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Enhanced memristor performance via coupling effect of oxygen vacancy and ferroelectric polarization

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Journal of Materials Science & Technology 2024年第4期171卷 139-146页

作者： Zhi yun Yue Zhi dong Zhang Zhan Jie Wang Shenyang National Laboratory for Materials Science Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China School of Materials Science and Engineering University of Science and Technology of ChinaShenyang 110016China School of Materials Science and Engineering Shenyang University of TechnologyShenyang 110870China

As a new type of nonvolatile memory,the resistive memristor has broad application prospects in in-formation storage and neural computing based on its excellent resistive switching(RS)*** present,it is still a great challenge to improve both ferroelectric polarization and leakage current to achieve a high RS on/offratio of ferroelectric ***,epitaxial Pb(Zr_(0.40)Ti_(0.60))O_(3)(PZT)thin films with low content Ca doping were deposited on the Nb:SrTiO_(3)substrate to prepare PCZT/NSTO het-erostructures and their RS behaviors were *** research findings show that compared with pure PZT film,the ferroelectric polarization of 1-mol%-Ca-doped PZT film is slightly improved,while the leak-age current is increased by three orders of ***,the RS on/offratio reaches 2.5×10^(5),about three orders of magnitude higher than pure PZT *** theoretical analysis reveals that the RS behavior of PCZT/NSTO heterostructures is controlled by the PCZT/NSTO interfacial barrier and the space charge-limited current *** results demonstrate that the ferroelectricity and electricity of ferroelectric thin films can be improved simultaneously by doping low-content Ca ions to increase the RS performance,which provides a good reference for the development of high-performance ferroelectric memristor devices.

关键词： Ferroelectric memristor Ca-doped PZT Ferroelectric polarization Oxygen vacancies Resistive switching

Dynamic Event-Triggered Quadratic Nonfragile Filtering for Non-Gaussian Systems:Tackling Multiplicative Noises and Missing Measurements

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1127-1138页

作者： Shaoying Wang Zidong Wang Hongli dong yun Chen Guoping Lu College of Science Shandong University of AeronauticsBinzhou 256603China College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590 Department of Computer Science Brunel University LondonUxbridge UB83PHUK Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum UniversityDaqing 163318China School of Automation Hangzhou Dianzi UniversityHangzhou 310018China School of Electrical Engineering Nantong UniversityNantong 226019China

This paper focuses on the quadratic nonfragile filtering problem for linear non-Gaussian systems under multiplicative noises,multiple missing measurements as well as the dynamic event-triggered transmission *** multiple missing measurements are characterized through random variables that obey some given probability distributions,and thresholds of the dynamic event-triggered scheme can be adjusted dynamically via an auxiliary *** attention is concentrated on designing a dynamic event-triggered quadratic nonfragile filter in the well-known minimum-variance *** this end,the original system is first augmented by stacking its state/measurement vectors together with second-order Kronecker powers,thus the original design issue is reformulated as that of the augmented ***,we analyze statistical properties of augmented noises as well as high-order moments of certain random *** the aid of two well-defined matrix difference equations,we not only obtain upper bounds on filtering error covariances,but also minimize those bounds via carefully designing gain ***,an example is presented to explain the effectiveness of this newly established quadratic filtering algorithm.

关键词： filtering quadratic bounds

Prediction of dissolved gas content in transformer oil based on multi-information fusion

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High Voltage 2024年第3期9卷 685-699页

作者： Tongliang Yang yun Fang Chengming Zhang Chao tang dong Hu College of Engineering and Technology Southwest UniversityChongqingChina International R&D Center for New Technologies of Smart Grid and Equipment Southwest UniversityChongqingChina

In order to accurately predict the content and variation trend of dissolved gas in trans-former oil and guide the condition maintenance of power transformers,a combined prediction model based on multi-information fusion is proposed and its effectiveness is *** of all,based on the possibility of pathological and missing historical sample data,a detection and filling method based on variable weight combination samples is ***,the authors propose two *** at the non-linear and non-stationary characteristics of gas content,a univariate decomposition prediction mode HBA-VMD-TCN which based on the Honey Badger algorithm,variational mode decomposition and time convolutional network(TCN)is *** the multi-variate Informer prediction model is established for gas content affected by multiple ***,the cross-entropy theory is used to determine the weight coefficients of the two models,and the multi-information fusion combined prediction model is ***,on the basis of the above,a method to determine the time step and the position information of the transition point adaptively in the process of prediction is proposed to further improve the prediction *** results show that,through a series of simulation experiments of model comparison and transformer anomaly prediction,the accuracy and effectiveness of the combined prediction model are verified.

关键词： content prediction dissolved

Deep decalcification of factory-provided freezing acidolysis solution to achieveα-high-strength gypsum

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Chinese Journal of Chemical Engineering 2024年第5期69卷 143-151页

作者： Wencai Ye Yulu Li Yonggang dong Lin Yang yun Yi Jianxin Cao School of Chemistry and Chemical Engineering Guizhou UniversityGuiyang 550025China Engineering Research Center of Efficient Utilization for Industrial Waste Guizhou UniversityGuiyang 550025China Key Laboratory of Guizhou Province for Green Chemical Industry and Clean Energy Technology Guizhou UniversityGuiyang 550025China

The freezing acidolysis solution of the nitric acid-phosphate fertilizer process has a high calcium content,which makes it difficult to produce fine phosphate and high water-soluble phosphate fertilizer ***,based on the potential crystallization principle of calcium sulfate in NH_(4)NO_(3)-H_(3)PO_(4)-H_(2)O,the deep decalcification(*** removal)technology to achieveα-high-strength gypsum originated from freezing acidolysis-solutions has been firstly proposed and ***,calcium can be removed from the factory-provided freezing acidolysis-solution by neutralizing it with ammonia,followed by the addition of ammonium sulfate *** a result,the formation of calcium sulfate in the reaction system undergoes the nucleation and growth of CaSO_(4)·2H_(2)O(DH),as well as its dissolution and crystallization into short columnarα-CaSO_(4)·0.5H_(2)O(α-HH).Remarkably,with the molar ratio of SO_(4)^(2-)/Ca^(2+)at 1.8,the degree of neutralization(NH_(3)/HNO_(3) molar ratio)at 1.7,the reaction temperature of 94℃,and the reaction time of 300 min,the decalcification rate can reach 86.89%,of which the high-strengthα-CaSO_(4)·0.5H_(2)O(α-HH)will be ***,the deep decalcification product meets the standards for the production of fine phosphates and highly water-soluble phosphate ***,the 2 h flexural strength ofα-HH is 5.3 MPa and the dry compressive strength is 36.8 MPa,which is up to the standard of commercialα-HH.

关键词： Nitrophosphate Ammonia neutralization Deep decalcification High-strengthα-hemihydrate gypsum Controlled crystallization at atmospheric pressure

Effect of liquid surface depression size on discharge characteristics and chemical distribution in the plasma-liquid anode system

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Plasma Science and Technology 2024年第9期26卷 17-31页

作者： yun LING dong DAI Jiaxin CHANG Buang WANG School of Electric Power South China University of TechnologyGuangzhou 510641People’s Republic of China University of Richmond Richmond 23173United States of America

Atmospheric pressure plasma-liquid interactions exist in a variety of applications,including wastewater treatment,wound sterilization,and *** practice,the phenomenon of liquid surface depression will inevitably *** applied gas will cause a depression on the liquid surface,which will undoubtedly affect the plasma generation and further affect the application ***,the effect of liquid surface deformation on the plasma is still *** this work,numerical models are developed to reveal the mechanism of liquid surface depressions affecting plasma discharge characteristics and the consequential distribution of plasma species,and further study the influence of liquid surface depressions of different sizes generated by different helium flow rates on the *** show that the liquid surface deformation changes the initial spatial electric field,resulting in the rearrangement of electrons on the liquid *** charges deposited on the liquid surface further increase the degree of distortion of the electric ***,the electric field and electron distribution affected by the liquid surface depression significantly influence the generation and distribution of active species,which determines the practical effectiveness of the relevant *** work explores the phenomenon of liquid surface depression,which has been neglected in previous related work,and contributes to further understanding of plasma-liquid interactions,providing better theoretical guidance for related applications and technologies.

关键词： plasma-liquid interaction deformation of the liquid surface liquid anode species fluxes

Deep learning from three-dimensional Lithium-ion battery multiphysics model Part II:Convolutional neural network and long short-term memory integration

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Energy and AI

Energy and AI 2024年第3期17卷 569-578页

作者： Yiheng Pang Anqi dong yun Wang Zhiqiang Niu Renewable Energy Resources Lab(RERL) Department of Mechanical and Aerospace EngineeringUniversity of CaliforniaIrvineCaliforniaUSA92697-3975 College of Engineering School of System Design and Intelligent ManufacturingSouthern University of Science and TechnologyChina Department of Aeronautical and Automotive Engineering Loughborough UniversityUnited KingdomLE113TU

Lithium-ion (Li-ion) batteries have emerged as a cornerstone of electric vehicles (EVs), enabling the road transportation towards net zero. The success of electric vehicles largely hinges on the battery performance and safety. It is challenging to test and predict battery performance and safety issues by conventional methods, which are usually time-consuming and expensive, involving significant human and measurement errors. To enable the quick estimation of battery performance and safety, we developed three data-driven machine learning (ML) models, namely a convolutional neural network (CNN), a long short-term memory (LSTM), and a CNN-LSTM to predict battery discharge curves and local maximum temperature (hot spot) under various operating conditions. The developed ML models mitigated data scarcity by employing a three-dimensional multi-physics Li-ion battery model to generate enormous and diverse high-quality data. It was found the CNN-LSTM model outperforms the others and achieved high accuracy of 98.68% to learn discharge curves and battery maximum temperature, owing to the integration of spatial and sequential feature extraction. The battery safety can be improved by comparing the predicted maximum battery temperature against safe temperature threshold. The proposed data development and data-driven ML models are of great potential to provide digital tools for engineering high-performance and safe EVs.

关键词： Li-ion batteries CNN LSTM Integration Performance Hot spot

Quantitative evaluation of the contribution of underground space to urban resilience:A case study in China

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Underground Space 2024年第4期17卷 1-24页

作者： Si-Cong Liu Fang-Le Peng Yong-Kang Qiao yun-Hao dong Research Center for Underground Space&Department of Geotechnical Engineering Tongji UniversityShanghai 200092China

Urban underground space(UUS)development has been acknowledged as a positive contribution to urban resilience(UR).Such contribution has been qualitatively addressed in recent years,but only quantitatively discussed in few *** evaluation methods for UR are widely used in China and around the world,but the role of underground space is barely *** paper provides a way to bridge this gap on the city scale.A UR evaluation framework was carefully constructed that covers the basic aspects and elements of *** contributions of UUS to UR were identified and integrated into the UR evaluation framework,and the measurement methods for each indicator related to UUS were determined.A case study of 19 sample cities in China were conducted using the integrated evaluation *** analysis and clustering analysis were further adopted to interpret the evaluation results,mainly with three indicators reflecting the level of UUS development,namely UUS area(m^(2)),UUS density(104 m^(2)/km^(2))and UUS area per capita(m^(2)/person).The results showed a strong correlation between UUS area and *** average proportion of UR provided by UUS in the 19 sample cities was 16.46%,while the maximum figure reached 29.20%.The sample cities were clustered into four categories based on the relationship between the proportion of UR provided by UUS,UUS area,and GDP per capita,where both high and low UUS area tend to provide less proportion of resilience than the medium UUS *** suggestions for UUS utilization were proposed to assist cities in achieving urban resilience.

关键词： Urban underground space(UUS) Urban resilience Resilience evaluation Resilient development

Planning an adaptive reuse development of underutilized urban underground infrastructures:A case study of Qingdao,China

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Underground Space 2024年第1期14卷 18-33页

作者： Yong-Kang Qiao Fang-Le Peng yun-Hao dong Chun-Fang Lu Research Center for Underground Space&Department of Geotechnical Engineering Tongji UniversityShanghai 200092China

Urban underground infrastructures(UUIs)are a vital component of built capital for urban ***,many cities are now home to a multitude of disused or underutilized UUIs,not least aged purpose-built underground facilities,causing a waste of valuable underground space resource *** the process of urban renewal,adaptive reuse can be an attractive solution to breathe new life into underutilized UUIs,while addressing some of the modern problems of the built environment by an economically feasible ***,there is a prevalent absence in the current literature of the overarching planning and decision-making approaches for an adaptive reuse development of underutilized *** the intention of addressing this shortfall,this paper first lays out development strategies,then sets the generic patterns for adaptive reuse of disused or underutilized *** the city of Qingdao,China as a case study,detailed planning and decision-making approaches with the aid of multi-source data and spatial analysis tools are *** is anticipated that the findings of this research will assist the adaptive reuse development of UUIs in providing theoretical guidance and empirical evidence,thereby enhancing the role of urban underground space use in contributing to urban revitalization and urban sustainability.

关键词： Urban underground infrastructures Underutilized Adaptive reuse Planning Urban renewal

Relative difficulty distillation for semantic segmentation

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Science China(Information Sciences) 2024年第9期67卷 126-145页

作者： dong LIANG Yue SUN yun DU Songcan CHEN Sheng-Jun HUANG MIIT Key Laboratory of Pattern Analysis and Machine Intelligence College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Shenzhen Research Institute Nanjing University of Aeronautics and Astronautics

Current knowledge distillation(KD) methods primarily focus on transferring various structured knowledge and designing corresponding optimization goals to encourage the student network to imitate the output of the teacher network. However, introducing too many additional optimization objectives may lead to unstable training, such as gradient conflicts. Moreover, these methods ignored the guidelines of relative learning difficulty between the teacher and student networks. Inspired by human cognitive science, in this paper, we redefine knowledge from a new perspective — the student and teacher networks' relative difficulty of samples, and propose a pixel-level KD paradigm for semantic segmentation named relative difficulty distillation(RDD). We propose a two-stage RDD framework: teacher-full evaluated RDD(TFE-RDD) and teacher-student evaluated RDD(TSE-RDD). RDD allows the teacher network to provide effective guidance on learning focus without additional optimization goals, thus avoiding adjusting learning weights for multiple losses. Extensive experimental evaluations using a general distillation loss function on popular datasets such as Cityscapes, Cam Vid, Pascal VOC, and ADE20k demonstrate the effectiveness of RDD against state-ofthe-art KD methods. Additionally, our research showcases that RDD can integrate with existing KD methods to improve their upper performance bound. Codes are available at https://***/sunyueue/***.

关键词： knowledge distillation semantic segmentation relative difficulty sample weighting prediction discrepancy