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| 1 | Characteristics and Cause Analysis of Heavy Haze in Changchun City in Northeast China显示文摘Northeast China has been reported as having serious air pollution in China with increasing occurrences of severe haze episodes. Changchun City, as the center of Northeast China, has longstanding industry and is an important agricultural base. Additionally, Changchun City has a long winter requiring heating of buildings emitting pollution into the air. These factors contribute to the complexity of haze pollution in this area. In order to analyze the causes of heavy haze, surface air quality has been monitored from 2013 to 2015. By using satellite and meteorological data, atmospheric pollution status, spatio-temporal variations and formation have been analyzed. Results indicated that the air quality in 88.9% of days exceeding air quality index(AQI) level-1 standard(AQI >50) according to the National Ambient Air Quality Standard(NAAQS) of China. Conversely, 33.7% of the days showed a higher level with AQI > 100. Extreme haze events(AQI > 300) occurred frequently during agricultural harvesting period(from October 10 to November 10), intensive winter heating period(from Late-December to February) and period of spring windblown dust(April and May). Most daily concentrations of gaseous pollutants, i.e., NO_2(43.8 μg/m^3), CO(0.9 mg/m^3), SO_2(37.9 μg/m^3), and O_3(74.9 μg/m^3) were evaluated within level-1 concentration limits of NAAQS standards. However, particulate matter(PM_(2.5) and PM10) concentrations(67.3 μg/m^3 and 115.2 μg/m^3, respectively) were significantly higher than their level-1 limits. Severe haze in spring was caused by offsite transported dust and windblown surface soil. Heavy haze periods during fall and winter were mainly formed by intensive emissions of atmospheric pollutants and steady weather conditions(i.e., low wind speed and inversion layer). The overlay emissions of widespread straw burning and coal combustion for heating were the dominant factors contributing to haze in autumn, while intensive coal burning during the coldest time was the primary component of total emissions. In addition, general emissions including automobile exhaust, road and construction dust, residential and industrial activities, have significantly increased in recent years, making heavy haze a more frequent occurrence. Therefore, both improved technological strategies and optimized pollution management on a regional scale are necessary to minimize emissions in specified seasons in Changchun City, as well as comprehensive control measures in Northeast China. | MA Siqi CHEN Weiwei ZHANG Shichun TONG Quansong BAO Qiuyang GAO Zongting | 2017 | Chinese Geographical Science2017，27，6： | 8 |
| 2 | Regional Characteristics and Causes of Haze Events in Northeast China显示文摘Northeast China experiences severe atmospheric pollution, with an increasing occurrence of heavy haze episodes. However, the underlying forces driving haze formation during different seasons are poorly understood. In this study, we explored the spatio-temporal characteristics and causes of haze events in Northeast China by combining a range of data sources(i.e., ground monitoring, satellite-based products, and meteorological products). It was found that the ‘Shenyang-Changchun-Harbin(SCH)'city belt was the most polluted area in the region on an annual scale. The spatial distribution of air quality index(AQI) values had a clear seasonality, with the worst pollution occurring in winter, an approximately oval-shaped polluted area around western Jilin Province in spring, and the best air quality occurring in summer and most of the autumn. The three periods that typically experienced intense haze events were Period I from mid-October to mid-November(i.e., late autumn and early winter), Period II from late-December to February(i.e., the coldest time in winter), and Period III from April to mid-May(i.e., spring). During Period I, strong PM_(2.5) emissions from seasonal crop residue burning and coal burning for winter heating were the dominant reasons for the occurrence of extreme haze events(AQI > 300). Period II had frequent heavy haze events(200 < AQI < 300) in the coldest months of January and February, which were due to high PM_(2.5) emissions from coal burning and vehicle fuel consumption, a lower atmospheric boundary layer, and stagnant atmospheric conditions. Haze events in Period III, with high PM_(10) concentrations, were primarily caused by the regional transportation of windblown dust from degraded grassland in central Inner Mongolia and bare soil in western Jilin Province. Local agricultural tilling could also release PM_(10) and enhance the levels of windblown dust from tilled soil. Better control of coal burning, fuel consumption, and crop residue burning in winter and autumn is urgently needed to address the haze problem in Northeast China. | CHEN Weiwei ZHANG Shichun TONG Quansong ZHANG Xuelei ZHAO Hongmei MA Siqi XIU Aijun HE Yuexin | 2018 | Chinese Geographical Science2018，28，5： | 7 |
| 3 | Brain network markers of abnormal cerebral glucose metabolism and blood flow in Parkinson's disease显示文摘Neuroimaging of cerebral glucose metabolism and blood flow is ideally suited to assay widely-distributed brain circuits as a result of local molecular events and behavioral modulation in the central nervous system.With the progress in novel analytical methodology,this endeavor has succeeded in unraveling the mechanisms underlying a wide spectrum of neurodegenerative diseases.In particular,statistical brain mapping studies have made significant strides in describing the pathophysiology of Parkinson's disease(PD)and related disorders by providing signature biomarkers to determine the systemic abnormalities in brain function and evaluate disease progression,therapeutic responses,and clinical correlates in patients.In this article,we review the relevant clinical applications in patients in relation to healthy volunteers with a focus on the generation of unique spatial covariance patterns associated with the motor and cognitive symptoms underlying PD.These characteristic biomarkers can be potentially used not only to improve patient recruitment but also to predict outcomes in clinical trials. | Shichun Peng David Eidelberg Yilong Ma | 2014 | Neuroscience Bulletin2014，30，5： | 7 |
| 4 | Thermal conductivity of natural rubber nanocomposites with hybrid fillers显示文摘Natural rubber nanocomposites filled with hybrid fillers of multi-walled carbon nanotubes(CNTs) and carbon black(CB) were prepared. CNTs were ultrasonically modified in mixture of hydrogen peroxide(H2O2) and distilled water(H2O). The functional groups on the surface of CNTs, changes in nanotube structure and morphology were characterized by Fourier transform infrared spectroscopy(FT-IR), Raman Spectroscopy, and transmission electron microscopy(TEM). It shows that hydroxyl(OH·) is successfully introduced. The surface defects of modified CNTs were obviously higher than those of original CNTs, and the degree of agglomeration was greatly reduced. Thermal conductivity of the composites was tested by protection heat flow meter method. Compared with unmodified CNTs/CB filling system, the thermal conductivity of hybrid composites is improved by an average of 5.8% with 1.5 phr(phr is parts per hundred rubber) of hydroxyl CNTs and 40 phr of CB filled. A three-dimensional heat conduction network composed of hydroxyl CNTs and CB, as observed by TEM, contributes to the good properties. Thermal conductivity of the hybrid composites increases as temperature rises. The mechanical properties of hybrid composites are also good with hydroxyl CNTs filled nanocomposites;the tensile strength, 100% and 300% tensile stress are improved by 10.1%, 22.4% and 26.2% respectively. | Junping Song Xiteng Li Kaiyan Tian Lianxiang Ma Wei Li Shichune Yao | 2019 | Chinese Journal of Chemical Engineering2019，27，4： | 3 |
| 5 | Acidic oxygen evolution reaction:Mechanism,catalyst classification,and enhancement strategies显示文摘As the most desirable hydrogen production device,the highly efficient acidic proton exchange membrane water electrolyzers(PEMWE)are severely limited by the sluggish kinetics of oxygen evolution reaction(OER)at the anode.Rutile IrO2 is a commercial acid-stable OER catalyst with poor activity and high cost,which has motivated the development of alternatives.However,hitherto most of the designed acidic OER catalysts have disadvantages of low activity or stability,which cannot meet the requirement of industrial applications.Thus,exploring suitable strategies to enhance the activity and stability of cost-effective acidic OER catalysts is crucial for developing the PEMWE technique.In this review,the main OER mechanisms,different types of catalysts,and their activity and stability characteristics are summarized and discussed,and then possible strategies to improve activity and stability are proposed.Finally,the problems and prospects of such catalysts are generalized to shed some light on the future research of advanced catalysts for acidic OER. | Qianli Ma Shichun Mu | 2023 | Interdisciplinary Materials2023，2，1： | 2 |
| 6 | Research Advances of Epidemiological Characteristics and Diagnosis Technology of Rabies Virus显示文摘Rabies is a zoonosis caused by rabies virus,which has been characterized by infection of central nervous system. Rabies virus,which can cause fatal infections in humans and other mammals,has the characteristic of neurotropism,and the mortality caused by rabies is almost 100%. Routine diagnosis of rabies include clinical symptoms,while a final diagnosis depends on laboratory diagnostic methods,such as etiological diagnosis,serological diagnosis and molecular biological diagnosis. As a zoonotic infectious disease,rabies presents a global distribution situation,and the deaths caused by rabies virus infection in China ranks the second place in the world. Therefore,strengthening the recognition of disease etiology and epidemiology is very important to comprehensive prevention measures of rabies. The author mainly introduced the research progress on pathogen,epidemiology and diagnosis technology of rabies virus at home and abroad. In addition,the advantages and disadvantages of various methods were compared respectively,in order to provide a scientific basis for further study and rapid diagnosis of rabies. | Sun Yu Ma Shichun Wang Xiaoying Wei Wei Su Zenghua Ma Jihong Xie Qiao Xu Yi Dong Hao Shi Jianzhong | 2015 | Animal Husbandry and Feed Science2015，7，4： | 2 |
| 7 | Perspective on solid‐electrolyte interphase regulation for lithium metal batteries显示文摘The solid‐electrolyte interphase(SEI)generated between the electrode and the electrolyte strongly influences the performance of batteries.As the most at-tractive next‐generation energy storage system with ultrahigh energy density,the development of lithium metal batteries(LMBs)has been greatly plagued by the uncontrollable lithium(Li)dendrite and serious electrolyte decom-position resulting from the self‐derived unstable SEI with poor properties.In this perspective,the recent progress of regulating the nature and composition of the SEI to stabilize the Li metal in LMBs is summarized,followed by a discussion of the formation mechanism and the property of the SEI.The strategies for constructing a stable SEI are summarized,for example,design of a compatible electrolyte with the anode,adding self‐sacrificing additives or solvation control additives,and the regulation of nonfaradaic electric ad-sorption and desorption progress.Finally,the guideline for the rational design of the SEI is proposed. | Mingguang Wu Yong Li Xinhua Liu Shichun Yang Jianmin Ma Shixue Dou | 2021 | SmartMat2021，2，1： | 1 |
| 8 | Review of Abnormality Detection and Fault Diagnosis Methods for Lithium‑Ion Batteries显示文摘Electric vehicles are developing prosperously in recent years.Lithium-ion batteries have become the dominant energy storage device in electric vehicle application because of its advantages such as high power density and long cycle life.To ensure safe and efficient battery operations and to enable timely battery system maintenance,accurate and reliable detection and diagnosis of battery faults are necessitated.In this paper,the state-of-the-art battery fault diagnosis methods are comprehensively reviewed.First,the degradation and fault mechanisms are analyzed and common abnormal behaviors are summarized.Then,the fault diagnosis methods are categorized into the statistical analysis-,model-,signal processing-,and data-driven methods.Their distinctive characteristics and applications are summarized and compared.Finally,the challenges facing the existing fault diagnosis methods are discussed and the future research directions are pointed out. | Xinhua Liu Mingyue Wang Rui Cao Meng Lyu Cheng Zhang Shen Li Bin Guo Lisheng Zhang Zhengjie Zhang Xinlei Gao Hanchao Cheng Bin Ma Shichun Yang | 2023 | Automotive Innovation2023，6，2： | 1 |
| 9 | Atomically dispersed dual Fe centers on nitrogen-doped bamboo-like carbon nanotubes for efficient oxygen reduction显示文摘Interfacial atomic configuration between dual-metal active species and nitrogen-carbon substrates is of great importance for improving the intrinsic activity of catalysts toward oxygen reduction reaction(ORR).Thus,from the atomic-scale engineering we develop a high intrinsic activity ORR catalyst in terms of incorporating atomically dispersed dual Fe centers(single Fe atoms and ultra-small Fe atomic clusters)into bamboo-like N-doped carbon nanotubes.Benefiting from atomically dispersed dual-Fe centers on the atomic interface of Fe-Nx/carbon nanotubes,the fabricated dual Fe centers catalyst exhibits an extremely high ORR activity(E_(onset)=1.006 V;E_(1/2)=0.90 V),beyond state-of-the-art Pt/C.Remarkably,this catalyst also shows a superior kinetic current density of 19.690 mA·cm^(−2),which is 7 times that of state-of-the-art Pt/C.Additionally,based on the excellent catalyst,the primary Zn-air battery reveals a high power density up to 137 mW·cm^(−2) and sufficient potential cycling stability(at least 25 h).Undoubtedly,given the unique structure–activity relationship of dual-Fe active species and metal-nitrogen-carbon substrates,the catalyst will show great prospects in highly efficient electrochemical energy conversion devices. | Ligang Ma Junlin Li Zhiwei Zhang Hao Yang Xueqin Mu Xiangyao Gu Huihui Jin Ding Chen Senlin Yan Suli Liu Shichun Mu | 2022 | Nano Research2022，15，3： | 0 |
| 10 | End-cloud collaboration method enables accurate state of health and remaining useful life online estimation in lithium-ion batteries显示文摘Though the lithium-ion battery is universally applied,the reliability of lithium-ion batteries remains a challenge due to various physicochemical reactions,electrode material degradation,and even thermal runaway.Accurate estimation and prediction of battery health conditions are crucial for battery safety management.In this paper,an end-cloud collaboration method is proposed to approach the track of battery degradation process,integrating end-side empirical model with cloud-side data-driven model.Based on ensemble learning methods,the data-driven model is constructed by three base models to obtain cloud-side highly accurate results.The double exponential decay model is utilized as an empirical model to output highly real-time prediction results.With Kalman filter,the prediction results of end-side empirical model can be periodically updated by highly accurate results of cloud-side data-driven model to obtain highly accurate and real-time results.Subsequently,the whole framework can give an accurate prediction and tracking of battery degradation,with the mean absolute error maintained below 2%.And the execution time on the end side can reach 261μs.The proposed end-cloud collaboration method has the potential to approach highly accurate and highly real-time estimation for battery health conditions during battery full life cycle in architecture of cyber hierarchy and interactional network. | Bin Ma Lisheng Zhang Hanqing Yu Bosong Zou Wentao Wang Cheng Zhang Shichun Yang Xinhua Liu | 2023 | Journal of Energy Chemistry2023，，7： | 0 |
| 11 | Non-invasive Characteristic Curve Analysis of Lithium-ion Batteries Enabling Degradation Analysis and Data-Driven Model Construction:A Review显示文摘Power battery technology is essential to ensuring the overall performance and safety of electric vehicles.Non-invasive char-acteristic curve analysis(CCA)for lithium-ion batteries is of particular importance.CCA can provide characteristic data for further applications such as state estimation and thermal runaway warning without disassembling the batteries.This paper summarizes the characteristic curves consisting of incremental curve analysis,differential voltage analysis,and differential thermal voltammetry from the perspectives of exploring the aging mechanism of batteries and constructing the data-driven model.The process of quantitative analysis of battery aging mechanism is presented and the steps of constructing data-driven models are induced.Moreover,the recent progress and application of the main features and methodologies are discussed.Finally,the applicability of battery CCA is discussed by converting non-quantifiable battery information into transportable data covering macrostate and micro-reaction information.Combined with the cloud-based battery management platform,the above-mentioned battery characteristic curves could be used as a valuable dataset to upgrade the next-generation battery management system design. | Rui Cao Hanchao Cheng Xuefeng Jia Xinlei Gao Zhengjie Zhang Mingyue Wang Shen Li Cheng Zhang Bin Ma Xinhua Liu Shichun Yang | 2022 | Automotive Innovation2022，5，2： | 0 |
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