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Core-shell nanoparticle enhanced Raman spectroscopy in situ probing the composition and evolution of interfacial species on PtCo surfaces

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Nano Research 2024年第6期17卷 4687-4692页

作者： Jing Liu Han-Liang Zhong Xiangyu Li Mu-Fei Yue Wei-Min Yang Xueqiu You Jing-Hua Tian Yao-Hui Wang Jian-Feng Li Fujian Provincial key laboratory of Oceanic Information perception and intelligent processing School of Ocean Information EngineeringJimei UniversityXiamen 361021China College of Chemistry Fuzhou UniversityFuzhou 350108China State key laboratory of Physical Chemistry of Solid Surfaces MOE Key Laboratory of Spectrochemical Analysis and InstrumentationiChEMCollege of Chemistry and Chemical EngineeringCollege of MaterialsCollege of EnergyXiamen UniversityXiamen 361005China Innovation laboratory for Sciences and Technologies of Energy Materials of Fujian Province(IKKEM) Xiamen 361005China Shenzhen Research Institute of Xiamen University Shenzhen 518000China

The composition and evolution of interfacial species play a key role during electrocatalytic *** the structural evolution and intermediate during catalytic process by in situ characterization can shed new light on the electrocatalytic reaction mechanism and develop highly efficient ***,directly probing the interfacial species is extremely difficult for most spectroscopic techniques due to complicated interfacial environment and ultra-low surface ***,electrochemical core-shell nanoparticle enhanced Raman spectroscopy is utilized to probe the composition and evolution processes of interfacial species on Au@Pt,Au@Co,and Au@PtCo core-shell nanoparticle *** spectral evidences of interfacial intermediates including hydroxide radical(OH*),superoxide ion(O_(2)^(−)),as well as metal oxide species are directly captured by in situ Raman spectroscopy,which are further confirmed by the both isotopic experiment and density functional theory *** results provide a mechanistic guideline for the rational design of highly efficient electrocatalysts.

关键词： in situ Raman core-shell nanoparticle PtCo interfacial species composition and evolution

Exploring the Cation Regulation Mechanism for Interfacial Water Involved in the Hydrogen Evolution Reaction by In Situ Raman Spectroscopy

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Nano-Micro Letters 2024年第3期16卷 303-312页

作者： Xueqiu You Dongao Zhang Xia‑Guang Zhang Xiangyu Li Jing‑Hua Tian Yao‑Hui Wang Jian‑Feng Li School of Ocean Information Engineering Fujian Provincial Key Laboratory of Oceanic Information Perception and Intelligent ProcessingJimei UniversityXiamen 361021People’s Republic of China State key laboratory of Physical Chemistry of Solid Surfaces MOE Key Laboratory of Spectrochemical Analysis and InstrumentationiChEMCollege of Chemistry and Chemical EngineeringCollege of MaterialsCollege of EnergyXiamen UniversityXiamen 361005People’s Republic of China key laboratory of Green Chemical Media and Reactions Ministry of EducationCollaborative Innovation Center of Henan Province for Green Manufacturing of Fine ChemicalsCollege of Chemistry and Chemical EngineeringHenan Normal UniversityXinxiang 453007People’s Republic of China Innovation laboratory for Sciences and Technologies of Energy Materials of Fujian Province(IKKEM) Xiamen 361005People’s Republic of China

Interfacial water molecules are the most important participants in the hydrogen evolution reaction(HER).Hence,understanding the behavior and role that interfacial water plays will ultimately reveal the HER ***,investigating interfacial water is extremely challenging owing to the interference caused by bulk water molecules and complexity of the interfacial ***,the behaviors of interfacial water in different cationic electrolytes on Pd surfaces were investigated by the electrochemistry,in situ core-shell nanostructure enhanced Raman spectroscopy and theoretical simulation *** spectral evidence reveals a red shift in the frequency and a decrease in the intensity of interfacial water as the potential is shifted in the positively *** comparing the different cation electrolyte systems at a given potential,the frequency of the interfacial water peak increases in the specified order:Li+

关键词： In situ Raman Interfacial water Hydrogen evolution reaction Cations

Brain-inspired artificial intelligence research: A review

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Science China(Technological Sciences) 2024年第8期67卷 2282-2296页

作者： WANG GuoYin BAO HuaNan LIU Qun ZHOU TianGang WU Si HUANG TieJun YU ZhaoFei LU CeWu GONG YiHong ZHANG ZhaoXiang HE Sheng Chongqing key laboratory of Computational Intelligence Chongqing University of Posts and TelecommunicationsChongqing 400065China key laboratory of Cyberspace Big Data intelligent Security Chongqing University of Posts and TelecommunicationsChongqing 400065China College of Computer and Information Science Chongqing Normal UniversityChongqing 401331China State key laboratory of Brain and Cognitive Science Institute of BiophysicsChinese Academy of SciencesBeijing 100101China School of Psychological and Cognitive Sciences Peking UniversityBeijing 100871China State key laboratory of Multimedia Information processing School of Computer SciencePeking UniversityBeijing 100871China Department of Computer Science School of ElectronicsInformation and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Faculty of Electronic and Information Engineering Xi’an Jiaotong UniversityXi’an 710049China The Center for Research on intelligent perception and Computing Institute of AutomationChinese Academy of SciencesBeijing 100190China Institute of Biophysics Chinese Academy of SciencesBeijing 100101China

Artificial intelligence(AI) systems surpass certain human intelligence abilities in a statistical sense as a whole, but are not yet the true realization of these human intelligence abilities and behaviors. There are differences, and even contradictions, between the cognition and behavior of AI systems and humans. With the goal of achieving general AI, this study contains a review of the role of cognitive science in inspiring the development of the three mainstream academic branches of AI based on the three-layer framework proposed by David Marr, and the limitations of the current development of AI are explored and analyzed. The differences and inconsistencies between the cognition mechanisms of the human brain and the computation mechanisms of AI systems are analyzed. They are found to be the cause of the differences and contradictions between the cognition and behavior of AI systems and humans. Additionally, eight important research directions and their scientific issues that need to focus on braininspired AI research are proposed: highly imitated bionic information processing, a large-scale deep learning model that balances structure and function, multi-granularity joint problem solving bidirectionally driven by data and knowledge, AI models that simulate specific brain structures, a collaborative processing mechanism with the physical separation of perceptual processing and interpretive analysis, embodied intelligence that integrates the brain cognitive mechanism and AI computation mechanisms,intelligence simulation from individual intelligence to group intelligence(social intelligence), and AI-assisted brain cognitive intelligence.

关键词： artificial intelligence cognitive science brain science intelligence science large language model

MCIF-Transformer Mask RCNN:Multi-Branch Cross-Scale Interactive Feature Fusion Transformer Model for PET/CT Lung Tumor Instance Segmentation

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Computers, Materials & Continua 2024年第6期79卷 4371-4393页

作者： Huiling Lu Tao Zhou School of Medical Information&Engineering Ningxia Medical UniversityYinchuan750004China School of Computer Science and Engineering North Minzu UniversityYinchuan750021China key laboratory of Image and Graphics intelligent processing of State Ethnic Affairs Commission NorthMinzu UniversityYinchuan750021China

The precise detection and segmentation of tumor lesions are very important for lung cancer computer-aided ***,in PET/CT(Positron Emission Tomography/Computed Tomography)lung images,the lesion shapes are complex,the edges are blurred,and the sample numbers are *** solve these problems,this paper proposes a Multi-branch Cross-scale Interactive Feature fusion Transformer model(MCIF-Transformer Mask RCNN)for PET/CT lung tumor instance segmentation,The main innovative works of this paper are as follows:Firstly,the ResNet-Transformer backbone network is used to extract global feature and local feature in lung *** pixel dependence relationship is established in local and non-local fields to improve the model perception ***,the Cross-scale Interactive Feature Enhancement auxiliary network is designed to provide the shallow features to the deep features,and the cross-scale interactive feature enhancement module(CIFEM)is used to enhance the attention ability of the fine-grained ***,the Cross-scale Interactive Feature fusion FPN network(CIF-FPN)is constructed to realize bidirectional interactive fusion between deep features and shallow features,and the low-level features are enhanced in deep semantic ***,4 ablation experiments,3 comparison experiments of detection,3 comparison experiments of segmentation and 6 comparison experiments with two-stage and single-stage instance segmentation networks are done on PET/CT lung medical image *** results showed that APdet,APseg,ARdet and ARseg indexes are improved by 5.5%,5.15%,3.11%and 6.79%compared with Mask RCNN(resnet50).Based on the above research,the precise detection and segmentation of the lesion region are realized in this *** method has positive significance for the detection of lung tumors.

关键词： PET/CT images instance segmentation mask RCNN interactive fusion transformer

MSD-Net: Pneumonia Classification Model Based on Multi-Scale Directional Feature Enhancement

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Computers, Materials & Continua 2024年第6期79卷 4863-4882页

作者： Tao Zhou Yujie Guo Caiyue Peng Yuxia Niu Yunfeng Pan Huiling Lu School of Computer Science and Engineering North Minzu UniversityYinchuan750021China School of Medical Information&Engineering Ningxia Medical UniversityYinchuan750004China key laboratory of Image and Graphics intelligent processing of State Ethnic Affairs Commission North Minzu UniversityYinchuan750021China

Computer-aided diagnosis of pneumonia based on deep learning is a research ***,there are some problems that the features of different sizes and different directions are not sufficient when extracting the features in lung X-ray images.A pneumonia classification model based on multi-scale directional feature enhancement MSD-Net is proposed in this *** main innovations are as follows:Firstly,the Multi-scale Residual Feature Extraction Module(MRFEM)is designed to effectively extract multi-scale *** MRFEM uses dilated convolutions with different expansion rates to increase the receptive field and extract multi-scale features ***,the Multi-scale Directional Feature perception Module(MDFPM)is designed,which uses a three-branch structure of different sizes convolution to transmit direction feature layer by layer,and focuses on the target region to enhance the feature ***,the Axial Compression Former Module(ACFM)is designed to perform global calculations to enhance the perception ability of global features in different *** verify the effectiveness of the MSD-Net,comparative experiments and ablation experiments are carried *** the COVID-19 RADIOGRAPHY DATABASE,the Accuracy,Recall,Precision,F1 Score,and Specificity of MSD-Net are 97.76%,95.57%,95.52%,95.52%,and 98.51%,*** the chest X-ray dataset,the Accuracy,Recall,Precision,F1 Score and Specificity of MSD-Net are 97.78%,95.22%,96.49%,95.58%,and 98.11%,*** model improves the accuracy of lung image recognition effectively and provides an important clinical reference to pneumonia Computer-Aided Diagnosis.

关键词： Pneumonia X-ray image ResNet multi-scale feature direction feature transformer

Analog spatiotemporal feature extraction for cognitive radio-frequency sensing with integrated photonics

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Light(Science & Applications) 2024年第3期13卷 478-487页

作者： Shaofu Xu Binshuo Liu Sicheng Yi Jing Wang Weiwen Zou State key laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center(imLic)Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghaiChina

Analog feature extraction(AFE)is an appealing strategy for low-latency and efficient cognitive sensing systems since key features are much sparser than the Nyquist-sampled ***,applying AFE to broadband radio-frequency(RF)scenarios is challenging due to the bandwidth and programmability bottlenecks of analog electronic ***,we introduce a photonics-based scheme that extracts spatiotemporal features from broadband RF signals in the analog *** feature extractor structure inspired by convolutional neural networks is implemented on integrated photonic circuits to process RF signals from multiple antennas,extracting valid features from both temporal and spatial *** of the tunability of the photonic devices,the photonic spatiotemporal feature extractor is trainable,which enhances the validity of the extracted ***,a digital-analog-hybrid transfer learning method is proposed for the effective and low-cost training of the photonic feature *** validate our scheme,we demonstrate a radar target recognition task with a 4-GHz instantaneous *** results indicate that the photonic analog feature extractor tackles broadband RF signals and reduces the sampling rate of analog-to-digital converters to 1/4 of the Nyquist sampling while maintaining a high target recognition accuracy of 97.5%.Our scheme offers a promising path for exploiting the AFE strategy in the realm of cognitive RF sensing,with the potential to contribute to the efficient signal processing involved in applications such as autonomous driving,robotics,and smart factories.

关键词： scheme driving smart

Artificial Intelligence Meets Flexible Sensors:Emerging Smart Flexible Sensing Systems Driven by Machine Learning and Artificial Synapses

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Nano-Micro Letters 2024年第1期16卷 235-273页

作者： Tianming Sun Bin Feng Jinpeng Huo Yu Xiao Wengan Wang Jin Peng Zehua Li Chengjie Du Wenxian Wang Guisheng Zou Lei Liu Department of Mechanical Engineering State Key Laboratory of Tribology in Advanced EquipmentKey Laboratory for Advanced Manufacturing by Materials Processing TechnologyMinistry of Education of PR ChinaTsinghua UniversityBeijing 100084People’s Republic of China College of Materials Science and Engineering Shanxi ProvinceTaiyuan University of TechnologyTaiyuan 030024People’s Republic of China

The recent wave of the artificial intelligence(AI)revolution has aroused unprecedented interest in the intelligentialize of human *** an essential component that bridges the physical world and digital signals,flexible sensors are evolving from a single sensing element to a smarter system,which is capable of highly efficient acquisition,analysis,and even perception of vast,multifaceted *** challenging from a manual perspective,the development of intelligent flexible sensing has been remarkably facilitated owing to the rapid advances of brain-inspired AI innovations from both the algorithm(machine learning)and the framework(artificial synapses)*** review presents the recent progress of the emerging AI-driven,intelligent flexible sensing *** basic concept of machine learning and artificial synapses are *** new enabling features induced by the fusion of AI and flexible sensing are comprehensively reviewed,which significantly advances the applications such as flexible sensory systems,soft/humanoid robotics,and human activity *** two of the most profound innovations in the twenty-first century,the deep incorporation of flexible sensing and AI technology holds tremendous potential for creating a smarter world for human beings.

关键词： Flexible electronics Wearable electronics Neuromorphic Memristor Deep learning

spatiotemporal evolution laws of sector-shaped dielectric-barrier-discharge plasma actuator

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Plasma Science and Technology 2024年第10期26卷 108-115页

作者： Borui ZHENG Jianbo ZHANG Shaojie QI Jianghua XU Yiche LI Yuanzhong JIN Dongliang BIAN School of Automation and Information Engineering Xi’an University of TechnologyXi’an 710048People’s Republic of China Shaanxi key laboratory of Complex System Control and intelligent Information processing Xi’an 710048People’s Republic of China School of Mechanical and Precision Instrument Engineering Xi’an University of TechnologyXi’an 710048People’s Republic of China Science and Technology on Plasma Dynamics laboratory Air Force Engineering UniversityXi’an 710038People’s Republic of China

Dielectric barrier discharge(DBD)plasma actuators are widely used in active flow control due to their simple design and rapid ***,they need more effectiveness and discharge *** overcome these limitations,a sector-shaped dielectric barrier discharge(SS-DBD)plasma actuator with an adjustable jet angle was developed to enhance flow control *** flow field dynamics induced by the SS-DBD plasma actuator were quantitatively analyzed using particle image velocimetry(PIV).Experimental investigations showed that precise adjustments to the actuation voltage can modulate the maximum velocity of the induced ***,a quasi-linear relationship between the sector-shaped angles of the SS-DBD and the deflected jet angles was established,indicating that changes in the sector-shaped angles directly influence the direction of the deflected *** correlation enables precise control over jet angles,significantly enhancing flow control by adjusting the SS-DBD-PA's sector-shaped angle.

关键词： plasma flow control plasma actuator particle image velocimetry

Intuitive Human-Robot-Environment Interaction With EMG Signals:A Review

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1075-1091页

作者： Dezhen Xiong Daohui Zhang Yaqi Chu Yiwen Zhao Xingang Zhao State key laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016 Institutes for Robotics and intelligent Manufacturing Chinese Academy of SciencesShenyang 110169 University of Chinese Academy of Sciences Beijing 100049China

A long history has passed since electromyography(EMG)signals have been explored in human-centered robots for intuitive ***,it still has a gap between scientific research and real-life *** studies mainly focused on EMG decoding algorithms,leaving a dynamic relationship between the human,robot,and uncertain environment in real-life scenarios seldomly *** fill this gap,this paper presents a comprehensive review of EMG-based techniques in human-robot-environment interaction(HREI)*** general processing framework is summarized,and three interaction paradigms,including direct control,sensory feedback,and partial autonomous control,are ***-based intention decoding is treated as a module of the proposed *** key issues involving precision,stability,user attention,compliance,and environmental awareness in this field are *** important directions,including EMG decomposition,robust algorithms,HREI dataset,proprioception feedback,reinforcement learning,and embodied intelligence,are proposed to pave the way for future *** the best of what we know,this is the first time that a review of EMG-based methods in the HREI system is *** provides a novel and broader perspective to improve the practicability of current myoelectric interaction systems,in which factors in human-robot interaction,robot-environment interaction,and state perception by human sensations are considered,which has never been done by previous studies.

关键词： robot summarized Robot