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MoS_(2)core-shell nanoparticles prepared through liquid-phase ablation and light exfoliation of femtosecond laser for chemical sensing

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Science China(Technological Sciences) 2023年第3期66卷 853-862页

作者： ZUO Pei JIANG Lan LI Xin TIAN MengYao YUAN YongJiu HAN WeiNa MA Le HU LiFei HE ZhiCong LI Fang School of Mechanical and Electrical Engineering Hubei Key Laboratory of Optical Information and Pattern RecognitionSchool of Optical Information and Energy EngineeringWuhan Institute of TechnologyWuhan 430073China Laser Micro/Nano Fabrication Laboratory School of Mechanical EngineeringBeijing Institute of TechnologyBeijing 100081China Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China

Molybdenum disulfide(MoS_(2))-based nanostructures are highly desirable for applications such as chemical and biological sensing,photo/electrochemical catalysis,and energy storage due to their unique physical and chemical *** this work,MoS_(2)core-shell nanoparticles were first prepared through the liquid-phase processing of bulk MoS2by a femtosecond *** core of prepared nanoparticles was incompletely and weakly crystalline MoS_(2);the shell of prepared nanoparticles was highly crystalline MoS_(2),which wrapped around the core layer by *** femtosecond laser simultaneously achieved liquid-phase ablation and light *** formation mechanism of the core-shell nanoparticles is to prepare the nanonuclei first by laser liquid-phase ablation and then the nanosheets by light exfoliation;the nanosheets will wrap the nanonuclei layer by layer through van der Waals forces to form core-shell *** MoS_(2)core-shell nanoparticles,because of Mo-S bond breakage and recombination,have high chemical activity for chemical ***,the nanoparticles were used as a reducing agent to directly prepare three-dimensional(3D)Au-MoS_(2)micro/nanostructures,which were applied as surface-enhanced Raman spectroscopy(SERS)substrates to explore chemical sensing *** ultrahigh enhancement factor(1.06×10^(11)),ultralow detection limit(10-13M),and good SERS adaptability demonstrate highly sensitive SERS activity,great ability of ultralow concentration detection,and ability to detect diverse analytes,*** work reveals the tremendous potential of 3D Au-MoS_(2)composite structures as excellent SERS substrates for chemical and biological sensing.

关键词： MoS_(2)core-shell nanoparticle femtosecond laser liquid-phase ablation light exfoliation 3D Au-MoS_(2)composite structure chemical sensing

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Yield enhancement of elliptical high harmonics driven by bicircular laser pulses

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Chinese Physics B 2022年第11期31卷 358-363页

作者： Xiaofan Zhang Xiaosong Zhu Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of TechnologyWuhan 430205China Wuhan National Laboratory for Optoelectronics and School of Physics Huazhong University of Science and TechnologyWuhan 430074China

We theoretically investigate the yield enhancement of elliptical high harmonics in the interaction of molecules with bicircular laser pulses by solving the time-dependent Schrodinger *** is shown that by adjusting the relative intensity ratio of the two bicircular field components in specific ranges the yield of the molecular high harmonics for the plateau and cutoff regions can be respectively *** analyze this enhancement phenomenon,we calculate the weights of the electron classical ***,we also study the ellipticity distribution of harmonics for different intensity *** find that these enhanced harmonics are elliptically polarized,which we mainly attribute to the recombination dipole moment of the major weighted *** enhanced elliptical extreme ultraviolet and soft x-ray radiations may serve as essential tools for exploring the ultrafast dynamics in magnetic materials and chiral media.

关键词： high harmonics extreme ultraviolet and soft x-ray bicircular laser pulses

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Semi-supervised PolSAR Image Change Detection using Similarity Matching

Semi-supervised PolSAR Image Change Detection using Similari...

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ISPRS Technical Commission I Midterm Symposium on Intelligent Sensing and Remote Sensing Application

作者： Wang, Lei Peng, Lingmu Hong, Hanyu Zhao, Shuwei Lv, Qiwen Gui, Rong Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of Technology Hubei Wuhan430205 China School of Geosciences and Info-physics Central South University Changsha410083 China

The lack of precisely labeled data limits the development of supervised polarimetric synthetic aperture radar (PolSAR) image change detection. Therefore, semi-supervised deep learning methods have recently demonstrated their significant capability for PolSAR image change detection. Similarity Matching (SimMatch) improves the performance of semi-supervised learning tasks across different benchmark datasets and different settings. Introducing SimMatch into the field of PolSAR image change detection can improve the performance of semi-supervised PolSAR image change detection under limited labeled data conditions. Usually, semi-supervision solves the problem of insufficient labeled data by generating pseudo-labels. However, when the pseudo-label method is simply applied, the model will fit on the confident but wrong pseudo-labels, resulting in poor performance. SimMatch offers a solution by requiring the strongly augmented view to share the same semantic similarity (i.e. label prediction) and instance characteristics (i.e. similarity between instances) with a weak augmented view for more intrinsic feature matching. Besides, by using a labeled memory buffer, the two similarities can be isomorphically transformed with each other by introducing the aggregating and unfolding techniques. Therefore, the semantic and instance pseudo-labels can be mutually propagated, and then, the detection performance of the PolSAR image change detection is improved. Experimental results on real PolSAR datasets demonstrated that SimMatch is an effective semi-supervised PolSAR change detection method and its performance surpasses some well-known change detection methods. Compared to the fully-supervised algorithm CWNN, the semi-supervised SimMatch algorithm can improve accuracy by up to 14.4%. © Author(s) 2024.

关键词： Change detection

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Dynamic Non-Invasive Detection of NADH Based on Blood Flow-Mediated Skin Fluorescence (FMSF) Method

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Open Journal of Applied Sciences 2024年第6期14卷 1437-1453页

作者： Peng Liu Tengfei Bi Gongzhi Du Long Yan Huayi Hou Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of Technology Wuhan China

Nicotinamide adenine dinucleotide (NADH/NAD+) is involved in important biochemical reactions in human metabolism, including participation in energy production by mitochondria. The changes in fluorescence intensity as a function of time in response to blocking and releasing of blood flow in a forearm are used as a measure of oxygen transport with blood to the tissue, which directly correlates with the skin microcirculation status. In this paper, a non-invasive dynamic monitoring system based on blood flow-mediated skin fluorescence (FMSF) technology is developed to monitor the NADH fluorescence intensity of skin tissue during the process of blocking reactive hyperemia. Simultaneously, laser speckle contrast imaging (LSCI) and laser Doppler flowmetry (LDF) were used to observe blood flow, blood oxygen saturation (SOt2) and relative amount of hemoglobin (rHb) during the measurement process, which helped to explore NADH dynamics relevant physiological changes. A variety of parameters have been derived to describe NADH fluorescence curve based on the FMSF device. The experimental results are conducive to understanding the NADH measurement and the physiological processes related to it, which help FMSF to be a great avenue for in vivo physiological, clinical and pharmacological research on mitochondrial metabolism.

关键词： Reduced Nicotinamide Adenine Dinucleotide (NADH) Flow-Mediated Skin Fluorescence (FMSF) Laser Doppler Flowmetry (LDF) Blood Flow

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SAR Image Water Extraction Based on Saliency Target Detection

SAR Image Water Extraction Based on Saliency Target Detectio...

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2022 International Conference on Artificial Intelligence and Computer information Technology, AICIT 2022

作者： Wang, Pengtian Zhang, Haibo Lv, Qiwen Zhao, Shuwei Wang, Lei Wuhan Institute of Technology Hubei Key Laboratory of Optical Information and Pattern Recognition China

ISBN: (数字)9781665450874

ISBN: (纸本)9781665450874

Synthetic aperture radar (SAR) image water extraction has important research significance in water resources monitoring and other applications. In SAR images, the scattering properties of some land cover types with low backscattering coefficients, such as broad roads and mountain shadows, are very close to the scattering properties of water. Most water extraction methods are easy to identify those false water targets as water. Meanwhile, the water area in the scene is very small, and the proportion of water and background in the training concentration is extremely unbalanced. The imbalance of water samples affects the water extraction performance. Traditional machine learning water extraction methods require manual extraction of effective features, which are time-consuming and inefficient. Therefore, we decided to introduce the deep learning-based salient object detection network Pool-Net into SRA image water extraction. To overcome the effect of class imbalance, we introduce the focus loss function into the Pool-Net network. Experimental results show that the proposed method achieves good water extraction results on water class imbalanced SAR images. The water extraction accuracy of the proposed method is 2& higher than Pool-Net and also surpasses some well-known image segmentation methods. © 2022 IEEE.

关键词： Synthetic aperture radar

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Photovoltaic panel string detection based on prior knowledge and feature learning 12

Photovoltaic panel string detection based on prior knowledge...

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SPIE 12th International Symposium on Multispectral Image Processing and pattern recognition, MIPPR 2023

作者： Li, Bolin Cheng, Bolin Ye, Liang Hubei Key Laboratory of Optical Information and Pattern Recognition China Hubei Engineering Research Center of Video Image and HD Projection China School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan430205 China

ISBN: (数字)9781510674943

ISBN: (纸本)9781510674936

Image-based photovoltaic panel inspection has become one of the important tasks of photovoltaic power generation. Due to the repeated patterns of photovoltaic string numbers and different specifications, it is easy to cause false detection by traditional template matching or model training methods. In order to solve this problem, this paper proposes a photovoltaic panel string detection method based on prior knowledge and feature learning. First, the infrared inspection image is segmented for the first time by using the difference in radiation characteristics between the photovoltaic string and the environmental background. Subsequently, according to the local features of the border around the PV string template image, feature matching is performed in the segmented foreground area, and then determine the exact position of the string through the closure and integrity of the matching area. Experiments show that this method has high detection accuracy and has good adaptability to complex and diverse string specifications. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Inspection

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An improved image segmentation algorithm based on MRF and Sobel operator 12

An improved image segmentation algorithm based on MRF and So...

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SPIE 12th International Symposium on Multispectral Image Processing and pattern recognition, MIPPR 2023

作者： Gao, Yao Tian, keyun Zhu, Cheng Hubei Key Laboratory of Optical Information and Pattern Recognition China Hubei Engineering Research Center of Video Image and HD Projection China School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan430205 China

ISBN: (数字)9781510674943

ISBN: (纸本)9781510674936

In response to the issues of over-segmentation, excessive noise, and suboptimal segmentation results commonly encountered in existing image segmentation algorithms based on Markov Random Fields (MRF), this paper proposes an enhanced image segmentation algorithm that integrates MRF with the Sobel operator. The algorithm begins by performing an initial segmentation of the image using a Markov Random Field (MRF)-based method. Subsequently, an enhanced Sobel operator is employed to eliminate noise points and extract fine edge details from the image. Finally, the segmentation result is refined through pixel-wise operations with the edge detection result, resulting in the ultimate segmentation output. The evaluation of segmentation performance is conducted using the Dice coefficient and Mean Hausdorff Distance as assessment metrics. Through experimental analysis, the method in this paper can improve the segmentation effect of the traditional MRF segmentation algorithm, and has better performance and higher adaptivity. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Image segmentation

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Defect detection of photovoltaic panel based on morphological segmentation 12

Defect detection of photovoltaic panel based on morphologica...

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SPIE 12th International Symposium on Multispectral Image Processing and pattern recognition, MIPPR 2023

作者： Cheng, Bolin Li, Bolin Ye, Liang Hubei Key Laboratory of Optical Information and Pattern Recognition China Hubei Engineering Research Center of Video Image and HD Projection China School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan430205 China

ISBN: (数字)9781510674943

ISBN: (纸本)9781510674936

The automatic inspection of photovoltaic panels based on infrared images is one of the important tasks in the daily maintenance of photovoltaic panels in photovoltaic power plants. In this paper, a defect detection method of infrared thermal image photovoltaic panel based on morphological segmentation is proposed. First of all, according to the infrared characteristics of the photovoltaic plant station and the morphological characteristics of the photovoltaic panel, the accurate region of each photovoltaic panel is determined in the inspection image. Then, statistical method is used for feature analysis to determine whether there are defects in photovoltaic panels, and then the defective photovoltaic panels are segmented and different defects are classified according to morphological characteristics, and finally the defect detection and classification of photovoltaic panels are realized. Through the experiment in the actual inspection image of photovoltaic plant station, it is verified that the proposed method has a high accuracy of defect detection and recognition. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Morphology

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Accurate extraction of line-structured optical stripe centerlines under low exposure 12

Accurate extraction of line-structured optical stripe center...

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SPIE 12th International Symposium on Multispectral Image Processing and pattern recognition, MIPPR 2023

作者： Zhu, Cheng Tian, keyun Gao, Yao Ding, Zhiqiang Hubei Key Laboratory of Optical Information and Pattern Recognition China Hubei Engineering Research Center of Video Image and HD Projection China School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan430205 China

ISBN: (数字)9781510674967

ISBN: (纸本)9781510674950

The line-structure light bar images acquired in industrial metal parts inspection may suffer from inaccurate extraction of the centerline of the line structure light bar due to the interference of ambient lighting and strong diffuse reflection and weak reflection of the part surface material. For this reason, this study proposes a method based on G-HL (Gauss-Hyper-Laplace Distribution) curve fitting to improve the center extraction accuracy of the line structure light bar in complex environments. First, the method uses Gaussian filtering to denoise the line-structured light image. Then, the laser line target pixel region is localized by finding the upper and lower boundaries of the line-structured light bar using the neighborhood gradient for each column of the line-structured light image, and the width of the line-structured light bar is calculated by the difference of the boundary coordinates, and the fitting interval is determined. Finally, within the fitting interval, the G-HL curve is used to fit the gray scale of the line-structured light cross-section to obtain the G-HL parameter, and the point of the maximum value of the G-HL curve is taken to be the coordinates of the center of the line-structured light. Experiments prove that the proposed method can accurately extract the center of the line structure light in low exposure. Compared with the methods such as the grayscale center of gravity method and the extreme value method, the proposed method has high accuracy and robustness. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Curve fitting

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Laser-induced core-polarization effects in high-order harmonic generation from solids

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Physical Review A 2024年第2期110卷 023104-023104页

作者： Wanzhu He Ning Sun Xiaosong Zhu Liang Li Pengfei Lan Peixiang Lu Wuhan National Laboratory for Optoelectronics and School of Physics Hubei Optical Fundamental Research Center Wuhan 430074 China Hubei Key Laboratory of Optical Information and Pattern Recognition

Under intense laser fields, atoms undergo core polarization, i.e., redistribution of the electron density around the nucleus. We systematically investigate the effect of core polarization on high-order harmonic generation (HHG) from solids using time-dependent density-functional theory in a laser-driven linear chain of atoms. It is shown that the presence of core polarization induces substantial variations in HHG compared with the results with a frozen core. Our study further provides insight into these phenomena by combining an approach that distinguishes the effects of core polarization from different shells and compares the contributions of inner and outer shells. Ultimately, we propose and demonstrate a two-color pump-probe scheme to effectively control the core-polarization effects, specifically by activating inner-shell electrons. This work highlights the significance of multielectron effects for solids and demonstrates the feasibility of manipulating the physical properties of materials through core polarization.

关键词： Atomic & molecular processes in external fields High-order harmonic generation Light-matter interaction Strong electromagnetic field effects 1-dimensional systems Density functional theory

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