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Preparation of tungsten-particle-reinforced Zr-based bulk metallic glass composites by two-step spark plasma sintering:microstructure evolution,densification mechanism and mechanical properties

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Rare Metals 2024年第4期43卷 1793-1808页

作者： Yun-fei Ma Pan Gong Mao Zhang Hui-EHu Zhen Peng Xiao Xu Xin Wang Mehdi Malekan Xue-feng Tang Lei Deng Jun-Song jin Xin-Yun Wang State Key Laboratory of Materials Processing and Die and Mould Technology School of Materials Science and EngineeringHuazhong University of Science and TechnologyWuhan430074China Research Institute of Huazhong university of Science and Technology in Shenzhen Shenzhen518057China Department of Chemistry and Materials Naval University of EngineeringWuhan430032China School of Materials Science and Engineering Jiangsu UniversityZhenjiang212013China College of Machine Shanghai Dianji UniversityShanghai201306China School of Metallurgy and Materials Engineering College of EngineeringUniversity of TehranTehran 11155-4563Iran

A new two-step spark plasma sintering(TSS)process with low-temperature pre-sintering and high-temperature final sintering has been successfully applied to prepare the tungsten-particle(Wp)-reinforced bulk metallic glass composites(Wp/BMGCs).Compared to normal spark plasma sintering(NS),the densification rate and relative density of Wp/BMGCs can be improved by selecting TSS with appropriate sintering pressure in the low temperature pre-sintering ***,the compressive strength and plastic strain of 30%Wp/BMGCs prepared by TSS are both higher than those of the samples prepared by *** TSS process can significantly enhance the compressive strength of 30%Wp/BMGCs by 12%and remarkably increase the plastic strain by 50%,while the trend is completely opposite for 50%Wp/***-in situ experiments and finite element simulations reveal that uneven temperature distribution among particles during low-temperature pre-sintering causes local overheating at contact points between particles,accelerating formation of sintering neck between particles and plastic deformation of *** the volume fraction of Wp is low,TSS can improve the interface bonding between particles by increasing the number of sintering *** makes the fracture mode of Wp/BMGCs being predominantly transgranular ***,as the volume fraction of Wp increases,the adverse effects of Wp plastic deformation are becoming more and more *** aggregated Wp tends to form a solid"cage structure"that hinders the bonding between particles at the interface;correspondingly,the fracture behavior of Wp/BMGCs is mainly dominated by intergranular ***,reducing the sintering pressure during the low-temperature pre-sintering stage of TSS has been shown to effectively decrease plastic deformation in Wp,resulting in a higher degree of densification and better mechanical properties.

关键词： Bulk metallic glass composites Tungsten particle Two-step spark plasma sintering Densification mechanism Mechanical properties

Constrained Multi-Objective Optimization With Deep Reinforcement Learning Assisted Operator Selection

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 919-931页

作者： fei Ming Wenyin Gong Ling Wang Yaochu jin the School of Computer Science China University of GeosciencesWuhan 430074China the Department of Automation Tsinghua UniversityBeijing 100084China the Faculty of Technology Bielefeld UniversityNorth Rhine-Westphalia33619 BielefeldGermany

Solving constrained multi-objective optimization problems with evolutionary algorithms has attracted considerable *** constrained multi-objective optimization evolutionary algorithms(CMOEAs)have been developed with the use of different algorithmic strategies,evolutionary operators,and constraint-handling *** performance of CMOEAs may be heavily dependent on the operators used,however,it is usually difficult to select suitable operators for the problem at ***,improving operator selection is promising and necessary for *** work proposes an online operator selection framework assisted by Deep Reinforcement *** dynamics of the population,including convergence,diversity,and feasibility,are regarded as the state;the candidate operators are considered as actions;and the improvement of the population state is treated as the *** using a Q-network to learn a policy to estimate the Q-values of all actions,the proposed approach can adaptively select an operator that maximizes the improvement of the population according to the current state and thereby improve the algorithmic *** framework is embedded into four popular CMOEAs and assessed on 42 benchmark *** experimental results reveal that the proposed Deep Reinforcement Learning-assisted operator selection significantly improves the performance of these CMOEAs and the resulting algorithm obtains better versatility compared to nine state-of-the-art CMOEAs.

关键词： Constrained multi-objective optimization deep Qlearning deep reinforcement learning(DRL) evolutionary algorithms evolutionary operator selection

Carbon nanotube films with ultrahigh thermal-shock and thermalshock-fatigue resistance characterized by ultra-fast ascending shock testing

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Nano Research 2024年第8期17卷 6777-6784页

作者： Mingquan Zhu Shijun Wang Yunxiang Bai feng Gao Zhenxing Zhu Congying Wang Peng Zhang Hao jin Hui Zhang Luqi Liu Zhiping Xu Xinghong Zhang fei Wei Zhong Zhang CAS Key Laboratory of Nanosystem and Hierarchical Fabrication CAS Center for Excellence in NanoscienceNational Center for Nanoscience and TechnologyChinese Academy of SciencesBeijing 100190China university of Chinese Academy of Sciences Beijing 100049China Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology Department of Chemical EngineeringTsinghua UniversityBeijing 100084China Department of Engineering Mechanics Tsinghua UniversityBeijing 100084China National Key Laboratory of Science and Technology on Advanced Composites in Special Environments Center for Composite Materials and StructuresHarbin Institute of TechnologyHarbin 150001China CAS Key Laboratory of Mechanical Behavior and Design of Materials Department of Modern MechanicsUniversity of Science and Technology of ChinaHefei 230027China

The exploration of material failure behavior not only involves defining its limits and underlying mechanisms but also entails devising strategies for improvement and protection in extreme ***'ve pioneered an advanced multi-scale,high-speed ascending thermal shock testing platform capable of inducing unprecedented heat shocks at rates surpassing 105℃/*** meticulous examination of the thermal shock responses of carbon nanotube(CNT)films,we've achieved remarkable *** employing an innovative macro-scale synchronous tightening and relaxing approach,we've attained a critical temperature differential in CNT films that exceeds an exceptional 2500℃—surpassing any previously reported metric for highperformance,thermal-shock-resistant ***,these samples have demonstrated exceptional resilience,retaining virtually unchanged strength even after enduring 10,000 thermal shock cycles at temperatures exceeding 1000℃.Furthermore,our research has revealed a novel thermal shock/fatigue failure mechanism that fundamentally diverges from conventional theories centered on thermal stress.

关键词： carbon nanotubes failure behavior thermal shock characterization

Predicting influenza-like illness trends based on sentinel surveillance data in china from 2011 to 2019:A modelling and comparative study

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Infectious Disease Modelling 2024年第3期9卷 816-827页

作者： Xingxing Zhang Liuyang Yang teng Chen Qing Wang jin Yang Ting Zhang Jiao Yang Hongqing Zhao Shengjie Lai Luzhao feng Weizhong Yang School of Population Medicine and Public Health Chinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing100073China State Key Laboratory of Respiratory Health and Multimorbidity China Key Laboratory of Pathogen Infection Prevention and Control(Peking Union Medical College) Ministry of EducationChina National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases National Institute for Communicable Disease Control and PreventionChinese Center for Disease Control and PreventionChina Department of Management Science and Information System Faculty of Management and EconomicsKunming University of Science and TechnologyKunming650506China Department of Applied Mathematics&Statistics Stony Brook UniversityStony BrookNY11794-3600USA WorldPop School of Geography and Environmental ScienceUniversity of SouthamptonSouthamptonSO171BJUK

Background Influenza is an acute respiratory infectious disease with a significant global disease ***,the coronavirus disease 2019 pandemic and its related non-pharmaceutical interventions(NPIs)have introduced uncertainty to the spread of ***,comparative studies on the performance of innovative models and approaches used for influenza prediction are ***,this study aimed to predict the trend of influenza-like illness(ILI)in settings with diverse climate characteristics in china based on sentinel surveillance data using three approaches and evaluate and compare their predictive *** The generalized additive model(GAM),deep learning hybrid model based on Gate Recurrent Unit(GRU),and autoregressive moving average-generalized autoregressive conditional heteroscedasticity(ARMA—GARCH)model were established to predict the trends of ILI 1-,2-,3-,and 4-week-ahead in Beijing,Tianjin,Shanxi,Hubei,Chongqing,Guangdong,Hainan,and the Hong Kong Special Administrative Region in china,based on sentinel surveillance data from 2011 to *** relevant metrics,namely,Mean Absolute Percentage Error(MAPE),Root Mean Squared Error(RMSE),and R squared,were calculated to evaluate and compare the goodness of fit and robustness of the three *** Considering the MAPE,RMSE,and R squared values,the ARMA—GARCH model performed best,while the GRU-based deep learning hybrid model exhibited moderate performance and GAM made predictions with the least accuracy in the eight settings in ***,the models’predictive performance declined as the weeks ahead ***,blocked cross-validation indicated that all models were robust to changes in data and had low risks of *** Our study suggested that the ARMA—GARCH model exhibited the best accuracy in predicting ILI trends in china compared to the GAM and GRU-based deep learning hybrid ***,in the future,the ARMA—GARCH model may be used

关键词： Influenza-like illness Influenza Sentinel surveillance china Predicting Modeling

Ternary-phase layered cathodes toward ultra-stable and highrate sodium ion storage

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Rare Metals 2024年第4期43卷 1589-1598页

作者： Wen-Ji Yin Pei-Dan Su Qi Lu Xiao-Qiong Li Ji-Ming Peng teng-fei Zhou Ge-Meng Liang Yu-Liang Cao Hong-Qiang Wang Qing-Yu Li Si-Jiang Hu Guangxi Key Laboratory of Low Carbon Energy Materials School of Chemistry and Pharmaceutical SciencesGuangxi Normal UniversityGuilin541004China Institutes of Physical Science and Information Technology Anhui UniversityHefei230601China Department of Chemistry and Pharmaceutical Sciences Guilin Normal CollegeGuilin541199China College of Chemistry and Chemical Engineering Huanggang Normal UniversityHuanggang438000China School of Chemical Engineering and Advanced Materials The University of AdelaideAdelaide5005Australia Engineering Research Center of Organosilicon Compounds and Materials of Ministry of Education College of Chemistry and Molecular SciencesWuhan UniversityWuhan430072China

With the shortage of lithium resources,sodiumion batteries(SIBs)are considered one of the most promising candidates for lithium-ion batteries.P2-type and O3-type layered oxides are one of the few cathodes that can access high energy ***,they usually exhibit structural change,capacity decay,and slow Na ion ***,we present layered ternary-phase cathodes with P2,P3 and O3 phases by a lattice doping strategy,which is demonstrated by X-ray diffraction(XRD)*** the characteristics of P2,P3 and O3 phases,the layered composites show performance improvement during long-term battery *** particular,Na_(0.7)Li_(0.1)Co_(0.3-)Fe_(0.3)Mn_(0.3)O_(2)(NLCFM)delivers a reversible capacity of120.1 mAh·g^(-1)at 0.1C(1.0C=175 mA·g^(-1))with a superior capacity retention of 72.5%after 1000 cycles *** work offers insights into the development of advanced cathode materials for SIBs.

关键词： Sodium-ion battery Cathode material Layered oxides Lattice doping Mixed phase

High critical current density in Li_(6.4)La_(3)Zr_(1.4)Ta_(0.6)O_(12) electrolyte via interfacial engineering with complex hydride

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Rare Metals 2024年第2期43卷 692-701页

作者： Ying-Tong Lv teng-fei Zhang Zhao-Tong Hu Guang-Lin Xia Ze-Ya Huang Zhen-Hua Liu Li-Hua Que Cai-Ting Yuan Fang-Qin Guo Takayuki Ichikawa Xue-Bin Yu College of Materials Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing210016China Centre for Hydrogenergy College of Materials Science and TechnologyNanjing University of Aeronautics and AstronauticsNanjing210016China Department of Materials Science Fudan UniversityShanghai200433China Graduate School of Advanced Science and Engineering Hiroshima University1-4-1 KagamiyamaHigashi-Hiroshima739-8527Japan

Garnet-type solid-state batteries(SSBs)are considered to be one of the most promising candidates to realize next-generation lithium metal batteries with high energy density and ***,the dendrite-induced short-circuit and the poor interfacial contact impeded the practical ***,interface engineering to achieve low interfacial resistance without high temperature calcination was developed,which Li_(6.4)La_(3)Zr_(1.4)Ta_(0.6)O_(12)(LLZTO)was simply coated with complex hydride(Li_(4)(BH_(4))_(3)I(3L1L))in various mass ratios n(Li_(4)(BH_(4))_(3)I)-(100−n)LLZTO(10≤n≤40).The interfacial conductivity increases by more than three orders of magnitude from 8.29×10^(−6)S·cm^(−1)to 1.10×10^(−2)S·cm^(−1).Symmetric Li cells exhibit a high critical current density(CCD)of 4.0 mA·cm^(−2) and an excellent cycling stability for 200 h at 4.0 mA·cm^(−2).SSBs with polymeric sulfur-polyacrylonitrile(SPAN)cathode achieve a high discharge capacity of 1149 mAh·g^(−1) with a capacity retention of 91%after 100 cycles(0.2 C).This attempt guides a simple yet efficient strategy for obtaining a stable Li/LLZTO interface,which would promote the development of solid-state batteries.

关键词： Hydrides Li_(6.4)La_(3)Zr_(1.4)Ta_(0.6)O_(12)(LLZTO) Critical current density Solid-state electrolytes(SSEs) Lithium-sulfur batteries

Diagnostic performance of intravascular ultrasound-based fractional flow reserve in evaluating of intermediate left main stenosis

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Journal of Geriatric Cardiology 2024年第1期21卷 34-43页

作者： yong-Gang SUI Cheng YANG Chang-Dong GUAN Yan-Lu XU Na-Qiong WU Wei-Xian YANG yong-Jian WU Ke-fei DOU Yue-jin YANG Shu-Bin QIAO Wei YU Bo XU Sheng-Xian TU Jie QIAN Department of Cardiology Fuwai HospitalNational Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina Catheterization Laboratories Fuwai HospitalNational Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina Biomedical Instrument Institute School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghaiChina National Clinical Research Center for Cardiovascular Diseases BeijingChina

BACKGROUND The recently introduced ultrasonic flow ratio(UFR),is a novel fast computational method to derive fractional flow reserve(FFR)from intravascular ultrasound(IVUS)*** the present study,we evaluate the diagnostic performance of UFR in patients with intermediate left main(LM)*** This is a prospective,single center study enrolling consecutive patients with presence of intermediated LM lesions(diameter stenosis of 30%-80%by visual estimation)underwent IVUS and FFR *** independent core laboratory assessed offline UFR and IVUS-derived minimal lumen area(MLA)in a blinded *** Both UFR and FFR were successfully achieved in 41 LM patients(mean age,62.0±9.9 years,46.3%diabetes).An acceptable correlation between UFR and FFR was identified(r=0.688,P50%(AUC=0.66,P<0.001)and numerically higher than IVUS-derived MLA(AUC=0.82;P=0.09).Patient level diagnostic accuracy,sensitivity and specificity for UFR to identify FFR≤0.80 was 82.9%(95%CI:70.2-95.7),93.1%(95%CI:82.2-100.0),58.3%(95%CI:26.3-90.4),*** In patients with intermediate LM diseases,UFR was proved to be associated with acceptable correlation and high accuracy with pressure wire-based FFR as standard *** present study supports the use of UFR for functional evaluation of intermediate LM stenosis.

关键词： stenosis flow fractional

Boundary Regularity of Isometries Between Infinitely Flat Complex Domains

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Acta Mathematica Sinica,English Series 2024年第6期40卷 1375-1387页

作者： jin Song LIU fei TAO Hong Yu WANG Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing 100190P.R.China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049P.R.China Beijing International Center for Mathematical Research Peking UniversityBeijing 100871P.R.China School of Science Beijing University of Posts and TelecommunicationsBeijing 100876P.R.China Key Laboratory of Mathematics and Information Networks(Beijing university of Posts and Telecommunications) Ministry of EducationBeijing 100876P.R.China

In this paper we prove that isometries with respect to the Kobayashi metric between certain domains having boundary points at which the boundary is infinitely flat extend continuously to the *** strategy is to reestab... 详细信息

关键词： Boundary extension Kobayashi metric isometries

Prediction of fracture initiation in cohesive soils based on data mining modelling and large-scale laboratory verification

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Underground Space 2024年第6期19卷 279-300页

作者： Weiping Luo Dajun Yuan Yannick Choy Hing Ng Dalong jin Ping Lu teng Wang Department of Geotechnical Engineering College of Civil EngineeringTongji UniversityShanghai 200092China Key Laboratory of the Ministry of Education for Urban Underground Engineering Beijing Jiaotong UniversityBeijing 100044China Department of Civil and Environmental Engineering National University of SingaporeSingapore 119077Singapore

Many empirical and analytical methods have been proposed to predict fracturing pressure in cohesive *** of them take into account three to four specific influencing factors and rely on the assumption of a failure *** this study,a novel data-mining approach based on the XGBoost algorithm is investigated for predicting fracture initiation in cohesive *** has the advantage of handling multiple influencing factors simultaneously,without pre-determining a failure mode.A dataset of 416 samples consisting of 14 distinct features was herein collected from past studies,and used for developing a regressor and a classifier model for fracturing pressure prediction and failure mode classification *** results show that the intrinsic characteristics of the soil govern the failure mode while the fracturing pressure is more sensitive to the stress *** XGBoost-based model was also tested against conventional approaches,as well as a similar machine learning algorithm namely random forest ***,several large-scale triaxial fracturing tests and an in-situ case study were carried out to further verify the generalization ability and applicability of the proposed data mining approach,and the results indicate a superior performance of the XGBoost model.

关键词： Fracturing pressure Failure mode Cohesive soil Data-mining Large-scale tests