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A Practical Approach for Missing Wireless Sensor Networks Data Recovery

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China Communications 2024年第5期21卷 202-217页

作者： Song Xiaoxiang Guo Yan Li ning Ren Bing The College of Communications Engineering Army Engineering University of PLANanjing 210007China The 63891 Unit of PLA Luoyang 471000China

In wireless sensor networks(WSNs),the performance of related applications is highly dependent on the quality of data ***,missing data is almost inevitable in the process of data acquisition and *** methods often rely on prior information such as low-rank characteristics or spatiotemporal correlation when recovering missing WSNs ***,in realistic application scenarios,it is very difficult to obtain these prior information from incomplete data ***,we aim to recover the missing WSNs data effectively while getting rid of the perplexity of prior *** designing the corresponding measurement matrix that can capture the position of missing data and sparse representation matrix,a compressive sensing(CS)based missing data recovery model is ***,we design a comparison standard to select the best sparse representation basis and introduce average cross-correlation to examine the rationality of the established ***,an improved fast matching pursuit algorithm is proposed to solve the *** results show that the proposed method can effectively recover the missing WSNs data.

关键词： average cross correlation matching pursuit missing data wireless sensor networks

Editable semiconductor photo-electrodes for sustainable ammonia synthesis

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Nano Research 2024年第4期17卷 3107-3112页

作者： ning Lan Kun Du Erling Zhao Wei Zhao Tao Ling Key Laboratory for Advanced Ceramics and Machining Technology of Ministry of Education Institute of New-EnergySchool of Materials Science and EngineeringTianjin UniversityTianjin 300072China School of Materials Science and Engineering Tianjin Chengjian UniversityTianjin 300384China

Powered by an inexhaustible supply of solar energy,photoelectrochemical(PEC)nitrogen reduction reaction(NRR)provides an ideal solution for the synthesis of green ammonia(NH_(3)).Although great efforts have been made in the past decades,there are still significant challenges in increasing the NH_(3) yields of the PEC-NRR *** addition to the issues of low activity and selectivity similar to electrochemical NRR,the progress of PEC-NRR is also impeded by the limited increase in NH_(3) yields as the electrode is ***,we propose an editable electrode design strategy that parallels unit photo-electrodes to achieve a linear increase in NH_(3) yields with electrode active *** demonstrate that the editable electrode design strategy minimizes the electrode charge transfer resistance,allowing more photo-generated carriers to reach the electrode surface and promote the catalytic *** believe that this editable electrode design strategy provides an avenue to achieve sustainable PEC NH_(3) production.

关键词： editable electrode photoelectrochemical nitrogen reduction reaction parallel electrode ZnSe

Modeling load distribution for rural photovoltaic grid areas using image recognition

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Global Energy Interconnection 2024年第3期7卷 270-283页

作者： ning Zhou Bowen Shang Jinshuai Zhang Mingming Xu State Grid Henan Electric Power Research Institutte Zhengzhou 450052P.R.China

Expanding photovoltaic(PV)resources in rural-grid areas is an essential means to augment the share of solar energy in the energy landscape,aligning with the“carbon peaking and carbon neutrality”***,rural power grids often lack digitalization;thus,the load distribution within these areas is not fully *** hinders the calculation of the available PV capacity and deduction of node *** study proposes a load-distribution modeling approach based on remote-sensing image recognition in pursuit of a scientific framework for developing distributed PV resources in rural grid ***,houses in remote-sensing images are accurately recognized using deep-learning techniques based on the YOLOv5 *** distribution of the houses is then used to estimate the load distribution in the grid ***,equally spaced and clustered distribution models are used to adaptively determine the location of the nodes and load power in the distribution ***,by calculating the connectivity matrix of the nodes,a minimum spanning tree is extracted,the topology of the network is constructed,and the node parameters of the load-distribution model are *** proposed scheme is implemented in a software package and its efficacy is demonstrated by analyzing typical remote-sensing images of rural grid *** results underscore the ability of the proposed approach to effectively discern the distribution-line structure and compute the node parameters,thereby offering vital support for determining PV access capability.

关键词： Deep learning Remote sensing image recognition Photovoltaic development Load distribution modeling Power flow calculation

Machine Learning-Based Research on Tensile Strength of SiC-Reinforced Magnesium Matrix Composites via Stir Casting

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Acta Metallurgica Sinica(English Letters) 2024年第3期37卷 453-466页

作者： Zhihong Zhu Wenhang ning Xuanyang Niu Yuhong Zhao Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology BeijingBeijing 100083China School of Materials Science and Engineering Collaborative Innovation Center of Ministry of Education and Shanxi Province for High-Performance Al/Mg Alloy MaterialsNorth University of ChinaTaiyuan 030051China Institute of Materials Intelligent Technology Liaoning Academy of MaterialsShenyang 110004China

SiC is the most common reinforcement in magnesium matrix composites,and the tensile strength of SiC-reinforced magnesium matrix composites is closely related to the distribution of *** a uniform distribution of SiC requires fine control over the parameters of SiC and the processing and preparation ***,due to the numerous adjustable parameters,using traditional experimental methods requires a considerable amount of experimentation to obtain a uniformly distributed composite ***,this study adopts a machine learning approach to explore the tensile strength of SiC-reinforced magnesium matrix composites in the mechanical stirring casting *** analyzing the influence of SiC parameters and processing parameters on composite material performance,we have established an effective predictive ***,six different machine learning regression models have been developed to predict the tensile strength of SiC-reinforced magnesium matrix *** validation and comparison,our models demonstrate good accuracy and reliability in predicting the tensile strength of the composite *** research findings indicate that hot extrusion treatment,SiC content,and stirring time have a significant impact on the tensile strength.

关键词： Machine learning Stirring casting Magnesium matrix composite Tensile strength

Synthesis of covalent organic framework materials and their application in the field of sensing

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Nano Research 2024年第1期17卷 162-195页

作者： Weiyu Zhang Shiwei Liu Qihua Sun ning Tian Zhaofeng Wu Xinjiang Key Laboratory of Solid-State Physics and Devices Urumqi 830046China School of Physics Science and Technology Xinjiang UniversityUrumqi 830046China

Covalent organic frameworks(COFs)are an emerging type of porous crystalline polymers formed by combining strong covalent bonds with organic building *** to their large surface area,high intrinsic pore space,good crystallization properties,high stability,and designability of the resultant units,COFs are widely studied and used in the fields of gas adsorption,drug transport,energy storage,photoelectric catalysis,electrochemistry,and *** recent years,the rapid development of the Internet of Things and people’s yearning for a better life have put forward higher and more requirements for sensors,which are the core components of the Internet of ***,this paper reviews the recent progress of COFs in synthesis methods and sensing applications,especially in the last five *** paper first introduces structure,properties,and synthesis methods of COFs and discusses advantages and disadvantages of different synthesis ***,the research progress of COFs in different sensing fields,such as metal ion sensors,gas sensors,biomedical sensors,humidity sensors,and pH sensors,is introduced *** and prospects are also presented in order to provide a reference for researchers concerned with COFs and sensors.

关键词： covalent organic framework materials structural design and synthesis sensing application gas sensors

An Interpretable Light Attention-Convolution-Gate Recurrent Unit Architecture for the Highly Accurate Modeling of Actual Chemical Dynamic Processes

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Engineering 2024年第8期39卷 104-116页

作者： Yue Li ning Li Jingzheng Ren Weifeng Shen School of Chemistry and Chemical Engineering Chongqing UniversityChongqing 400044China Chongqing Key Laboratory of Catalysis and New Environmental Materials School of Environment and ResourcesChongqing Technology and Business UniversityChongqing 400067China Department of Industrial and Systems Engineering The Hong Kong Polytechnic UniversityHong Kong 999077China

To equip data-driven dynamic chemical process models with strong interpretability,we develop a light attention–convolution–gate recurrent unit(LACG)architecture with three sub-modules—a basic module,a brand-new light attention module,and a residue module—that are specially designed to learn the general dynamic behavior,transient disturbances,and other input factors of chemical processes,*** with a hyperparameter optimization framework,Optuna,the effectiveness of the proposed LACG is tested by distributed control system data-driven modeling experiments on the discharge flowrate of an actual deethanization *** LACG model provides significant advantages in prediction accuracy and model generalization compared with other models,including the feedforward neural network,convolution neural network,long short-term memory(LSTM),and ***,compared with the simulation results of a deethanization model built using Aspen Plus Dynamics V12.1,the LACG parameters are demonstrated to be interpretable,and more details on the variable interactions can be observed from the model parameters in comparison with the traditional interpretable model *** contribution enriches interpretable machine learning knowledge and provides a reliable method with high accuracy for actual chemical process modeling,paving a route to intelligent manufacturing.

关键词： Interpretable machine learning Light attention-convolution-gate recurrent unit architecture Process knowledge discovery Data-driven process model Intelligent manufacturing

Constructing Built-In Electric Fields with Semiconductor Junctions and Schottky Junctions Based on Mo-MXene/Mo-Metal Sulfides for Electromagnetic Response

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Nano-Micro Letters 2024年第10期16卷 453-473页

作者： Xiaojun Zeng Xiao Jiang Ya ning Yanfeng Gao Renchao Che School of Materials Science and Engineering Jingdezhen Ceramic UniversityJingdezhen 333403People's Republic of China School of Materials Science and Engineering Shanghai UniversityShanghai 200444People's Republic of China Laboratory of Advanced Materials Shanghai Key Lab of Molecular Catalysis and Innovative MaterialsAcademy for Engineering and TechnologyFudan UniversityShanghai 200438People's Republic of China Zhejiang Laboratory Hangzhou 311100People's Republic of China

The exploration of novel multivariate heterostructures has emerged as a pivotal strategy for developing high-performance electromagnetic wave(EMW)absorption ***,the loss mechanism in traditional heterostructures is relatively simple,guided by empirical observations,and is not *** this work,we presented a novel semiconductor-semiconductor-metal heterostructure sys-tem,Mo-MXene/Mo-metal sulfides(metal=Sn,Fe,Mn,Co,Ni,Zn,and Cu),including semiconductor junctions and Mott-Schottky *** skillfully combining these distinct functional components(Mo-MXene,MoS_(2),metal sulfides),we can engineer a multiple heterogeneous interface with superior absorption capabilities,broad effective absorption bandwidths,and ultrathin matching *** successful establishment of semiconductor-semiconductor-metal heterostructures gives rise to a built-in electric field that intensifies electron transfer,as confirmed by density functional theory,which collaborates with multiple dielectric polarization mechanisms to substantially amplify EMW *** detailed a successful synthesis of a series of Mo-MXene/Mo-metal sulfides featuring both semiconductor-semiconductor and semiconductor-metal *** achievements were most pronounced in Mo-MXene/Mo-Sn sulfide,which achieved remarkable reflection loss values of-70.6 dB at a matching thickness of only 1.885 *** cross-section calculations indicate that these MXene/Mo-metal sulfides have tremendous potential in practical military stealth *** work marks a departure from conventional component design limitations and presents a novel pathway for the creation of advanced MXene-based composites with potent EMW absorption capabilities.

关键词： Semiconductor-semiconductor-metal heterostructure Semiconductor junctions Mott-Schottky junctions Built-in electric field Electromagnetic wave absorption

1.42-fold enhancement of formate selectivity by linker conversion on the Zn-based metal organic framework catalyst

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Journal of Energy Chemistry 2024年第3期90卷 183-190,I0006页

作者： Yayu Guan Yuyu Liu Fanghua ning Jin Yi Jiujun Zhang Institute for Sustainable Energy College of SciencesShanghai UniversityShanghai 200444China

Electro-reduction of carbon dioxide(ERCO_(2)) is considered an effective method to alleviate the greenhouse effect and produce value-added *** the dominant selectivity of Zn-based catalysts for formate remains a *** this article,the ZnIn-E_(12) catalyst is successfully prepared by solvent assisted ligand exchange(SALE) method to convert organic ligands,achieving a Faradaic efficiency of 72.28% for formate at-1.26 V ***(V_(RHE)),which is 1.42 times higher than the original *** shows that the successful conversion of organic ligands can transform the catalyst from the original large size polyhedron to cross-linked network of particles with a diameter of about 30 *** increased specific surface area can expose more active sites and facilitate the electrocatalytic conversion of CO_(2) to *** work is expected to provide inspiration for the regulation of formate selectivity and catalyst size in Zn-based catalysts.

关键词： Electrocatalyst Carbon dioxide Formate Linker conversion

Effect of fore/aft-loaded rotor on compressor stability under inlet circumferential distortion

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Chinese Journal of Aeronautics 2024年第5期37卷 199-213页

作者： Dakun SUN Benhao GU Fangfei ning Dengke XU Xiaofeng SUN School of Energy and Power Engineering Beihang UniversityBeijing 102206China Research Institute of Aero-engine Beihang UniversityBeijing 102206China

A modified small perturbation stability prediction model for axial compressors with circumferential inlet distortions is established and applied to investigate the effect of fore/aft-loaded rotor on compressor stability under circumferentially distorted inlet *** inlet total pressure distribution downstream of the distortion screen is measured in experiments and employed for simulations which are implemented via time-space spectral *** stall inception prediction results via the stability model indicate that the compressor with aft-loaded rotor not only performs better in terms of stability under uniform inlet,but also maintains a larger stability margin under circumferentially distorted *** experiments for compressors with fore-loaded and aft-loaded rotor are respectively carried *** results validate the reliability of numerical simulations and the predicted conclusion that the aft-loaded rotor is beneficial for compressor ***,the ability of the developed theoretical model for compressor stability prediction under circumferential distortions is *** addition,dynamic pressure signals at rotor tip measured in experiments illustrate that the circumferential distortion has little effect on the compressor stall pattern.

关键词： Axial compressor stability Inlet distortion Blade loading Small perturbation Time-space spectral method