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Designing hard wear-resistant conductors by introducing high-plasma-energy heterogeneous metals into transition metal nitrides

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Journal of Materials science & technology 2023年第26期157卷 213-219页

作者： Yuankai Li Chaoquan Hu Yao Wu Zhenan Qiao Yifan Cheng Zhiqing Gu Gang Gao Weitao Zheng State Key Laboratory of Superhard Materials Key Laboratory of Automobile Materials of Ministry of EducationSchool of Materials Science and EngineeringJilin Provincial International Cooperation Key Laboratory of High-Efficiency Clean Energy MaterialsJilin UniversityChangchun 130012China State Key Laboratory of Inorganic Synthesis and Preparative Chemistry College of ChemistryJilin UniversityChangchun 130012China SINOPEC Star Co.Ltd. Beijing 100083China Key Laboratory of Medical Electronics and Digital Health of Zhejiang Province College of Information Science and EngineeringJiaxing UniversityJiaxing 314001China National Key Laboratory of Science and Technology on Advanced Composites in Special Environments Harbin Institute of TechnologyHarbin 150080China State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130025China

*** Hard and wear-resistant conductors(HWCs)refer to functional films with simultaneously high hardness,high wear resistance,and good electrical *** have important applica-tions such as next-generation sliding electrical contacts,high-end conductive probe-tip,and oval hole guides for the precision rolling mill[1-4],which has drawn extensive research ***,it is still challenging to integrate high hardness,super wear resis-tance,and high electrical conductivity in one ***-ally,researchers have mainly alloyed the highly conductive met-als Cu,Au,and Pt to improve their hardness and wear resistance.

关键词： wear high electrical

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Predefined time attitude control for quadrotor UAV with output constraints and input saturation

Predefined time attitude control for quadrotor UAV with outp...

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2024 China Automation Congress, CAC 2024

作者： Li, Shuo Pei, Hailong Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangdong Engineering Technology Research Center of Unmanned Aerial Vehicle Systems College of Automation Science and Enginneering South China University of Technology Guangzhou510640 China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangdong Engineering Technology Research Center of Unmanned Aerial Vehicle Systems School of Automation Science and Enginneering South China University of Technology Guangzhou510640 China

ISBN: (纸本)9798350368604

In this paper, we examine the predefined time flight control of a quadrotor UAV with output constraints and input saturation. The attitude tracking error of UAV is constrained by the tan-type barrier Lyapunov function. The undesirable effects of the saturated input limitations are addressed by introducing an auxiliary system. Then a predefined time tracking control strategy is designed and the stability of the scheme is analyzed. Eventually, the simulation results show the method allows the angular tracking error to converge to the specified range in a predefined time. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Efficient degradation of tetracycline by singlet oxygen-dominated peroxymonosulfate activation with magnetic nitrogen-doped porous carbon

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Journal of Environmental sciences 2022年第5期34卷 330-340页

作者： Shaohua Wu Chunping Yang Yan Lin Jay J.Cheng Guangdong Provincial Key Laboratory of Petrochemcial Pollution Processes and Control School of Environmental Science and EngineeringGuangdong University of Petrochemical TechnologyMaomingGuangdong 525000China College of Environmental Science and Engineering Hunan University and Key Laboratory of Environmental Biology and Pollution Control(Hunan University)Ministry of EducationChangshaHunan 410082China Maoming Engineering Research Center for Organic Pollution Control Academy of Environmental and Resource SciencesGuangdong University of Petrochemical TechnologyMaomingGuangdong 525000China Hunan Provincial Environmental Protection Engineering Center for Organic Pollution Control of Urban Water and Wastewater ChangshaHunan 410001China Department of Biological and Agricultural Engineering North Carolina State UniversityRaleighNC 27695USA

Nonradical reaction driven by peroxymonosulfate(PMS)based advanced oxidation pro-cesses has drawn widespread attention in water treatment due to their inherent advantages,but the degradation behavior and mechanism of organic pollutants are still *** this study,the performance,intermediates,mechanism and toxicity of tetracycline(TC)degra-dation were thoroughly examined in the constructed magnetic nitrogen-doped porous car-bon/peroxymonosulfate(Co-N/C-PMS)*** results showed that 85.4%of TC could be removed within 15 min when Co-N/C and PMS was simultaneously added and the degra-dation rate was enhanced by 3.4 and 14.7 folds compared with Co-N/C or PMS alone,***,the performance of Co-N/C was superior to that of most previously reported *** lines of evidence indicated that Co-N/C-PMS system was a singlet oxygen-dominated nonradical reaction,which was less interfered by pH and water compo-nents,and displayed high adaptability to actual water ***,the degrada-tion process was elaborated on the basis of three-dimensional excitation-emission matrix spectra and liquid chromatography-mass *** last,the toxicity of treated TC was greatly reduced by using microalgae Coelastrella *** ecological *** study provides a promising approach based on singlet oxygen-dominated nonradical reaction for eliminating TC in water treatment.

关键词： Tetracycline Peroxymonosulfate Activation Singlet oxygen Toxicity

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Airfoil Aerodynamic Force Prediction Based on Graph Neural Networks

Airfoil Aerodynamic Force Prediction Based on Graph Neural N...

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第43届中国控制会议

作者： Guoqing Wang Junzhe Cao Control Science and Engineering Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Aerodynamic force prediction is an important application of deep learning in the field of fluid *** this paper,a light graph neural network model with residual connections named LRGCN is designed to speed the computational process of the aerodynamic *** with other graph convolutional networks,the LRGCN reduces redundant operations and introduces skip connections,overcomes the limitations of traditional machine learning methods that require geometric airfoil *** using CFD simulation,a dataset of aerodynamic forces for airfoil profiles was generated,where the nodes and edges of the flow field grids are abstracted to build a graph structure for aerodynamic force *** study takes variations of the airfoil shape and pitch angle into consideration,enabling the prediction of lift and drag to be *** the numerical experiments,the LRGCN achieves the result that normalized test set loss is around 10-3 and the R2 is higher than 90%,which exhibits stronger robustness and higher accuracy than three other current convolutional *** the LRGCN runs 60 times faster than the normal CFD method for the same prediction task,which significantly reduces time costs.

关键词： deep learning aerodynamic force prediction unstructured grid graph neural network

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Water‑immersion softening mechanism of coal rock mass based on split Hopkinson pressure bar experiment

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International Journal of Coal science & technology 2022年第4期9卷 122-134页

作者： Zhiyuan Liu Gang Wang Jinzhou Li Huaixing Li Haifeng Zhao Hongwei Shi Jianli Lan School of Petroleum Engineering China University of PetroleumBeijingBeijing 102249China Mine Disaster Prevention and Control-Ministry of State Key Laboratory Breeding Base Shandong University of Science and TechnologyQingdao 266590China College of Safety and Environmental Engineering Shandong University of Science and TechnologyQingdao 266590China

The coal mining process is afected by various water sources such as groundwater and coal seam water *** the dynamic mechanical parameters of water-immersed coal is helpful for coalmine safe *** impact compression tests were performed on coal with diferent moisture contents by using theϕ50 mm Split Hopkinson Pressure Bar(SHPB)experimental system,and the dynamic characteristics and energy loss laws of water-immersed coal with diferent compositions and water contents were *** analysis and discussion,it is found that:(1)When the moisture content of the coal sample is 0%,30%,60%,the stress,strain rate and energy frst increase and then decrease with time.(2)When the moisture content of the coal sample increases from 30%to 60%,the stress“plateau”of the coal sample becomes more obvious,resulting in an increase in the compressive stress stage and a decrease in the expansion stress stage.(3)The increase of moisture content of the coal sample will afect its impact deformation and failure *** the moisture content is 60%,the incident rod end and the transmission rod end of the coal sample will have obvious compression failure,and the middle part of the coal sample will also experience expansion and deformation.(4)The coal composition ratio suitable for the coal immersion softening impact experiment is optimized.

关键词： Coal immersion softening Dynamic compressive response Split Hopkinson pressure bar Softening mechanism model

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A Novel Point Cloud Deep Learning Method for Predicting Variable Airfoil Flow Fields

A Novel Point Cloud Deep Learning Method for Predicting Vari...

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第43届中国控制会议

作者： Xinyao Zhang Junzhe Cao Control Science and Engineering Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Airfoil flow field is of great significance to the design optimization of aircraft *** Neural Networks(CNNs) have been applied in flow field prediction studies,which greatly reduce the cost of computation time in traditional Computational Fluid Dynamics(CFD) ***,such CNN-based approaches normally bring extra errors due to the procedure of interpolating irregular grid data into Cartesian grids,which may lead to underperforming prediction *** this paper,an improved PointNet++ point cloud deep learning method was proposed for the airfoil flow field *** unstructured grid vertices in the CFD domain were treated as point cloud as well as the input of neural network,and only the original information of the data was adopted to avoid *** relationship features were defined and spliced with neighborhood point features,and the features were integrated by simultaneously solving for the maximum,minimum,sum,and average values to extract the local or global features of the system to enhance the performance of deep network for extracting the ***,the proposed network was trained and tested by using 549 sets of flow field data formed by 61 airfoils under 9 angle-of-attack conditions,and further predicted for an additional 32 datasets with different airfoils and *** simulation results show that the method proposed in this study gets lower prediction errors in terms of pressure,Mach number,x-direction velocity,and y-direction velocity than the two other current point cloud deep networks,PointNet and PointNet++.At the same time,the computation speed of this method is about 14 times faster than the traditional CFD method.

关键词： Flow field prediction point cloud PointNet++ neighbourhood relationship

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Maternal obesity exacerbates the responsiveness of offspring BALB/c mice to cow's milk protein-induced food allergy

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Food science and Human Wellness 2023年第3期12卷 920-928页

作者： Jingxin Gao Tiange Li Dong Liang Han Gong Liang Zhao Xueying Mao Key Laboratory of Functional Dairy Ministry of EducationCollege of Food Science and Nutritional EngineeringChina Agricultural UniversityBeijing 100083China Henan Engineering Technology Research Center of Food Processing and Circulation Safety Control College of Food Science and TechnologyHenan Agricultural UniversityZhengzhou 450002China Applied Nutrition I China National Center for Food Safety Risk AssessmentBeijing 100022China

Food allergy has become a significant public health problem affecting a large number of people *** obesity causes inflammation and alters the immune system of offspring,which may exacerbate their food *** aim of this study was to determine whether offspring mice born to obese mothers would have more serve reactions to cow's milk protein-induced food allergy,and further investigate the underlying *** offspring BALB/c mice of mothers with normal and high-fat diets were sensitized withβ-lactoglobulin(BLG),*** obesity increased the serum immunoglobulin E and mouse mast cell protease levels,though did not have significant influence on anaphylactic symptom score,core temperature and diarrhea rate of offspring mice after BLG ***,maternal obesity led to a lower level of occludin mRNA expression in BLG-sensitized *** mice born to obese mothers exhibited increased mRNA expression levels of GATA-3,interleukin(IL)-4 and IL-10 in jejunum after BLG sensitization,indicating maternal obesity intensified Th2-type biased immune *** conclusion,maternal obesity exerted exacerbating effects on the responsiveness of their offspring to cow's milk protein sensitization.

关键词： Cow's milk allergy Maternal obesity Offspring Intestinal barrier Immune response

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High-precision flexible sweat self-collection sensor for mental stress evaluation

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npj Flexible Electronics 2024年第1期8卷 417-426页

作者： Chenhao Wang Zhengyu Wang Wei Wei Zhenjie Zhang Anne Ailina Li Guanghao Huang Xian Li Shuzhi Sam Ge Lianqun Zhou Hui Kong Institute for Future School of AutomationShandong Key Laboratory of Industrial Control TechnologyQingdao UniversityQingdao266071China ETH Zürich Department of Biosystems Science and EngineeringBio Engineering LaboratoryBasel4056Switzerland The University of Sydney 2006 SydneyAustralia Natl Univ Singapore Dept Elect&Comp EngnSingapore117576Singapore Suzhou Institute of Biomedical Engineering and Technology Chinese.Academy of SciencesSuzhou215163China

As a stress hormone existing in the human body,cortisol can reflect the psychological stress and health status in daily life,and is a potential biomarker of the body’s stress *** effectively collect sweat and accurately identify the target,this paper reports a flexible wearable cortisol detection device with outstanding reliability and *** imprinted polymer(MIP)ensures cortisol *** carbon nanotubes(CNT)on electrodes increase sensitivity,expanding the detection range to 10^(−3) to 10^(4) nM,with sensitivity at 189.2 nA/lg(nM).In addition,porous chitosan hydrogel(PCSH)collects sweat effectively,its adhesive properties and 80%swelling rate offer a low-cost alternative to *** printed circuit board(FPCB)and serpentine electrode(SE)ensure device *** non-invasive,highly sensitive device offers a novel method for mental stress monitoring and clinical diagnosis,advancing human physiological state monitoring.

关键词： stress durability swelling

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Pickering multiphase materials using plant-based cellulosic micro/nanoparticles

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Aggregate 2024年第2期5卷 130-145页

作者： Wei Liu Bo Pang Meng Zhang Jiayi Lv Ting Xu Long Bai Xu-Min Cai Shuangquan Yao Siqi Huan Chuanling Si Tianjin Key Laboratory of Pulp and Paper Tianjin University of Science and TechnologyTianjinChina Department of Materials and Environmental Chemistry Stockholm UniversityStockholmSweden Key Laboratory of Bio-based Material Science and Technology(Ministry of Education) Northeast Forestry UniversityHarbinChina Guangxi Key Laboratory of Clean Pulp&Papermaking and Pollution Control College of Light Industry and Food EngineeringGuangxi UniversityNanningChina Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources College of Chemical EngineeringNanjing Forestry UniversityNanjingChina Department of Chemistry and Biological Engineering University of British ColumbiaVancouverCanada

Pickering multiphase systems stabilized by solid particles have recently attracted increasing attention due to their excellent *** various solid stabilizers,natural and renewable cellulosic micro/nanoparticles that are derived from agricultural and forestry sources have become promising candidates for Pickering stabilization due to their unique morphological features and tunable surface *** this review,recent progress on forming and stabilizing Pickering multiphase systems using cellulosic colloidal particles is summarized,including the physicochemical factors affecting their assembly at the interfaces and the preparation methods suitable for producing Pickering *** addition,relevant application prospects of corresponding Pickering multiphase materials are ***,current challenges and future perspectives of such renewable Pickering multiphase systems are *** review aims to encourage the utilization of cellulosic micro/nanoparticles as key components in the development of Pickering systems,leading to enhanced performance and unique functionalities.

关键词： cellulose nanocrystals cellulose nanofibrils cellulosic micro/nanoparticles Pickering emulsions Pickering foams

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Flow Field Prediction of Variable Geometry using a Novel Deep CNN Model with Dual-Feature of Flow Regions

Flow Field Prediction of Variable Geometry using a Novel Dee...

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第43届中国控制会议

作者： Mai Zhang Junzhe Cao Control Science and Engineering Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Flow field prediction of variable geometry aims for the precise prediction of varying flow fields with complex geometric shapes and their variations. By combining a novel deep convolutional neural network(CNN) model with a Computational Fluid Dynamics(CFD) method, the solution of the Navier-Stokes equation can be effectively approximated with a significant reduction in the corresponding computation time cost. This paper proposes an approach named AM UNet-3 for predicting the flow field of variable geometry, which can directly predict the expected flow field of new shapes after the training of deep CNN through extracting and identifying dual features of flow field regions: geometric information features and multi-class channel features. The AM UNet-3 is a convolutional neural network model that combines a U-Net variant structure with three independent decoders and attention mechanisms. The framework of U-Net can learn the complete numerical solutions of the N-S equations to velocity and pressure fields from ground-truth data. The three independent decoders are used to output the pressure field and the velocity components in the x-direction and y-direction respectively. The embedded channel attention and spatial attention mechanisms can enhance the ability of AM UNet-3 to extract fast-changing boundary layer characteristics. The performances of AM UNet-3, U-Net and UNet-3 are tested and compared on a dataset consisting of flow field data with 981different geometric shapes. Experiment results show that AM UNet-3 gets the fastest inference and the lowest prediction error in the three methods. Compared with the standard CFD method, AM UNet-3 is able to speed up the computation more than three orders of magnitude.

关键词： CFD Dual-Feature U-Net Attention Mechanism

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