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Preparation of Self-limiting Heating Cables with Excellent Processability, Mechanical Properties and PTC Effect via Thermal and Electrical Treatments

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Chinese Journal of Polymer Science 2024年第4期42卷 511-520页

作者： tian-Hao Yang Tong Wu Qiang Fu State Key Laboratory of Polymer Materials Engineering College of Polymer Science and EngineeringSichuan UniversityChengdu610065China State Key Laboratory of Polymer Materials Engineering Polymer Research Institute of Sichuan UniversityChengdu610065China

Polymer/conductive filler composites have been widely used for the preparation of self-limiting heating cables with the positive temperature coefficient (PTC) effect. The control of conductive filler distribution and network in polymer matrix is the most critical for performance of PTC materials. In order to compensate for the destruction of the filler network structure caused by strong shearing during processing, an excessive conductive filler content is usually added into the polymer matrix, which in turn sacrifices its processability and mechanical properties. In this work, a facile post-treatment of the as-extruded cable, including thermal and electrical treatment to produce high-density polyethylene (HDPE)/carbon black (CB) cable with excellent PTC effect, is developed. It is found for the as-extruded sample, the strong shearing makes the CB particles disperse uniformly in HDPE matrix, and 25 wt% CB is needed for the formation of conductive paths. For the thermal-treated sample, a gradually aggregated CB filler structure is observed, which leads to the improvement of PTC effect and the notable reduction of CB content to 20 wt%. It is very interesting to see that for the sample with combined thermal and electrical treatment, CB particles are agglomerated and oriented along the electric field direction to create substantial conductive paths, which leads to a further decrease of CB content down to 15 wt%. In this way, self-limiting heating cables with excellent processability, mechanical properties and PTC effect have simultaneously been achieved.

关键词： Self-limiting heating cables Positive temperature coefficient Thermal treatment Electrical treatment

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Electrochemical anodic oxidation assisted fabrication of memristors

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International Journal of Extreme Manufacturing 2024年第3期6卷 250-272页

作者： Shuai-Bin Hua tian Jin Xin Guo School of Materials Science and Engineering State Key Laboratory of Material Processing and Die&Mould TechnologyHuazhong University of Science and TechnologyWuhan 430074People’s Republic of China

Owing to the advantages of simple structure,low power consumption and high-density integration,memristors or memristive devices are attracting increasing attention in the fields such as next generation non-volatile memories,neuromorphic computation and data ***,the deposition of memristive films often requires expensive equipment,strict vacuum conditions,high energy consumption,and extended processing *** contrast,electrochemical anodizing can produce metal oxide films quickly(e.g.10 s) under ambient *** means of the anodizing technique,oxide films,oxide nanotubes,nanowires and nanodots can be fabricated to prepare *** film thickness,nanostructures,defect concentrations,etc,can be varied to regulate device performances by adjusting oxidation parameters such as voltage,current and *** memristors fabricated by the anodic oxidation technique can achieve high device consistency,low variation,and ultrahigh yield *** article provides a comprehensive review of the research progress in the field of anodic oxidation assisted fabrication of ***,the principle of anodic oxidation is introduced;then,different types of memristors produced by anodic oxidation and their applications are presented;finally,features and challenges of anodic oxidation for memristor production are elaborated.

关键词： anodic oxidation anodized aluminium oxide memristor resistive switching electrical properties

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Model-driven path planning for robotic plasma cutting of branch pipe with single Y-groove based on pipe-rotating scheme

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Advances in Manufacturing 2024年第1期12卷 94-107页

作者： Yan Liu Qiu Tang Xin-Cheng tian School of Control Science and Engineering Shandong UniversityJinan250061People’s Republic of China Engineering Research Center of Intelligent Unmanned System Ministry of EducationJinan250061People’s Republic of China School of Mechanical and Electronic Engineering Shandong Jianzhu UniversityJinan250101People’s Republic of China

The automatic cutting of intersecting pipes is a challenging task in *** improved automation and accuracy,this paper proposes a model-driven path planning approach for the robotic plasma cutting of a branch pipe with a single ***,it summarizes the intersection forms and introduces a dual-pipe intersection *** on this model,the moving three-plane structure(a description unit of the geometric characteristics of the intersecting curve)is constructed,and a geometric model of the branch pipe with a single Y-groove is ***,a novel mathematical model for plasma radius and taper compensation is ***,the compensation model and groove model are integrated by establishing movable ***,to prevent collisions between the plasma torch and workpiece,the torch height is planned and a branch pipe-rotating scheme is *** the established models and moving frames,the planned path description of cutting robot is provided in this novel *** accuracy of the proposed method is verified by simulations and robotic cutting experiments.

关键词： Automatic groove cutting of intersecting pipes Model-driven robot path planning Plasma beam radius and taper compensation

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Friendship Inference Based on Interest Trajectory Similarity and Co-occurrence

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Chinese Journal of Electronics 2024年第3期33卷 708-720页

作者： Junfeng tian Zhengqi HOU School of Cyber Security and Computer Hebei University Hebei Key Laboratory of High Confidence Information Systems Hebei University

Most of the current research on user friendship speculation in location-based social networks is based on the co-occurrence characteristics of users,however,statistics find that co-occurrence is not common among all users;meanwhile,most of the existing work focuses on mining more features to improve the accuracy but ignoring the time complexity in practical *** this basis,a friendship inference model named ITSIC is proposed based on the similarity of user interest tracks and joint user location *** utilizing MeanShift clustering algorithm,ITSIC clustered and filtered user check-ins and divided the dataset into interesting,abnormal,and noise *** interest trajectories were constructed from user interest check-in data,which allows ITSIC to work efficiently even for users without *** the same time,by application of clustering,the single-moment multi-interest trajectory was further proposed,which increased the richness of the meaning of the trajectory *** extensive experiments on two real online social network datasets show that ITSIC outperforms existing methods in terms of AUC score and time efficiency compared to existing methods.

关键词： Data privacy Social networking (online) Noise Clustering algorithms Prediction algorithms Inference algorithms Data models

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Capturing metal clusters at the strong-interaction region to reverse Ostwald ripening

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Science China Materials 2024年第4期67卷 1363-1364页

作者： Shuheng tian Ding Ma Beijing National Laboratory for Molecular Sciences New Cornerstone Science LaboratoryCollege of Chemistry and Molecular EngineeringPeking UniversityBeijing 100871China

High-temperature interactions induce sintering of metal nanoparticles(NPs) on heterogeneous catalyst surfaces, leading to reduced surface area and active site loss through Ostwald ripening [1]. This irreversible deactivation necessitates costly catalyst replacement, notably impacting metals like copper in hydrogenation and reforming reactions [2].

关键词： catalyst reforming irreversible

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Defect Engineering and Carbon Supporting to Achieve Ni‑Doped CoP_(3) with High Catalytic Activities for Overall Water Splitting

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Nano-Micro Letters 2024年第11期16卷 569-584页

作者： Daowei Zha Ruoxing Wang Shijun tian Zhong‑Jie Jiang Zejun Xu Chu Qin Xiaoning tian Zhongqing Jiang Department of Physics Zhejiang Sci-Tech UniversityHangzhou 310018People’s Republic of China Department of Materials and Chemical Engineering Ningbo University of TechnologyNingbo 315211People’s Republic of China Guangzhou Key Laboratory for Surface Chemistry of Energy Materials Guangdong Engineering and Technology Research Center for Surface Chemistry of Energy MaterialsCollege of Environment and EnergySouth China University of TechnologyGuangzhou 510006People’s Republic of China

This work reports the use of defect engineering and carbon supporting to achieve metal-doped phosphides with high activities and stabilities for the hydrogen evolution reaction(HER)and the oxygen evolution reaction(OER)in alkaline ***,the nitrogen-doped carbon nanofiber-supported Ni-doped CoP_(3) with rich P defects(Pv·)on the carbon cloth(p-NiCoP/NCFs@CC)is synthesized through a plasma-assisted phosphorization *** p-NiCoP/NCFs@CC is an efficient and stable catalyst for the HER and the *** only needs overpotentials of 107 and 306 mV to drive 100 mA cm^(-2) for the HER and the OER,*** catalytic activities are higher than those of other catalysts reported *** high activities of the p-NiCoP/NCFs@CC mainly arise from its peculiar structural *** density functional theory calculation indicates that the Pv·richness,the Ni doping,and the carbon supporting can optimize the adsorption of the H atoms at the catalyst surface and promote the strong electronic couplings between the carbon nanofiber-supported p-NiCoP with the surface oxide layer formed during the OER *** gives the p-NiCoP/NCFs@CC with the high activities for the HER and the *** used in alkaline water electrolyzers,the p-NiCoP/NCFs@CC shows the superior activity and excellent stability for overall water splitting.

关键词： Plasma Electrocatalysis Hydrogen evolution reaction Oxygen evolution reaction Water splitting

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Research on human gait sensing based on triboelectric nanogenerator

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Nanotechnology and Precision Engineering 2024年第2期7卷 32-40页

作者： Gang Yang Lifang Wang Jiayun tian School of Communication and Information Engineering Xi’an University of Posts and TelecommunicationsXi’an 710121China

To address the problem of frequent battery replacement for wearable sensors applied to fall detection among the elderly,a portable and lowcost triboelectric nanogenerator(TENG)-based self-powered sensor for human gait monitoring is *** main fabrication materials of the TENG are polytetrafluoroethylene(PTFE)film,aluminum(Al)foil,and polyimide(PI)film,where PTFE and Al are the friction layer materials and the PI film is used to improve the output *** the ability of TENGs to monitor changes in environmental conditions,a self-powered sensor based on the TENG is placed in an insole to collect gait *** a TENG does not require a power source to convert physical and mechanical signals into electrical signals,the electrical signals can be used as sensing signals to be analyzed by a computer to recognize daily human activities and fall *** results show that the accuracy of the TENG-based sensor for recognizing human gait is 97.2%,demonstrating superior sensing performance and providing valuable insights for future monitoring of fall events in the elderly population.

关键词： Triboelectric nanogenerator Sensor Gait monitoring

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In memoriam:Shizhu Wen(1932-2023)

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Friction 2024年第7期12卷 1341-1346页

作者： Jianbin LUO Yonggang MENG Yu tian State Key Laboratory of Tribology in Advanced Equipment Tsinghua UniversityBeijing 100084China

Professor Shizhu Wen,the winner of the 2015 Tribology Gold Medal,passed away due to illness on November 3,2023,at the age of *** was a professor of Tsinghua University,an academician of the Chinese Academy of Sciences,and the Honorary President of the Chinese Tribology Institute(CTI)from 1997 to *** Wen was born in 1932 in Jiangxi Province of China and graduated from Tsinghua University in 1955,where he was awarded the Outstanding Graduate Gold Medal and then remained as an assistant professor at the *** Wen was promoted to full professor in *** had undertaken tribology research at the Imperial College London in 1979 and *** 1985,he presided over the establishment of the State Key Laboratory of Tribology(SKLT)of Tsinghua University and served as the first director of the SKLT.

关键词： sided professor zhu

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TSC prediction and dynamic control of BOF steelmaking with state-of-the-art machine learning and deep learning methods

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Journal of Iron and Steel Research International 2024年第1期31卷 174-194页

作者： tian-yi Xie Cai-dong Zhang Quan-lin Zhou Zhi-qiang tian Shuai Liu Han-jie Guo Material Technology Research Institute Hesteel GroupShijiazhuang050023HebeiChina Tangsteel Company Hesteel GroupTangshan063611HebeiChina School of Artificial Intelligence Beijing Technology and Business UniversityBeijing100048China School of Metallurgical and Ecological Engineering University of Science and Technology BeijingBeijing100083China

Mathematical(data-driven)models based on state-of-the-art(SOTA)machine learning and deep learning models and data collected from 12,786 heats were established to predict the values of temperature,sample,and carbon(TSC)test,including temperature of molten steel(TSC-Temp),carbon content(TSC-C)and phosphorus content(TSC-P),which made prepa-ration for eliminating the TSC *** maximize the prediction accuracy of the proposed approach,various models with different inputs were implemented and compared,and the best models were applied to the production process of a Hesteel Group steelmaking plant in China in the *** number of tabular features(hot metal information,scrap,additives,blowing practices,and preset values)was expanded,and time series(off-gas profiles and blowing practice curves)that could reflect the entire steelmaking process were introduced as ***,the latest machine learning models(LightGBM,CatBoost,TabNet,and NODE)were used to make predictions with tabular features,and the best coefficient of determination R^(2)values obtained for TSC-P,TSC-C and TSC-Temp predictions were 0.435(LightGBM),0.857(Cat-Boost)and 0.678(LightGBM),respectively,which were higher than those of classic models(backpropagation and support vector machine).Then,making predictions was performed by using SOTA time series regression models(SCINet,DLinear,Informer,and MLSTM-FCN)with original time series,SOTA image regression models(NesT,CaiT,ResNeXt,and GoogLeNet)with resized time series,and the proposed Concatenate-Model and Parallel-Model with both tabular features and time *** optimization and comparisons,it was finally determined that the Concatenate-Model with MLSTM-FCN,SCINet and Informer as feature extractors performed the best,and its R^(2)values for predicting TSC-P,TSC-C and TSC-Temp reached 0.470,0.858 and 0.710,*** field test accuracies for TSC-P,TSC-C and TSC-Temp were 0.459,0.850 and 0.685,respectively.A related importance analysis was carri

关键词： BOF steelmaking In-blow prediction TSC test Machine learning Deep learning Field application

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Prediction of ball-on-plate friction and wear by ANN with data-driven optimization

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Friction 2024年第6期12卷 1235-1249页

作者： Alexander KOVALEV Yu tian Yonggang MENG State Key Laboratory of Tribology in Advanced Equipment Tsinghua UniversityBeijing 100084China

For training artificial neural network(ANN),big data either generated by machine or measured from experiments are used as input to"learn"the unspecified functions defining the *** experimental data are fed directly into the optimizer allowing training to be performed according to a predefined loss *** predict sliding friction and wear at mixed lubrication conditions,in this study a specific ANN structure was so designed that deep learning algorithms and data-driven optimization models can be *** ball-on-plate friction and wear data were analyzed using the specific training procedure to optimize the weights and biases incorporated into the neural layers of the ANN,and only two independent experimental data sets were used during the ANN optimization *** the training procedure,the ANN is capable to predict the contact and hydrodynamic pressure by adapting the output data according to the tribological condition implemented in the optimization algorithm.

关键词： machine learning deep learning artificial neural network mixed lubrication

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