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Nano Research 2024年第6期17卷 4994-5001页

作者： Xitong Ren Jiajie Sun Yusen Li Feng bai Key Laboratory for Special Functional Materials of Ministry of Education National and Local Joint Engineering Research Center for High-Efficiency Display and Lighting TechnologySchool of Materials Science and Engineeringand Collaborative Innovation Center of Nano Functional Materials and ApplicationsHenan UniversityKaifeng 475004China School of Physics and Electronics Henan UniversityKaifeng 475004China

The combination of donor-acceptor(D-A)structures presents a viable strategy for fabricating covalent organic frameworks(COFs)with exceptional photocatalytic ***,the selection of functional groups on donor or acceptor building blocks and their effect on the macroscopic properties of COFs are *** this study,we tactfully synthesized a pair of Py-DBT-COFs from the same pyrene(Py)donor and 4,7-diphenylbenzo[c][1,2,5]thiadiazole(DBT)acceptor cores with distinct primitive functional *** primitive functional groups of building units determine the photocatalytic properties of corresponding ***,Py-C-DBT-COF synthesized from Py-4CHO and DBT-2NH_(2)showcases a splendid H_(2)evolution rate as high as 21,377.7μmol/(g·h)(with 5 wt.%Pt)originating from better charge transfer capacity,which is significantly superior to that of Py-N-DBT-COF constructed from Py-4NH_(2)and *** distinct photocatalytic performances of the two COFs are demonstrated to originate from the different charge separation and transfer *** work supplies a new avenue for optimizing the photocatalytic performance of D-A COFs from the perspective of primitive functional group selections.

关键词： covalent organic frameworks functional group donor-acceptor photocatalysis

Surface roughness classification using light scattering matrix and deep learning

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Science China(Technological Sciences) 2024年第2期67卷 520-535页

作者： SUN Hao TAN Wei RUAN YiXiao bai Long XU JianFeng State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China Wuhan Digital Design and Manufacturing Innovation Center Co. LtdWuhan 430074China

High-quality optical components have been widely used in various applications;thus,extremely high beam quality is ***,surface roughness is a key indicator of the surface *** this study,the angular distribution of light scattering field intensity was obtained for surfaces having different roughness profiles based on the finite difference time domain(FDTD)method,and the results were compared with those obtained using the generalized Harvey-Shack(GHS)*** was shown that the FDTD approach can be used for an accurate simulation of the scattered field of a rough surface,and the superposition of results obtained from many surfaces that have the same roughness level was in good agreement with the result given by the analytic GHS model.A light scattering matrix(LSM)method was proposed based on the FDTD simulation results that could obtain rich surface roughness *** classification effect of LSM was compared with that of the single-incidence scattering distribution(SISD)based on a ResNet-50 deep learning *** classification accuracy of the model trained with the LSM dataset was obtained as 95.74%,which was 23.40%higher than that trained using the SISD ***,the effects of different noise types and filtering methods on the classification performance were analyzed,and the LSM was also shown to improve the robustness and generalizability of the trained surface roughness ***,the proposed LSM method has important implications for improving the data acquisition scheme of current light scattering measurement systems,and it also has the potential to be used for detection and characterization of surface defects of optical components.

关键词： surface roughness FDTD simulation GHS theory deep learning light scattering matrix

Voltage rise rate-related generalised probabilistic lifetime model of turn-to-turn insulation in inverter-fed motors

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High Voltage 2024年第1期9卷 46-55页

作者： Yan Yang Xueyang bai Yuxing Lei Kai Liu Guangning Wu School of Electrical Engineering Southwest Jiaotong UniversityChengduChina

The lifetime model of turn-to-turn insulation in inverter-fed motors is studied.A lifetime model has been built by considering the effect of inverter-generated high voltage rise rate(dv/dt up to 20 V/ns).This model is followed by the generalised probabilistic model,in which the lifetime is proportional to the nth power of the voltage rise ***,by investigating the effect of voltage rise rate on the partial discharge characteristics,it is found that the effect of voltage rise rate on the charge transport process in a voltage cycle is similar to that of the voltage *** enhanced partial discharge activity and induced charges are responsible for accelerated ageing and thus determine the final lifetime of turn-to-turn *** this case,the generalised probabilistic electric lifetime model is applicable to the voltage rise rate as well as the voltage amplitude.

关键词： lifetime inverter insulation

Sawtooth-enhanced bend sensor for gesture recognition

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Science China(Technological Sciences) 2024年第6期67卷 1727-1736页

作者： bai YanRu ZHANG ZiHang WANG HaoYu GUO Rui LI XiSheng School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing100083China School of Advanced Engineering University of Science and Technology BeijingBeijing100083China School of Precision Instrument and Opto-Electronics Engineering Tianjin UniversityTianjin300072China School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China

Gesture recognition has diverse application prospects in the field of human-computer ***,gesture recognition devices based on strain sensors have achieved remarkable results,among which liquid metal materials have considerable advantages due to their high tensile strength and *** improve the detection sensitivity of liquid metal strain sensors,a sawtooth-enhanced bending sensor is proposed in this *** with the results from previous studies,the bending sensor shows enhanced resistance *** addition,combined with machine learning algorithms,a gesture recognition glove based on the sawtooth-enhanced bending sensor is also fabricated in this study,and various gestures are accurately *** the fields of human-computer interaction,wearable sensing,and medical health,the sawtooth-enhanced bending sensor shows great potential and can have wide application prospects.

关键词： liquid metal bending sensor gesture recognition machine learning

Digitalizing river aquatic ecosystems

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Journal of Environmental Sciences 2024年第3期137卷 677-680页

作者： Yaohui bai Hui Lin Chenchen Wang Qiaojuan Wang Jiuhui Qu Key Laboratory of Drinking Water Science and Technology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China University of Chinese Academy of Sciences Beijing 100049China School of Environmental and Municipal Engineering Tianjin Chengjian UniversityTianjin 300384China Center for Water and Ecology Tsinghua UniversityBeijing 100084China

Traditional river health assessment relies on limited water quality indices and representative organism activity,but does not comprehensively obtain biotic and abiotic information of the ***,we propose a new approach to evaluate the ecological and health risks of river aquatic ***,detailed physicochemical and biological characterization of a river ecosystem can be obtained through pollutant determination(especially emerging pollutants)and DNA/RNA ***,supervised machine learning can be applied to perform classification analysis of characterization data and ascertain river ecosystem ecology and *** proposed methodology transforms river ecosystem health assessment and can be applied in river management.

关键词： Digitalizing River ecosystem health Emerging pollutants High throughput sequencing Machine learning

Social Robot Detection Method with Improved Graph Neural Networks

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Computers, Materials & Continua 2024年第2期78卷 1773-1795页

作者： Zhenhua Yu Liangxue bai Ou Ye Xuya Cong Institute of Systems Security and Control College of Computer Science and TechnologyXi’an University of Science and TechnologyXi’an710054China

Social robot accounts controlled by artificial intelligence or humans are active in social networks,bringing negative impacts to network security and social *** social robot detection methods based on graph neural networks suffer from the problem of many social network nodes and complex relationships,which makes it difficult to accurately describe the difference between the topological relations of nodes,resulting in low detection accuracy of social *** paper proposes a social robot detection method with the use of an improved neural ***,social relationship subgraphs are constructed by leveraging the user’s social network to disentangle intricate social relationships ***,a linear modulated graph attention residual network model is devised to extract the node and network topology features of the social relation subgraph,thereby generating comprehensive social relation subgraph features,and the feature-wise linear modulation module of the model can better learn the differences between the ***,user text content and behavioral gene sequences are extracted to construct social behavioral features combined with the social relationship subgraph ***,social robots can be more accurately identified by combining user behavioral and relationship *** carrying out experimental studies based on the publicly available datasets TwiBot-20 and Cresci-15,the suggested method’s detection accuracies can achieve 86.73%and 97.86%,*** with the existing mainstream approaches,the accuracy of the proposed method is 2.2%and 1.35%higher on the two *** results show that the method proposed in this paper can effectively detect social robots and maintain a healthy ecological environment of social networks.

关键词： Social robot detection social relationship subgraph graph attention network feature linear modulation behavioral gene sequences

From atomistic modeling to materials design:computation-driven material development in lithium-ion batteries

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Science China Chemistry 2024年第1期67卷 276-290页

作者： Xiangrong Li Xiang Chen Qiang bai Yifei Mo Yizhou Zhu Research Center for Industries of the Future and School of Engineering Westlake UniversityHangzhou 310030China Department of Chemical Engineering Tsinghua UniversityBeijing 100084China College of Materials Science and Engineering Taiyuan University of TechnologyTaiyuan 030024China Department of Materials Science and Engineering University of MarylandCollege Park 20742United States

As an advanced energy storage system,lithium-ion batteries play an essential role in modern *** their ubiquitous success,there is a great demand for continuous improvements of the battery performance,including higher energy density,lower safety risk,longer cycling life,and lower *** performance improvement requires the design and development of novel electrode and electrolyte materials that exhibit desirable properties and satisfy strict *** modeling can provide a unique perspective to fundamentally understand and rationally design battery *** this paper,we review a few recent successful examples of computation-driven discovery and design in electrode and electrolyte ***,we highlight how atomistic modeling can reveal the underlying mechanisms,predict the important properties,and guide the design and engineering of electrode and electrolyte *** have a conclusion with a discussion of the unique capability of atomistic modeling in battery material development and provide a perspective on future challenges and directions for computation-driven battery material developments.

关键词： materials design computation modeling batteries electrolyte electrode

Solvation strategies in various electrolytes for advanced zinc metal anode

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Journal of Energy Chemistry 2024年第7期94卷 740-757页

作者： Zhenxu Wang Lichong bai Hongguang Fan Yanpeng Wang Wei Liu School of Materials Science and Engineering Ocean University of ChinaQingdao 266100ShandongChina

Aqueous zinc-ion batteries(AZIBs),known for their high safety,low cost,and environmental friendliness,have a wide range of potential applications in large-scale energy storage ***,the notorious dendrite growth and severe side reactions on the anode have significantly hindered their further practical *** studies have shown that the solvation chemistry in the electrolyte is not only closely related to the barriers to the commercialization of AZIBs,but have also sparked a number of valuable ideas to address the challenges of ***,we systematically summarize and discuss the regulatory mechanisms of solvation chemistry in various types of electrolytes and the influence of the solvation environment on battery *** challenges and future directions for solvation strategies based on the electrolyte environment are proposed to improve their performance and expand their application in AZIBs.

关键词： Solvation strategy Electrolyte Aqueous zinc-ion batteries Zinc dendrite

Novel soft robotic finger model driven by electrohydrodynamic(EHD)pump

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2024年第7期25卷 596-604页

作者： Xuehang bai Yanhong PENG Dongze LI Zhuochao LIU Zebing MAO Department of Mechanical Automotive and Materials EngineeringFaculty of EngineeringUniversity of WindsorWindsorN9B 3P4Canada Department of Information and Communication Engineering Graduate School of EngineeringNagoya UniversityNagoya464-8601Japan Department of Intelligent Science and Technology College of Computer Science and TechnologyQingdao UniversityQingdao266071China Design and Research Institute of University of Science and Technology Beijing Co.Ltd. Beijing100083China Faculty of Engineering Yamaguchi UniversityYamaguchi755-8611Japan

1Introduction In the field of robotic-human interactions,soft robotics offers enhanced safety and adaptability.A major challenge in this area is the integration of soft actuators with pump systems,which often increases the system volume and *** study presents the development and testing of a robotic finger powered by electrohydrodynamic(EHD)*** leveraging the electric field-induced flow of dielectric fluids.

关键词： robotic complexity. pump

Reliable calculations of nuclear binding energies by the Gaussian process of machine learning

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Nuclear Science and Techniques 2024年第6期35卷 130-144页

作者： Zi-Yi Yuan Dong bai Zhen Wang Zhong-Zhou Ren School of Physics Science and Engineering Tongji UniversityShanghai 200092China College of Science Hohai UniversityNanjing 211100China Key Laboratory of Advanced Micro-Structure Materials Ministry of EducationShanghai 200092China

Reliable calculations of nuclear binding energies are crucial for advancing the research of nuclear physics. Machine learning provides an innovative approach to exploring complex physical problems. In this study, the nuclear binding energies are modeled directly using a machine-learning method called the Gaussian process. First, the binding energies for 2238 nuclei with Z > 20 and N > 20 are calculated using the Gaussian process in a physically motivated feature space, yielding an average deviation of 0.046 MeV and a standard deviation of 0.066 MeV. The results show the good learning ability of the Gaussian process in the studies of binding energies. Then, the predictive power of the Gaussian process is studied by calculating the binding energies for 108 nuclei newly included in AME2020. The theoretical results are in good agreement with the experimental data, reflecting the good predictive power of the Gaussian process. Moreover, the α-decay energies for 1169 nuclei with 50 ≤ Z ≤ 110 are derived from the theoretical binding energies calculated using the Gaussian process. The average deviation and the standard deviation are, respectively, 0.047 MeV and 0.070 MeV. Noticeably, the calculated α-decay energies for the two new isotopes ^ (204 )Ac(Huang et al. Phys Lett B 834, 137484(2022)) and ^ (207) Th(Yang et al. Phys Rev C 105, L051302(2022)) agree well with the latest experimental data. These results demonstrate that the Gaussian process is reliable for the calculations of nuclear binding energies. Finally, the α-decay properties of some unknown actinide nuclei are predicted using the Gaussian process. The predicted results can be useful guides for future research on binding energies and α-decay properties.

关键词： Nuclear binding energies decay Machine learning Gaussian process