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Journal of Magnesium and Alloys 2024年第1期12卷 361-383页

作者： Chao Xie Shijie bai Xiao Liu Minghua Zhang Jianke Du The Faculty of Mechanical Engineering and Mechanics Ningbo UniversityNingbo 315211P.R.China Key Laboratory of High Temperature Wear Resistant Materials Preparation Technology of Hunan Province Hunan University of Science and TechnologyXiangtan 411201P.R.China

In this study,a phase-field scheme that rigorously obeys conservation laws and irreversible thermodynamics is developed for modeling stress-corrosion coupled damage(SCCD).The coupling constitutive relationships of the deformation,phase-field damage,mass transfer,and electrostatic field are derived from the entropy inequality.The SCCD localization induced by secondary phases in Mg is numerically simulated using the implicit iterative algorithm of the self-defined finite elements.The quantitative evaluation of the SCCD of a C-ring is in good agreement with the experimental results.To capture the damage localization,a micro-galvanic corrosion domain is defined,and the buffering effect on charge migration is explored.Three cases are investigated to reveal the effect of localization on corrosion acceleration and provide guidance for the design for resistance to SCCD at the crystal scale.

关键词： Phase field Mg alloys Stress-corrosion coupled damage Damage localization Finite element method

Prospects of the Multi-channel Photometric Survey Telescope in the Cosmological Application of Type Ia Supernovae

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Research in Astronomy and Astrophysics 2024年第4期24卷 183-191页

作者： Zhenyu Wang Jujia Zhang Xinzhong Er Jinming bai Yunnan Observatories Chinese Academy of SciencesKunming 650216China University of Chinese Academy of Sciences Beijing 100049China Key Laboratory for the Structure and Evolution of Celestial Objects Chinese Academy of SciencesKunming 650216China International Centre of Supernovae Yunnan Key LaboratoryKunming 650216China South-Western Institute for Astronomy Research Yunnan UniversityKunming 650500China

The Multi-channel Photometric Survey Telescope(Mephisto)is a real-time,three-color photometric system designed to capture the color evolution of stars and transients accurately.This telescope system can be crucial in cosmological distance measurements of low-redshift(low-z,z■0.1)Type Ia supernovae(SNe Ia).To optimize the capabilities of this instrument,we perform a comprehensive simulation study before its official operation is scheduled to start.By considering the impact of atmospheric extinction,weather conditions,and the lunar phase at the observing site involving the instrumental features,we simulate light curves of SNe Ia obtained by Mephisto.The best strategy in the case of SN Ia cosmology is to take the image at an exposure time of 130 s with a cadence of 3 days.In this condition,Mephisto can obtain hundreds of high-quality SNe Ia to achieve a distance measurement better than 4.5%.Given the on-time spectral classification and monitoring of the Lijiang 2.4 m Telescope at the same observatory,Mephisto,in the whole operation,can significantly enrich the well-calibrated sample of supernovae at low-z and improve the calibration accuracy of high-z SNe Ia.

关键词： (stars:)supernovae:general (cosmology:)cosmological parameters telescopes

Hypoxic and temporal variation in the endocrine disrupting toxicity of perfluorobutanesulfonate in marine medaka(Oryzias melastigma)

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Journal of Environmental Sciences 2024年第2期136卷 279-291页

作者： baili Sun Jing Li Yachen bai Xiangzhen Zhou Paul K.S.Lam Lianguo Chen State Key Laboratory of Freshwater Ecology and Biotechnology Institute of HydrobiologyChinese Academy of SciencesWuhan 430072China University of Chinese Academy of Sciences Beijing 100049China Office of the President Hong Kong Metropolitan University30 Good Shepherd StreetKowloonHong Kong SARChina

Perfluorobutanesulfonate(PFBS)is an emerging pollutant capable of potently disrupting the sex and thyroid endocrine systems of teleosts.However,the hypoxic and temporal variation in PFBS endocrine disrupting toxicity remain largely unknown.In the present study,adult marine medaka were exposed to environmentally realistic concentrations of PFBS(0 and 10μg/L)under normoxia or hypoxia conditions for 7 days,aiming to explore the interactive behavior between PFBS and hypoxia.In addition,PFBS singular exposure was extended till 21days under normoxia to elucidate the time-course progression in PFBS toxicity.The results showed that hypoxia inhibited the growth and caused the suspension of egg spawn regardless of PFBS exposure.With regard to the sex endocrine system,7-day PFBS exposure led to an acute stimulation of transcriptional profiles in females,which,subsequently,recovered after the 21-day exposure.The potency of hypoxia to disturb the sex hormones was much stronger than PFBS.A remarkable increase in estradiol concentration was noted in medaka blood after hypoxia exposure.Changes in sex endocrinology of coexposed fish were largely determined by hypoxia,which drove the formation of an estrogenic environment.PFBS further enhanced the endocrine disrupting effects of hypoxia.However,the hepatic synthesis of vitellogenin and choriogenin,two commonly used sensitive biomarkers of estrogenic activity,failed to initiate in response to the estrogen stimulus.Compared to sex endocrine system,disturbances in thyroidal axis by PFBS or hypoxia were relatively mild.Overall,the present findings will advance our toxicological understanding about PFBS pollutant under the interference of hypoxia.

关键词： Perfluorobutanesulfonate(PFBS) Aquatic hypoxia Temporal toxicity Combined exposure Endocrine disruption Marine medaka

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 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

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

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 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

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

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

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

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