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Laser Wire Additive Manufacturing of Ti-6Al-4V Alloy and Its Machine Learning Study for Parameters Optimization(Invited)

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中国激光 2024年第4期51卷 182-198页

作者： Wu Junyi zhang Bo wang Weihua Li Weipeng Yao Xiyu wang dawei Xing Wei Yan Ming Department of Materials Science and Engineering Southern University of Science and TechnologyShenzhen 518055GuangdongChina Songshan Lake Materials Laboratory Dongguan 523830GuangdongChina Institute of Physics Chinese Academy of SciencesBeijing 100190China Jiaxing Research Institute Southern University of Science and TechnologyShenzhen 518055GuangdongChina High Performance Computing Department National Supercomputing CenterShenzhen 518055GuangdongChina

Ti-6Al-4V is a benchmark Ti alloy. Laser wire additive manufacturing(LWAM) offers advanced manufacturing capability to the alloy for applications possibly including exploration of outer space. As a typical multiple-variable process, LWAM is complex, which, however, can be analyzed, predicated or even optimized by artificial intelligence(AI) methods such as machine learning(ML). In this study, printing parameters of the Ti-6Al-4V is firstly optimized using single-track-single-layer experiments, and then single-track-multiple-layer samples are printed, whose properties in terms of hardness and compressive strength are analyzed subsequently by both experiments and ML. The two ML approaches, artificial neural network(ANN) and support vector machine(SVM), are employed to predict the experimental results, whose coefficients of determination R2 show good values. Further optimized properties are realized by adopting genetic algorithm(GA) and simulated annealing(SA) approaches, which contribute to high mechanical properties achieved, for instance, an engineering compressive strength of about 1694 MPa. The results here indicate that important mechanical properties of the LWAM-prepared Ti alloys can be well predicted and enhanced using suitable ML approaches.

关键词： artificial printing additive

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Comprehensive Relation Modelling for Image Paragraph Generation

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Machine Intelligence Research 2024年第2期21卷 369-382页

作者： Xianglu Zhu zhang zhang Wei wang Zilei wang Automation Department University of Science and Technology of ChinaHefei 230027China Center for Research on Intelligent Perception and Computing National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100864China

Image paragraph generation aims to generate a long description composed of multiple sentences,which is different from traditional image captioning containing only one *** of previous methods are dedicated to extracting rich features from image regions,and ignore modelling the visual *** this paper,we propose a novel method to generate a paragraph by modelling visual relationships ***,we parse an image into a scene graph,where each node represents a specific object and each edge denotes the relationship between two ***,we enrich the object features by implicitly encoding visual relationships through a graph convolutional network(GCN).We further explore high-order relations between different relation features using another graph convolutional *** addition,we obtain the linguistic features by projecting the predicted object labels and their relationships into a semantic embedding *** these features,we present an attention-based topic generation network to select relevant features and produce a set of topic vectors,which are then utilized to generate multiple *** evaluate the proposed method on the Stanford image-paragraph dataset which is currently the only available dataset for image paragraph generation,and our method achieves competitive performance in comparison with other state-of-the-art(SOTA)methods.

关键词： Image paragraph generation visual relationship scene graph graph convolutional network(GCN) long short-term memory

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False Negative Sample Detection for Graph Contrastive Learning

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Tsinghua Science and Technology 2024年第2期29卷 529-542页

作者： Binbin zhang Li wang College of Data Science Taiyuan University of TechnologyJinzhong 030600China

Recently,self-supervised learning has shown great potential in Graph Neural Networks (GNNs) through contrastive learning,which aims to learn discriminative features for each node without label information. The key to graph contrastive learning is data augmentation. The anchor node regards its augmented samples as positive samples,and the rest of the samples are regarded as negative samples,some of which may be positive samples. We call these mislabeled samples as “false negative” samples,which will seriously affect the final learning effect. Since such semantically similar samples are ubiquitous in the graph,the problem of false negative samples is very significant. To address this issue,the paper proposes a novel model,False negative sample Detection for Graph Contrastive Learning (FD4GCL),which uses attribute and structure-aware to detect false negative samples. Experimental results on seven datasets show that FD4GCL outperforms the state-of-the-art baselines and even exceeds several supervised methods.

关键词： graph representation learning contrastive learning false negative sample detection

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Accelerated water harvesting from vapor via a bio-inspired hydrogel pattern

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National Science Review 2024年第3期11卷 48-49页

作者： Lianbin zhang Peng wang State Key Laboratory of Material Processing and Die&Mould Technology Key Laboratory of Materials Chemistry for Energy Conversion and Storage of Ministry of Education School of Chemistry and Chemical Engineering Huazhong University of Science and Technology(HUST) School of Environmental Science and Engineering Sun Yat-sen University

Water and energy sustainability are integral parts of resource sustainability of the world. Due to water molecules' superior capability of serving as both hydrogenbond donor and acceptor, phase change of water, especially between liquid and vapor, underpins global water cycles,facilitates energy transformation and transfer, and thus helps shape the unique local weather and global climate patterns.

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Value iteration algorithm for continuous-time linear quadratic stochastic optimal control problems

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Science China(Information Sciences) 2024年第2期67卷 170-180页

作者： Guangchen wang Heng zhang School of Control Science and Engineering Shandong University

In this study, we investigate a continuous-time infinite-horizon linear quadratic stochastic optimal control problem with multiplicative noise in control and state variables. Using the techniques of stochastic stability, exact observability, and stochastic approximation, a value iteration algorithm is developed to solve the corresponding generalized algebraic Riccati equation. Unlike the existing policy iteration algorithm, this algorithm does not rely on an initial stabilizing control. Further, this algorithm can also be used to compute policy evaluation steps that arise in the policy iteration algorithm. Herein, a simulation example is provided to validate the obtained results.

关键词： stochastic systems optimal control linear quadratic stochastic problem generalized algebraic Riccati equation value iteration algorithm

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Time-sensitive prediction of NO_(2) concentration in China using an ensemble machine learning model from multi-source data

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Journal of Environmental Sciences 2024年第3期137卷 30-40页

作者： Chenliang Tao Man Jia Guoqiang wang Yuqiang zhang Qingzhu zhang Xianfeng wang Qiao wang Wenxing wang Big Data Research Center for Ecology and Environment Environment Research InstituteShandong UniversityQingdao 266237China Shandong Provincial Eco-environment Monitoring Center Jinan 250101China

Nitrogen dioxide(NO_(2))poses a critical potential risk to environmental quality and public health.A reliable machine learning(ML)forecasting framework will be useful to provide valuable information to support government *** on the data from1609 air quality monitors across China from 2014-2020,this study designed an ensemble ML model by integrating multiple types of spatial-temporal variables and three sub-models for time-sensitive prediction over a wide *** ensemble ML model incorporates a residual connection to the gated recurrent unit(GRU)network and adopts the advantage of Transformer,extreme gradient boosting(XGBoost)and GRU with residual connection network,resulting in a 4.1%±1.0%lower root mean square error over XGBoost for the test *** ensemble model shows great prediction performance,with coefficient of determination of 0.91,0.86,and 0.77 for 1-hr,3-hr,and 24-hr averages for the test results,*** particular,this model has achieved excellent performance with low spatial uncertainty in Central,East,and North China,the major site-dense *** the interpretability analysis based on the Shapley value for different temporal resolutions,we found that the contribution of atmospheric chemical processes is more important for hourly predictions compared with the daily scale predictions,while the impact of meteorological conditions would be ever-prominent for the *** with existing models for different spatiotemporal scales,the present model can be implemented at any air quality monitoring station across China to facilitate achieving rapid and dependable forecast of NO_(2),which will help developing effective control policies.

关键词： Air quality prediction Deep learning Ensemble method Nitrogen dioxide Spatiotemporal covariates

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Research on Fiber Optic Surface Plasmon R ***:A Review

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Photonic Sensors 2024年第2期14卷 1-30页

作者： Qi wang Dianyun zhang Yizhuo QIAN Xiangyu YIN Lei wang Shushuai zhang Yuyang wang State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China College of Information Science and Engineering Northeastern UniversiyShenyang 110819China Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Qinhuangdao 066004China State Key Laboratory of Chemo/Biosensing and Chemometrics Hunan UniversityChangsha 410082China

Due to the benefits of the high sensitivity,real-time response,no labeling requirement,and good selectivity,fiber optic sensors based on surface plasmon resonance(SPR)have gained popularity in biochemical sensing in recent *** current research on such sensors is hot in enhancing sensitivity,improving detection accuracy,and achieving the detection of biochemical *** goal of this work is to present a thorough overview of recent developments in the optical fiber SPR biosensor ***,it explores the basic principles and sensing structures of optical fiber SPR biosensors,focusing on four ***,this paper introduces three fiber optic surface plasmon biosensors:SPR,localized surface plasmon resonance(LSPR),and long-range surface plasmon resonance(LRSPR).Each concept is explained from the perspective of the basic principles of fiber optic SPR ***,a classification of fiber optic SPR biosensors in health monitoring,food safety,environmental monitoring,marine detection,and other applications is introduced and ***,this paper summarizes the current research directions of SPR ***,it provides a prospective outlook on how fiber optic SPR sensors will develop in the future.

关键词： Surface plasmon resonance biosensors optical fiber sensors sensitivity

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Boosting Li-ion storage kinetics via constructing layered TiO_(2) anode

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Particuology 2024年第10期93卷 22-29页

作者： Jiyue Hou Fei wang Enfeng zhang Ying wang Peng Dong Yunxiao wang Yiyong zhang Xue Li Yingjie zhang National and Local Joint Engineering Research Center of Lithium-ion Batteries and Materials Preparation Technology Faculty of Metallurgical and Energy EngineeringKunming University of Science and TechnologyKunming650093China College of Electrical Information Engineering Panzhihua UniversityPanzhihua617000China University Wollongong Australian Inst Innovat MatInst Superconducting&Elect MatInnovat Campus Squires WayWollongongNSW2500Australia

Due to the typical intercalation-deintercalation mechanism,TiO_(2) holds great promise as a sustainable anode for next-generation lithium-ion batteries(LIBs).However,commercial TiO_(2)(C–TiO_(2))is granular and shows slow ionic conductivity,which greatly hinders its development due to sluggish kinetics,leading to low reversible capacity and inferior rate *** this study,a two-dimensional layered TiO_(2)(L-TiO_(2))anode is prepared via a one-step calcination process,which can effectively shorten the lithium ions diffusion path and improve its lithium ions *** elucidated the enhanced electrochemical performance of L-TiO_(2) as an anode in LIBs through pseudocapacitive acceleration of lithium ions intercalation and deintercalation using various characterization techniques,including different scan rate cyclic voltammetry tests,in situ electrochemical impedance spectroscopy,in situ Raman spectroscopy,and in situ X-ray *** comparison to C–TiO_(2) material,L-TiO_(2) material showcases remarkable electrochemical performance,achieving a capacity of 166 mAh/g after 100 cycles at 0.1 ***,the lithium-ion diffusion coefficient calculated for the L-TiO_(2) is two orders of magnitude greater,underscoring its potential as a negative electrode material for LIBs.

关键词： Lithium-ionbatteries Anode MXene Layered TiO_(2)

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Diatomic Pd catalyst with conjugated backbone for synergistic electrochemical CO_(2)reduction

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Nano Research 2024年第6期17卷 4850-4855页

作者： Wenxuan zhang Mengran zhang Hongjuan wang Wen zhang Min zhang MOE International Joint Laboratory of Materials Microstructure Institute for New Energy Materials and Low Carbon TechnologiesSchool of Materials Science and EngineeringTianjin University of TechnologyTianjin 300384China Tianjin Key Laboratory of Organic Solar Cells and Photochemical Conversion School of Chemistry and Chemical EngineeringTianjin University of TechnologyTianjin 300384China

Double-site catalysts have attracted widespread attention in the field of electrocatalysis due to their high metal loading,adjustable active centres,and electronic valence ***,the development of bimetallic sites catalysts that coordinate with definite atoms is still in the exploratory ***,we designed and synthesized a bimetallic palladium complex(BPB-Pd_(2))with conjugated *** supported BPB-Pd_(2)was applied to electrochemical CO_(2)reduction reaction(CO_(2)RR)for the first *** as-obtained BPB-Pd_(2)gives an exceptional Faradaic efficiency of CO(FECO)of 94.4%at−0.80 V *** hydrogen electrode(RHE),which is significantly superior to monoatomic palladium catalyst(BPB-Pd1).The density functional theory(DFT)calculations revealed that the essential reason for the outstanding activity of BPB-Pd_(2)toward CO_(2)RR was that the electronic effect between diatomic palladium reduces the free energy change for CO_(2)RR ***,BPB-Pd_(2)exhibits moderate free energy change to form COOH*intermediate,which was beneficial for the generation of CO in CO_(2)RR.

关键词： synthesis electrocatalysis CO_(2)reduction bimetallic palladium complex synergistic catalysis

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Electrical control of excitonic oscillator strength and spatial distribution in a monolayer semiconductor

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Nano Research 2024年第9期17卷 8424-8430页

作者： Yanming wang Junrong zhang Tianhua Ren Meng Xia Long Fang Xiangyi wang Xingwang zhang Kai zhang Junyong wang School of Nano-Tech and Nano-Bionics University of Science and Technology of ChinaHefei 230026China CAS Key Laboratory of Nanophotonic Materials and Devices&Key Laboratory of Nanodevices and Applications i-LabSuzhou Institute of Nano-Tech and Nano-Bionics(SINANO)Chinese Academy of SciencesSuzhou 215123China Institute of Applied Physics and Materials Engineering University of MacaoTaipaMacao 999078China College of New Energy Inner Mongolia University of TechnologyHohhot 010051China

Electrical modulation of luminescence is significant to modern light-emitting *** transition metal dichalcogenides are emerging direct-bandgap luminescent materials with unique excitonic properties,and the multiple exciton complexes provide new opportunities to modulate the property of luminescence in atomically thin ***,we report an electrical control of exciton emission in the oscillator strength and spatial distribution of excitons in a monolayer *** modulation of excitonic emission intensity with a degree of modulation of~92%has been demonstrated by an electric field at room *** spatial carrier redistribution tuned by a lateral electric field results in distinct excitonic emission patterns by *** modulation approach to exciton oscillator strength and distribution provides an efficient way to investigate the exciton diffusion dynamics and to construct electrically tunable optoelectronic devices.

关键词： monolayer semiconductor exciton electrical modulation spatial distribution

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