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Surface roughness classification using light scattering matrix and deep learning

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 required.Moreover,surface roughness is a key indicator of the surface quality.In 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)theory.It 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 information.The classification effect of LSM was compared with that of the single-incidence scattering distribution(SISD)based on a ResNet-50 deep learning network.The 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 dataset.Moreover,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 classifier.Overall,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

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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 rate.Moreover,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 amplitude.The enhanced partial discharge activity and induced charges are responsible for accelerated ageing and thus determine the final lifetime of turn-to-turn insulation.In 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

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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 Beijing School of Advanced Engineering University of Science and Technology Beijing School of Precision Instrument and Opto-Electronics Engineering Tianjin University School of Computer and Communication Engineering University of Science and Technology Beijing

Gesture recognition has diverse application prospects in the field of human-computer interaction. Recently, 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 conductivity. To improve the detection sensitivity of liquid metal strain sensors,a sawtooth-enhanced bending sensor is proposed in this study. Compared with the results from previous studies, the bending sensor shows enhanced resistance variation. In 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 identified. In 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

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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 life.Existing 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 robots.This paper proposes a social robot detection method with the use of an improved neural network.First,social relationship subgraphs are constructed by leveraging the user’s social network to disentangle intricate social relationships effectively.Then,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 nodes.Next,user text content and behavioral gene sequences are extracted to construct social behavioral features combined with the social relationship subgraph features.Finally,social robots can be more accurately identified by combining user behavioral and relationship features.By 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%,respectively.Compared with the existing mainstream approaches,the accuracy of the proposed method is 2.2%and 1.35%higher on the two datasets.The 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

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Effects of operating conditions on iron(hydr)oxides evolution and ciprofloxacin degradation in potassium ferrate-ozone stepwise oxidation system

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Journal of Environmental Sciences 2024年第1期135卷 367-378页

作者： Xiaochen Li Yifan Wang Ning Wang Mei Li Maomao bai Jingtao Xu Hongbo Wang School of Municipal and Environmental Engineering Shandong Jianzhu UniversityJinan 250101China Resources and Environment Innovation Institute Shandong Jianzhu UniversityJinan 250101China

In this study,a stepwise oxidation system of potassium ferrate(K_(2)FeO_(4))combined with ozone(O+3)was used to degrade ciprofloxacin(CIP).The effects of pH and pre-oxidation time of K_(2)FeO_(4) on the evolution of K_(2)FeO_(4) reduction products(iron(hydr)oxides)and CIP degradation were investigated.It was found that in addition to its own oxidation capacity,K_(2)FeO_(4) can also influence the treatment effect of CIP by changing the catalyst content.The presence of iron(hydr)oxides effectively enhanced the mineralization rate of CIP by catalyzing ozonation.The pH value can influence the content and types of the components with catalytic ozonation effect in iron(hydr)oxides.The K_(2)FeO_(4) pre-oxidation stage can produce more iron(hydr)oxides with catalytic components for subsequent ozonation,but the evolution of iron(hydr)oxides components was influenced by O_(3) treatment.It can also avoid the waste of oxidation capacity owing to the oxidation of iron(hydr)oxides by O_(3) and free radicals.The intermediate degradation products were identified by Fourier transform ion cyclotron resonance mass spectrometry(FT-ICR-MS).Besides,the degradation pathways were proposed.Among the degradation products of CIP,the product with broken quinolone ring structure only appeared in the stepwise oxidation system.

关键词： Potassium ferrate reduction products Catalytic ozonation Ciprofloxacin Potassium ferrate pre-oxidation time

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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 systems.However,the notorious dendrite growth and severe side reactions on the anode have significantly hindered their further practical development.Recent 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 AZIBs.Therefore,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 performance.The 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

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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 technologies.Despite 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 cost.Such performance improvement requires the design and development of novel electrode and electrolyte materials that exhibit desirable properties and satisfy strict requirements.Atomistic modeling can provide a unique perspective to fundamentally understand and rationally design battery materials.In this paper,we review a few recent successful examples of computation-driven discovery and design in electrode and electrolyte materials.Particularly,we highlight how atomistic modeling can reveal the underlying mechanisms,predict the important properties,and guide the design and engineering of electrode and electrolyte materials.We 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

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Heat distribution model under hydrogen-rich low-carbon conditions in blast furnace

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Journal of Iron and Steel Research(International) 2024年第3期31卷 584-594页

作者： Gang Wang Jun Xu Kun He Zhong-ping Zou Hao bai School of Metallurgy and Ecological Engineering University of Science and Technology BeijingBeijing 100083China CISDI Low-Carbon Blast Furnace Research Office MCC Low-Carbon Technology Research InstituteChongqing 401122China

Low carbon development of blast furnaces is one of the key technological directions in the current development of ironmaking.Owing to the differences in the physical and chemical properties of hydrogen and carbon,hydrogen-rich media entering a blast furnace will change the heat distribution,thus affecting the stability of production.Accordingly,a heat distribution model was proposed to study the temperature distribution in a blast furnace,simultaneously considering gas-solid heat exchange,slag and iron melting,and chemical reactions.The model was used to analyze the temperature distribution of a 2300 m^(3) blast furnace and was verified via comparison with actual production data.Subsequently,the effects of the injection rate of hydrogen-rich media,H2 concentration,and oxygen enrichment rate of the blast on the temperature distribution were investigated.Results indicated that the increase in the injection rate of the hydrogen-rich media decreased the amount of direct reduction and led to an increase in the furnace temperature.Furthermore,an increase in the oxygen enrichment rate led to a decrease in the furnace temperature,but could reduce the solid fuel ratio,while the change in H2 concentration had less effect on the temperature distribution.The combination of hydrogen-rich media injection and the increase in the oxygen enrichment rate would help to adjust the temperature distribution to the same level as the conventional blast furnace conditions.

关键词： Heat distribution Blast furnace Low-carbon condition Hydrogen enrichment Calculation model

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Recent Advances in Asymmetric Structural Composites for Excellent Electromagnetic Interference Shielding: A Review

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Chinese Journal of Polymer Science 2024年第6期42卷 693-710页

作者： Ying Zhou bai Xue Lan Xie Chang-Mei Wu Qiang Zheng Department of Polymer Materials and Engineering College of Materials and Metallurgy Guizhou University National Engineering Research Center for Compounding and Modification of Polymer Materials National and Local Joint Engineering Research Center for Functional Polymer Membrane Materials and Membrane Processes State Key Laboratory of Public Big Data Guizhou University Department of Polymer Science and Engineering Zhejiang University

Since electromagnetic pollution is detrimental to human health and the environment, numerous efforts have been successively made to achieve excellent electromagnetic interference shielding effectiveness(EMI SE) via designing the hierarchical structures for electromagnetic interference(EMI) shielding polymer composites. Among the plentiful structures, the asymmetric structures are currently a hot spot, principally categorizing into multi-layered, porous, fibrous, and segregated asymmetric structures, which endows the high EMI shielding performance for polymer composites incorporated with magnetic, conductive, and/or dielectric micro/nano-fillers, due to the “absorption-reflection-reabsorption” shielding mechanism. Therefore, this review provides the retrospection and summary of the efforts with respect to abundant asymmetric structures and multifunctional micro/nano-fillers for enhancing EMI shielding properties, which is conducive to the booming development of polymeric EMI shielding materials for the promising prospect in modern electronics and 5-generation(5G) technology.

关键词： Asymmetric structure Microano functional filler Polymer composite Electromagnetic interference shielding

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Multi-electron reaction and fast Al ion diffusion of δ-MnO_(2) cathode materials in rechargeable aluminum batteries via first-principle calculations

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Chinese Chemical Letters 2024年第4期35卷 248-254页

作者： Lumin Zheng Ying bai Chuan Wu School of Materials Science&Engineering Beijing Institute of TechnologyBeijing 100081China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing 314019China

Rechargeable aluminum batteries with multi-electron reaction have a high theoretical capacity for next generation of energy storage devices. However, the diffusion mechanism and intrinsic property of Al insertion into MnO_(2) are not clear. Hence, based on the first-principles calculations, key influencing factors of slow Al-ions diffusion are narrow pathways, unstable Al-O bonds and Mn^(3+) type polaron have been identified by investigating four types of δ-MnO_(2)(O3, O'3, P2 and T1). Although Al insert into δ-MnO_(2) leads to a decrease in the spacing of the Mn-Mn layer, P2 type MnO_(2) keeps the long(spacious pathways)and stable(2.007–2.030 A) Al-O bonds resulting in the lower energy barrier of Al diffusion of 0.56 e V. By eliminated the influence of Mn^(3+)(low concentration of Al insertion), the energy barrier of Al migration achieves 0.19 e V in P2 type, confirming the obviously effect of Mn^(3+) polaron. On the contrary, although the T1 type MnO_(2) has the sluggish of Al-ions diffusion, the larger interlayer spacing of Mn-Mn layer,causing by H_(2)O could assist Al-ions diffusion. Furthermore, it is worth to notice that the multilayer δ-MnO_(2) achieves multi-electron reaction of 3|e|. Considering the requirement of high energy density, the average voltage of P2(1.76 V) is not an obstacle for application as cathode in RABs. These discover suggest that layered MnO_(2) should keep more P2-type structure in the synthesis of materials and increase the interlayer spacing of Mn-Mn layer for providing technical support of RABs in large-scale energy storage.

关键词： Rechargeable aluminum batteries δ-MnO_(2) First-principles calculations Multi-electron reaction Diffusion mechanism

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