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Reactive destabilization and bidirectional catalyzation for reversible hydrogen storage of liBH_(4) by novel waxberry-like nano-additive assembled from ultrafine Fe_(3)O_(4) particles

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Journal of Materials Science & Technology 2024年第6期173卷 63-71页

作者： S.Wang M.H.Wu y.y.Zhu Z.L.li y.X.yang y.Z.li H.F.liu M.X.Gao Department of Material Science Shenzhen MSU-BIT UniversityShenzhen 518172China State Key Laboratory of Silicon and Advanced Semiconductor Materials&School of Materials Science and Engineering Zhejiang UniversityHangzhou 310027China Institute of Resources Utilization and Rare Earth Development State Key Laboratory of Rare Metals Separation and Comprehensive UtilizationGuangdong Provincial Key Laboratory of Rare Earth Development and ApplicationGuangdong Academy of SciencesGuangzhou 510650China Institute of Science and Technology for New Energy Xi’an Technological UniversityXi’an 710021China National Supercomputing Center in Shenzhen Shenzhen 518055China

liBH_(4) containing 18.5 wt.%H_(2) is an attractive high-capacity hydrogen storage material,however,it suffers from high operation temperature and poor ***,a novel and low-cost bifunctional additive,waxberry-like Fe_(3)O_(4) secondary nanospheres assembled from ultrafine primary Fe_(3)O_(4) nanoparticles,is synthesized,which exhibits significant destabilization and bidirectional catalyzation towards(de)hydrogenation of liBH_(4).With an optimized addition of 30 wt.% waxberry-like Fe_(3)O_(4),the system initiated dehydrogenation below 100℃ and released a total of 8.1 wt.%H_(2) to 400℃.After 10 cycles,a capacity retention of 70% was achieved,greatly superior to previously reported oxides-modified *** destabilizing and catalyzing mechanisms of waxberry-like Fe_(3)O_(4) on liBH_(4) were systematically analyzed by phase and microstructural evolutions during dehydrogenation and hydrogenation cycling as well as density functional theory(DFT)*** present work provides new insights in developing advanced nano-additives with unique structural and multifunctional designs towards liBH4 hydrogen storage.

关键词： liBH_(4) Hydrogen storage Waxberry-like Fe_(3)O_(4) Destabilization Catalysis

Conventional and micro scale finite element modeling for metal cutting process:A review

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Chinese Journal of Aeronautics 2024年第2期37卷 199-232页

作者： Le WANG Caixu yUE Xianli liU Ming li yongshi XU Steven y.liANG Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of EducationHarbin University of Science and TechnologyHarbin 150080China George W.Woodruff School of Mechanical Engineering Georgia Institute of TechnologyAtlanta 30332USA

The metal cutting process is accompanied by complex stress field,strain field,temperature *** comprehensive effects of process parameters on chip morphology,cutting force,tool wear and residual stress are complex and *** element method(FEM)is considered as an effective method to predict process variables and reveal microscopic physical phenomena in the cutting ***,the finite element(FE)simulation is used to research the conventional and micro scale cutting process,and the differences in the establishment of process variable FE simulation models are distinguished,thereby improving the accuracy of FE *** reliability and effectiveness of FE simulation model largely depend on the accuracy of the simulation method,constitutive model,friction model,damage model in describing mesh element,the dynamic mechanical behavior of materials,the tool-chip-workpiece contact process and the chip formation *** this paper,the FE models of conventional and micro process variables are comprehensively and up-to-date reviewed for different materials and machining *** purpose is to establish a FE model that is more in line with the real cutting conditions,and to provide the possibility for optimizing the cutting process *** development direction of FE simulation of metal cutting process is discussed,which provides guidance for future cutting process modeling.

关键词： Conventional and micro scale Finite element simulation Metal cutting process Micro cutting Modeling

Physics-informed deep learning for fringe pattern analysis

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Opto-Electronic Advances 2024年第1期7卷 4-15页

作者： Wei yin yuxuan Che Xinsheng li Mingyu li yan Hu Shijie Feng Edmund y.Lam Qian Chen Chao Zuo Smart Computational Imaging Laboratory(SCILab) School of Electronic and Optical EngineeringNanjing University of Science and TechnologyNanjing 210094China Smart Computational Imaging Research Institute(SCIRI)of Nanjing University of Science and Technology Nanjing 210019China Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense Nanjing 210094China Department of Electrical and Electronic Engineering The University of Hong KongPokfulamHong Kong SAR 999077China

Recently,deep learning has yielded transformative success across optics and photonics,especially in optical *** neural networks (DNNs) with a fully convolutional architecture (e.g.,U-Net and its derivatives) have been widely implemented in an end-to-end manner to accomplish various optical metrology tasks,such as fringe denoising,phase unwrapping,and fringe ***,the task of training a DNN to accurately identify an image-to-image transform from massive input and output data pairs seems at best naive,as the physical laws governing the image formation or other domain expertise pertaining to the measurement have not yet been fully exploited in current deep learning *** this end,we introduce a physics-informed deep learning method for fringe pattern analysis (PI-FPA) to overcome this limit by integrating a lightweight DNN with a learning-enhanced Fourier transform profilometry (Le FTP) *** parameterizing conventional phase retrieval methods,the Le FTP module embeds the prior knowledge in the network structure and the loss function to directly provide reliable phase results for new types of samples,while circumventing the requirement of collecting a large amount of high-quality data in supervised learning *** by the initial phase from Le FTP,the phase recovery ability of the lightweight DNN is enhanced to further improve the phase accuracy at a low computational cost compared with existing end-to-end *** results demonstrate that PI-FPA enables more accurate and computationally efficient single-shot phase retrieval,exhibiting its excellent generalization to various unseen objects during *** proposed PI-FPA presents that challenging issues in optical metrology can be potentially overcome through the synergy of physics-priors-based traditional tools and data-driven learning approaches,opening new avenues to achieve fast and accurate single-shot 3D imaging.

关键词： optical metrology deep learning physics-informed neural networks fringe analysis phase retrieval

Hard yet tough and self-lubricating(CuNiTiNbCr)C_(x) high-entropy nanocomposite films:Effects of carbon content on structure and properties

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Journal of Materials Science & Technology 2024年第6期173卷 20-30页

作者： y.T.li X.M.Chen X.K.Zeng M.liu X.Jiang y.X.Leng Key Laboratory of Advanced Technologies of Materials Ministry of EducationSchool of Materials Science and EngineeringSouthwest Jiaotong UniversityChengdu 610031China Key Laboratory of Noise and Vibration Research Institute of AcousticsChinese Academy of SciencesBeijing 100190China State Key Laboratory of Acoustics Institute of AcousticsChinese Academy of SciencesBeijing 100190China School of Mechanical and Electrical Engineering Mianyang Teachers’CollegeMianyang 621000China

The single-phase high-entropy alloy film is difficult to meet severe friction conditions due to its low hardness and high friction ***-composite structure film is composed of at least two separated phases,showing the properties of strength and toughness integration and excellent wear *** design of nanocomposite structures can effectively improve the mechanical properties and tribological properties of high-entropy alloy *** this study,the(CuNiTiNbCr)C_(x) nanocomposite high-entropy films(HEFs)integrated with high hardness,high toughness,and self-lubrication were synthesized by the double-target co-sputtering *** effect of carbon content on microstructure,mechanical properties,and tribological properties of(CuNiTiNbCr)C_(x) films was *** the increase of carbon content in the HEFs,the carbon atoms preferentially react with Ti,Nb,and Cr to form a(TiNbCr)C ceramic-reinforced phase,and then the excess carbon atoms precipitate in the form of amorphous carbon(a-C)lubricating phase in the *** structure of the HEFs changes from an amorphous structure to a nanocomposite structure of amorphous(amorphous CuNiTiNbCr phase+a-C phase)/nanocrystalline(TiN-bCr)C *** the carbon content is about 21.2 at.%,the carbide phase in the film reaches saturation and the hardness and modulus of the films are highest,which are 18 GPa and 228 GPa,*** HEFs with a carbon content of 44.0 at.%show the best toughness and tribological properties with a friction coefficient of 0.16 and a wear rate of 2.4×10^(-6) mm^(3)/(N m),which is mainly attributed to the excellent resistance to fatigue crack growth and the interfacial lubricating layer formed in the friction *** nanocomposite(CuNiTiNbCr)C_(x) HEFs show very promising application prospect in the field of friction protection.

关键词： High-entropy films Nanocomposite Double-target co-sputtering Strengthening-toughening Tribological properties

Re-Distributing Facial Features for Engagement Prediction with ModernTCN

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Computers, Materials and Continua 2024年第1期81卷 369-391页

作者： li X. Zhu W. li Q. Hou C. Zhang y. College of Information and Artificial Intelligence Nanchang Institute of Science and Technology Nanchang 330108 China School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan 430205 China School of Electronic Information Engineering Wuhan Donghu University Wuhan 430212 China

Automatically detecting learners’ engagement levels helps to develop more effective online teaching and assessment programs, allowing teachers to provide timely feedback and make personalized adjustments based on students’ needs to enhance teaching effectiveness. Traditional approaches mainly rely on single-frame multimodal facial spatial information, neglecting temporal emotional and behavioural features, with accuracy affected by significant pose variations. Additionally, convolutional padding can erode feature maps, affecting feature extraction’s representational capacity. To address these issues, we propose a hybrid neural network architecture, the redistributing facial features and temporal convolutional network (RefEIP). This network consists of three key components: first, utilizing the spatial attention mechanism large kernel attention (LKA) to automatically capture local patches and mitigate the effects of pose variations; second, employing the feature organization and weight distribution (FOWD) module to redistribute feature weights and eliminate the impact of white features and enhancing representation in facial feature maps. Finally, we analyse the temporal changes in video frames through the modern temporal convolutional network (ModernTCN) module to detect engagement levels. We constructed a near-infrared engagement video dataset (NEVD) to better validate the efficiency of the RefEIP network. Through extensive experiments and in-depth studies, we evaluated these methods on the NEVD and the Database for Affect in Situations of Elicitation (DAiSEE), achieving an accuracy of 90.8% on NEVD and 61.2% on DAiSEE in the four-class classification task, indicating significant advantages in addressing engagement video analysis problems. © 2024 The Authors. Published by Tech Science Press.

关键词： Engagement prediction re-distributing facial features spatiotemporal network temporal convolutional network

Towards an ultrafast 3D imaging scanning liDAR system:a review

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Photonics Research 2024年第8期12卷 1709-1729页

作者： ZHI li yAQI HAN liCAN WU ZIHAN ZANG MAOliN DAI SZE yUN SET SHINJI yAMASHITA QIAN li H.y.FU Tsinghua Shenzhen International Graduate School Tsinghua UniversityShenzhen 518055China Department of Electrical Engineering and Information Systems The University of TokyoTokyo 113-8656Japan Research Center for Advanced Science and Technology The University of TokyoTokyo 153-8904Japan School of Electronic and Computer Engineering Peking UniversityShenzhen 518055China

light detection and ranging(liDAR),as a hot imaging technology in both industry and academia,has undergone rapid innovation and *** current mainstream direction is towards system miniaturization and *** are many metrics that can be used to evaluate the performance of a liDAR system,such as lateral resolution,ranging accuracy,stability,size,and *** recently,with the continuous enrichment of liDAR application scenarios,the pursuit of imaging speed has attracted tremendous research ***,for autonomous vehicles running on motorways or industrial automation applications,the imaging speed of liDAR systems is a critical *** this review,we will focus on discussing the upper speed limit of the liDAR *** on the working mechanism,the limitation of optical parts on the maximum imaging speed is *** beam scanner has the greatest impact on imaging *** provide the working principle of current popular beam scanners used in liDAR systems and summarize the main constraints on the scanning ***,we highlight the spectral scanning liDAR as a new paradigm of ultrafast ***,to further improve the imaging speed,we then review the parallel detection methods,which include multiple-detector schemes and multiplexing ***,we summarize the liDAR systems with the fastest point acquisition rate reported *** the outlook,we address the current technical challenges for ultrafast liDAR systems from different aspects and give a brief analysis of the feasibility of different approaches.

关键词： liDAR scanner system

Optimization of chemistry and process parameters for control of intermetallic formation in Mg sludges

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Journal of Magnesium and Alloys 2024年第4期12卷 1431-1448页

作者： y.Fu G.G.Wang A.Hu y.li K.B.Thacker J.P.Weiler H.Hu Department of Mechanical Automotive and Materials EngineeringUniversity of Windsor401 Sunset AveWindsorOntario N9B 3P4Canada Global Technology Centre Meridian Lightweight Technologies25 MacNab AveStrathroyOntario N7G 4H6Canada

Intermetallic formation in sludge during magnesium(Mg)melting,holding and high pressure die casting practices is a very important ***,very often it is overlooked by academia,original equipment manufacturers(OEM),metal ingot producers and even die *** aim of this study was to minimize the intermetallic formation in Mg sludge via the optimization of the chemistry and process *** Al8Mn5 intermetallic particles were identified by the microstructure analysis based on the Al and Mn *** design of experiment(DOE)technique,Taguchi method,was employed to minimize the intermetallic formation in the sludge of Mg alloys with various chemical compositions of Al,Mn,Fe,and different process parameters,holding temperature and holding *** sludge yield(Sy)and intermetallic size(IS)was selected as two *** optimum combination of the levels in terms of minimizing the intermetallic formation were 9 wt.%Al,0.15 wt.%Mn,0.001 wt.%(10 ppm)Fe,690℃ for the holding temperature and holding at 30 mins for the holding time,*** best combination for smallest intermetallic size were 9 wt.%Al,0.15 wt.%Mn,0.001 wt.%(10 ppm)Fe,630℃ for the holding temperature and holding at 60 mins for the holding time,*** groups of sludge factors,Chemical Sludge(CSF),Physical Sludge(PSF)and Comprehensive Sludge Factors(and CPSF)were established for prediction of sludge yields and intermetallic sizes in Al-containing Mg *** CPSF with five independent variables including both chemical elements and process parameters gave high accuracy in prediction,as the prediction of the PSF with only the two processing parameters of the melt holding temperature and time showed a relatively large deviation from the experimental *** Chemical Sludge Factor was primarily designed for small ingot producers and die casters with a limited melting and holding capacity,of which process parameters could be fixed *** Physical Sludge Factor could be used f

关键词： Magnesium sludge Al-Mn intermetallic Optimization Taguchi method Sludge factor Chemical composition Process parameter

Weakly Supervised Object Localization with Background Suppression Erasing for Art Authentication and Copyright Protection

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Machine Intelligence Research 2024年第1期21卷 89-103页

作者： Chaojie Wu Mingyang li ying Gao Xinyan Xie Wing W.y.Ng Ahmad Musyafa School of Computer Science and Engineering South China University of TechnologyGuangzhou 511442China Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application Guangdong Provincial People's HospitalGuangzhou 510180China

The problem of art forgery and infringement is becoming increasingly prominent,since diverse self-media contents with all kinds of art pieces are released on the Internet every *** art paintings,object detection and localization provide an efficient and ef-fective means of art authentication and copyright ***,the acquisition of a precise detector requires large amounts of ex-pensive pixel-level *** alleviate this,we propose a novel weakly supervised object localization(WSOL)with background su-perposition erasing(BSE),which recognizes objects with inexpensive image-level ***,integrated adversarial erasing(IAE)for vanilla convolutional neural network(CNN)dropouts the most discriminative region by leveraging high-level semantic ***,a background suppression module(BSM)limits the activation area of the IAE to the object region through a self-guidance ***,in the inference phase,we utilize the refined importance map(RIM)of middle features to obtain class-agnostic loc-alization *** experiments are conducted on paintings,CUB-200-2011 and ILSVRC to validate the effectiveness of our BSE.

关键词： Weakly supervised object localization erasing method deep learning computer vision art authentication and copyright protection

Research on Defect Detection ofWind Turbine Blades Based onMorphology and Improved Otsu Algorithm Using Infrared Images

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Computers, Materials and Continua 2024年第1期81卷 933-949页

作者： Kang S. He y. li W. liu S. School of Mechanical and Control Engineering Baicheng Normal University Baicheng 137000 China School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin 132022 China

To address the issues of low accuracy and high false positive rate in traditional Otsu algorithm for defect detection on infrared images of wind turbine blades (WTB), this paper proposes a technique that combines morphological image enhancement with an improved Otsu algorithm. First, mathematical morphology's differential multi-scale white and black top-hat operations are applied to enhance the image. The algorithm employs entropy as the objective function to guide the iteration process of image enhancement, selecting appropriate structural element scales to execute differential multi-scale white and black top-hat transformations, effectively enhancing the detail features of defect regions and improving the contrast between defects and background. Afterwards, grayscale inversion is performed on the enhanced infrared defect image to better adapt to the improved Otsu algorithm. Finally, by introducing a parameter K to adjust the calculation of inter-class variance in theOtsumethod, theweight of the target pixels is increased. Combined with the adaptive iterative threshold algorithm, the threshold selection process is further fine-tuned. Experimental results show that compared to traditional Otsu algorithms and other improvements, the proposed method has significant advantages in terms of defect detection accuracy and reducing false positive rates. The average defect detection rate approaches 1, and the average Hausdorff distance decreases to 0.825, indicating strong robustness and accuracy of the method. © 2024 The Authors.

关键词： adaptive iterative thresholding grayscale inversion improved Otsu algorithm infrared image Morphological enhancement