年第11期25卷 20854-20869页

作者： Xu, Hengyu Ye, Fang Su, Hang Su, Chunxia Harbin Engineering University Key Laboratory of Advanced Marine Communication and Information Technology College of Information and Communication Engineering Harbin150001 China Harbin Engineering University National Key Laboratory of Underwater Acoustic Technology College of Information and Communication Engineering Harbin150001 China Suzhou University of Science and Technology School of Electronic and Information Engineering Suzhou215009 China

Underwater acoustic sensor networks (UASNs) play a crucial role in marine data collection. However, due to harsh underwater channel conditions and the finite energy supply of sensor nodes, underwater data transmission faces difficulties such as low reliability, limited spectrum, and constrained energy resources. How to ensure the performance of UASNs, such as network lifetime and energy efficiency (EE), under limited resources is a critical problem that needs to be addressed. To tackle these challenges, a matching game-based approach for relay selection and power allocation is proposed in this paper. Specifically, we model the network lifetime maximization (NLM) problem under resource constraints as a matching game problem, and develop an iterative matching algorithm based on NLM to ensure stable outcomes for relay selection and power allocation. Additionally, we devise a power allocation algorithm focused on energy efficiency to enhance system EE while guaranteeing NLM. The simulation results show that the proposed strategy greatly surpasses other benchmark algorithms in extending network lifetime and optimizing EE, validating its effectiveness and practicality. © 2001-2012 IEEE.

关键词： Relays Resource management Sensors Optimization Energy efficiency Underwater acoustics Wireless sensor networks Energy consumption Games Game theory

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Angle robust transmitted plasmonic colors with different surroundings utilizing localized surface plasmon resonance

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Chinese Physics B 2023年第7期32卷 226-233页

作者：高旭峰王琦张世杰洪瑞金张大伟 Shanghai Key Laboratory of Modern Optic Systems Engineering Research Center of Optical Instrument and SystemMinistry of Education and Shanghai Key Laboratory of Modern Optical SystemsSchool of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and TechnologyShanghai 200093China

Color filters in different surroundings inherently suffer from angular sensitivity,which hinders their practical ***,we present an angle-insensitive plasmonic filter that can produce different color responses to different surrounding *** color filters are based on a two-dimensional periodically and randomly distributed silver nanodisk array on a silica *** proposed plasmonic color filters not only produce bright colors by altering the diameter of the Ag nanodisk,but also achieve continuous color palettes by changing the surrounding *** to the weak coupling between the metallic nanodisks,the plasmonic color filters can enable good incident angle-insensitive properties(up to 30°).The strategy presented here could exhibit robust and promising applicability in anti-counterfeiting and imaging technologies.

关键词： plasmonic color filter color sensing high angular tolerance

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Wireless Interference Classification with Low Complexity Multi-Branch Networks

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China Communications 2023年第4期20卷 382-394页

作者： Song Ma Yufan Cheng Ying Mou Pengyu Wang Qihang Peng Jun Wang National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of ChinaChengdu 611731China School of Information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

In non-cooperative communication systems,wireless interference classification(WIC)is one of the most essential ***,deep learning(DL)based WIC methods have been ***,conventional DL-based WIC methods have high computational complexity and unsatisfactory accuracy,especially when the interference-tonoise ratio(INR)is *** this end,we propose three effective ***,we introduce multibranch convolutional neural networks(CNNs)for interference *** multi-branch CNN is constructed by repeating a layer that aggregates several transformations with the same topology,and it notably improves the recognition ability for *** design avoids the carefully crafted selection of each ***,multi-branch CNNs are computationally expensive and *** this end,we further propose Low complexity multibranch networks(LCMN),which are mathematically equivalent to multi-branch CNNs but maintain low computing costs and efficient ***,we present novel loss function,which encourages networks to have consistent prediction probabilities for samples with high visual similarities,resulting in increasing recognition accuracy of *** results demonstrate the proposed methods consistently boost the classification performance of WIC without substantially increasing computational overhead compared to traditional DL-based methods.

关键词： electromagnetic interference wireless interference identification deep learning multi-branch architectures

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Online Optimization in Power systems With High Penetration of Renewable Generation:Advances and Prospects

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 839-858页

作者： Zhaojian Wang Wei Wei John Zhen Fu Pang Feng Liu Bo Yang Xinping Guan Shengwei Mei Key Laboratory of System Control and Information Processing Ministry of Education of ChinaDepartment of AutomationShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Power System and the Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Institute of High Performance Computing(IHPC) Agency for Science Technology and Research(A*STAR)Singapore 138632Singapore

Traditionally,offline optimization of power systems is acceptable due to the largely predictable loads and reliable *** increasing penetration of fluctuating renewable generation and internet-of-things devices allowing for fine-grained controllability of loads have led to the diminishing applicability of offline optimization in the power systems domain,and have redirected attention to online optimization ***,online optimization is a broad topic that can be applied in and motivated by different settings,operated on different time scales,and built on different theoretical *** paper reviews the various types of online optimization techniques used in the power systems domain and aims to make clear the distinction between the most common techniques *** particular,we introduce and compare four distinct techniques used covering the breadth of online optimization techniques used in the power systems domain,i.e.,optimization-guided dynamic control,feedback optimization for single-period problems,Lyapunov-based optimization,and online convex optimization techniques for multi-period ***,we recommend some potential future directions for online optimization in the power systems domain.

关键词： optimization Lyapunov optimization online convex optimization online optimization optimization-guided control

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Fine-Grained Cross-Modal Fusion Based Refinement for Text-to-Image Synthesis

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Chinese Journal of Electronics 2023年第6期32卷 1329-1340页

作者： SUN Haoran WANG Yang LIU Haipeng QIAN Biao Department of Computer Science and Information Engineering Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data Ministry of EducationHefei University of Technology

Text-to-image synthesis refers to generating visual-realistic and semantically consistent images from given textual descriptions. Previous approaches generate an initial low-resolution image and then refine it to be high-resolution. Despite the remarkable progress, these methods are limited in fully utilizing the given texts and could generate text-mismatched images, especially when the text description is complex. We propose a novel finegrained text-image fusion based generative adversarial networks(FF-GAN), which consists of two modules: Finegrained text-image fusion block(FF-Block) and global semantic refinement(GSR). The proposed FF-Block integrates an attention block and several convolution layers to effectively fuse the fine-grained word-context features into the corresponding visual features, in which the text information is fully used to refine the initial image with more details. And the GSR is proposed to improve the global semantic consistency between linguistic and visual features during the refinement process. Extensive experiments on CUB-200 and COCO datasets demonstrate the superiority of FF-GAN over other state-of-the-art approaches in generating images with semantic consistency to the given texts.

关键词： Visualization Fuses Convolution Semantics Linguistics Benchmark testing Generative adversarial networks

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Remote entangling gate between a quantum dot spin and a transmon qubit mediated by microwave photons

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Chinese Physics B 2024年第2期33卷 52-59页

作者：朱行宇朱乐天涂涛李传锋 Key Laboratory of Quantum Information Chinese Academy of SciencesUniversity of Science and Technology of ChinaHefei 230026China School of Mechanical and Electronic Engineering Suzhou UniversitySuzhou 234000China Hefei National Laboratory University of Science and Technology of ChinaChinese Academy of SciencesHefei 230088China

Spin qubits and superconducting qubits are promising candidates for realizing solid-state quantum information *** a hybrid architecture that combines the advantages of different qubits on the same chip is a highly desirable but challenging *** we propose a hybrid architecture that utilizes a high-impedance SQUID array resonator as a quantum bus,thereby coherently coupling different solid-state *** employ a resonant exchange spin qubit hosted in a triple quantum dot and a superconducting transmon *** this hybrid system is highly tunable,it can operate in a dispersive regime,where the interaction between the different qubits is mediated by virtual *** utilizing such interactions,entangling gate operations between different qubits can be realized in a short time of 30 ns with a fidelity of up to 96.5%under realistic parameter *** utilizing this interaction,remote entangled state between different qubits can be prepared and is robust to perturbations of various *** results pave the way for exploring efficient fault-tolerant quantum computation on hybrid quantum architecture platforms.

关键词： hybrid quantum architectures circuit quantum electrodynamics entangling gate

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Bi-Directional and Triangular Circulation Fusion Neural Networks for Small Object Detection

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IEEE Transactions on Circuits and systems for Video technology 2024年第6期35卷 5140-5152页

作者： Li, Fangyu Duan, Junzhu Zhang, Qiyu Shan, Caifeng Han, Honggui the School of Information Science and Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Engineering Research Center of Digital Community Ministry of Education Beijing Artificial Intelligence Institute Beijing University of Technology Beijing100124 China the State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China the School of Intelligence Science and Technology Nanjing University Suzhou215163 China

Deep learning-driven object detection models are capable of accurately identifying and localizing objects. However, small objects contain limited information relative to global features, resulting in the fact that detection models often do not learn small object features adequately. To enhance the precision in detecting small objects, we propose a bi-directional and triangular circulation fusion neural network (BTFN). First, to selectively strengthen the position features of small objects, we propose a feature circulation extraction module composed of a bi-directional triangular densely nested convolutional network (BTF), thus achieving repetitive multi-layer feature fusion. Second, to fill up the semantic gaps between different scales of features, we design a mixed dual attention module (MDA) in the bi-directional triangular densely nested network. Third, to mitigate the lost information in the neural networks with deep layers as well as improve the inference time, we design a re-parameterization bi-directional composite feature fusion module (Rep-BFM) that fuses the features of multiple scales. The proposed model is evaluated extensively on the MS COCO, Tsinghua-Tencent 100k, and Haier dismantled parts of used home appliances datasets. The experiment results show that the proposed model improves the AP on MS COCO by 4%, especially the APS of small objects is improved by 7.7% compared with SOTA models. © 2024 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Domestic appliances

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MCFF-Net: Multi-Scale Contextual Feature Fusion Network for Polyp Segmentation

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Journal of Shanghai Jiaotong University (science) 2025年 1-13页

作者： Ma, Lei Yan, Jiangkai Shao, Dangguo Li, Jingtao Wang, Jiawei Yan, Yukun Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Yunnan Provincial Key Laboratory of Artificial Intelligence Kunming650500 China

In clinical practice, technologies for automatically segmenting polyps might greatly improve the speed and accuracy of medical diagnosis, significantly reducing the chances of patients developing colorectal cancer. Nevertheless, the segmentation of polyps presents a considerable challenge due to their low contrast, presence of occlusion, and intricate background disturbances. In this paper, we propose an innovative approach for segmenting polyps, called multi-scale contextual feature fusion network for polyp segmentation (MCFF-Net). Specifically, MCFF-Net includes three modules: feature enhancement module (FEM), global-local feature fusion module (GLFF), and cross-scale feature fusion module (CFFM). Among them, FEM is used to improve the features at each scale. Building on this, the CFFM enables comprehensive interaction among the information across various scales, enhancing the diversity of the feature scales extracted. Moreover, the GLFF fuses global-local features to generate a rough object localization map. This map further modulates the fusion features from the CFFM, facilitating more precise segmentation. On five publicly available datasets, our approach not only segments various polyp types but also surpasses existing methods in terms of accuracy and generalizability. © Shanghai Jiao Tong University 2024.

关键词： Diseases

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