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Science China Chemistry 2022年第8期65卷 1615-1622页

作者： Kuibao Yu Wei Song Jinfeng Ge kanghui zheng Lin Xie Zhenyu Chen Yi Qiu Ling Hong Cuirong Liu Ziyi Ge Zhejiang Provincial Engineering Research Center of Energy Optoelectronic Materials and Devices Ningbo Institute of Materials Technology&EngineeringChinese Academy of SciencesNingbo 315201China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing 100049China College of Materials Science and Engineering Taiyuan University of Science and TechnologyTaiyuan 030024China

Optimizing the photoactive layer morphology is a simple,promising way to improve the power conversion efficiencies(PCEs)of organic solar cells(OSCs).Here,we compared different post-processing treatments on PM6:Y6 blend films and relevant effects on device performances,including as-cast,thermal annealing and solvent *** solvent annealing processes can effectively improve the vertical distribution and aggregation of polymer donors and small molecule acceptors,then optimize the active layer film morphology,ultimately elevating ***,one of champion efficiencies of 18.01%was achieved based on the PM6:Y6 binary *** addition,a relatively high light utilization efficiency(2.53%)was achieved when a transparent electrode made of Cu(1 nm)and Ag(15 nm)was utilized to fabricate a semitransparent OSC with a remarkable PCE of 13.07%and 19.33%average visible-light *** results demonstrated that carefully optimizing morphology of active layer is conducive to achieving a high-performance OSC.

关键词： organic solar cells solvent vapor annealing morphology optimization light utilization efficiency

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Improved phase stability of CsPbI2Br perovskite by released microstrain toward highly efficient and stable solar cells

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InfoMat 2021年第12期3卷 1431-1444页

作者： kanghui zheng Jinfeng Ge Chang Liu Qiang Lou Xia Chen Yuanyuan Meng Xu Yin Shixiao Bu Cuirong Liu Ziyi Ge Ningbo Institute of Materials Technology and Engineering Chinese Academy of SciencesNingboChina College of Materials Technology and Engineering Taiyuan University of Science and TechnologyTaiyuanChina Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijingChina

All-inorganic perovskite solar cells(PSCs)have developed rapidly in the field of photovoltaics due to their excellent thermal and light ***,compared with organic–inorganic hybrid perovskites,the phase instability of inorganic perovskite under humidity still remains as a critical issue that ham-pers the commercialization of inorganic *** originally propose in this work that microstrains between the perovskite lattices/grains play a key role in affecting the phase stability of inorganic *** this end,we inno-vatively design theπ-conjugated p-type molecule bis(2-ethylhexyl)3,30((4,8-bis(5-(2-ethylhexyl)-3,4-difluorothiophen-2-yl)benzo[1,2-b:4,5-b0]dithiophene-2,6-di yl)bis(3,300-dioctyl[2,20:50,200-terthiophene]-500,5-diyl))(2E,20 E)-bis(2-cyanoacrylate)(BTEC-2F)to covalent with the Pb dangling bonds in CsPbI2Br perovskite film,which significantly suppress the trap states and release the defect-induced local stress between perovskite *** interplay between the microstrains and phase stability of the inorganic perovskite are scrutinized by a series of charac-terizations including x-ray photoelectron spectroscopy,photoluminescence,x-ray diffraction,scanning electron microscopy,and so forth,based on which,we conclude that weaker local stresses in the perovskite film engender superior phase stability by preventing the perovskite lattice distortion under *** this rational design,PSCs based on CsPbI2Br perovskite system deliver an outstanding power conversion efficiency(PCE)up to 16.25%.The unencapsulated device also exhibits an exceptional moisture stability by retaining over 80%of the initial PCE after 500 h aging in ambient with relative humidity of(RH)25%.

关键词： CsPbI2Br interface modification microstrains phase stability π-conjugated small molecule

雷州半岛土壤-农作物汞元素含量特征与健康风险分析

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生态环境学报 2022年第3期31卷 572-582页

作者：陈碧珊郑康慧王璟叶林海宋军霞岭南师范学院地理科学学院广东湛江524048

汞是能在生态系统中完整循环的重金属元素。在工农业生产中,汞的广泛使用使汞污染愈发严重。随着大型工业企业入驻湛江,这些企业在生产过程中排放的重金属元素经过扩散、淋溶和下渗等方式,对土壤和农作物等造成污染。雷州半岛地势平坦,... 详细信息

汞是能在生态系统中完整循环的重金属元素。在工农业生产中,汞的广泛使用使汞污染愈发严重。随着大型工业企业入驻湛江,这些企业在生产过程中排放的重金属元素经过扩散、淋溶和下渗等方式,对土壤和农作物等造成污染。雷州半岛地势平坦,热量资源丰富,种植历史悠久,在广东省乃至全国都具有重要的农业战略地位。该研究旨在了解雷州半岛地区农业土壤和农作物中汞元素的分布情况,分析其对生态和人体健康的风险,为当地农作物的科学合理种植、土壤污染防治、土壤改良和农业生态建设与发展提供基础数据和科学理论依据。以水稻田、蔬菜地和果园地土壤3种典型的农业土壤类型及相应的农作物为研究对象,共采集了128份农业表层土壤样品和65份农作物可食用部分的样品,采用单因素方差方法及Hakanson潜在生态危害指数法,分析了雷州半岛农业土壤及其农作物的汞元素的累积特征、潜在生态风险和对人体的健康风险。结果表明,雷州半岛农业土壤中汞的平均质量分数为0.121 mg·kg^(−1),超过研究区的背景值,呈现明显的累积效应。汞元素含量的空间分布不均匀,大致呈现西南多,东北少的特征。蔬菜的平均汞含量最大,为0.033 mg·kg^(−1);叶类蔬菜的富集能力最强。水果中菠萝的富集能力强,其余水果的富集能力较弱。研究区出现强潜在生态风险的采样点占43.75%,农业土壤中汞元素的整体生态风险较高。农业土壤以及农作物中的汞对人体造成的健康风险均在可接受范围内,但仍存在一定的风险,需继续关注。

关键词：农业土壤农作物汞元素健康风险雷州半岛

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广东省湛江市水稻台风灾害风险评估

灾害学 2021年第3期36卷 85-90页

作者：尚志海周铭毅梁其胜杨舒惠张荣龙郑康慧岭南师范学院地理科学学院广东湛江524048

水稻是南方地区最重要的粮食作物,以其为研究对象进行台风灾害风险评估具有重要意义。基于自然灾害风险的形成机制,综合考虑发灾场敏感性、致灾力危险性和承灾体暴露性等三个方面10个指标,建立评估指标体系,运用突变级数法构建评估模型,... 详细信息

水稻是南方地区最重要的粮食作物,以其为研究对象进行台风灾害风险评估具有重要意义。基于自然灾害风险的形成机制,综合考虑发灾场敏感性、致灾力危险性和承灾体暴露性等三个方面10个指标,建立评估指标体系,运用突变级数法构建评估模型,以1998—2018年影响湛江市台风资料为基础数据,进行水稻台风灾害风险等级评估。结果表明:湛江市水稻台风灾害承灾体暴露性呈现出中部和北部高的特征;致灾力危险性分布呈现出东部和南部高的特征;发灾场敏感性呈现出东部和中部高的特征。水稻台风灾害风险高的区域在湛江市中部和北部地区,风险指数为0的区域主要分布在徐闻县中部地区、雷州市中部和南部、遂溪县中部地区。研究结果可以为地级市台风灾害的分级风险管理提供依据。

关键词：台风灾害水稻风险评估湛江市

Quantitative Precipitation Forecast Experiment Based on Basic NWP Variables Using Deep Learning

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Advances in Atmospheric Sciences 2022年第9期39卷 1472-1486页

作者： kanghui ZHOU Jisong SUN Yongguang zheng Yutao ZHANG National Meteorological Center Beijing 100081China Nanjing Joint Institute for Atmospheric Sciences Nanjing 210000China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China

The quantitative precipitation forecast(QPF)performance by numerical weather prediction(NWP)methods depends fundamentally on the adopted physical parameterization schemes(PS).However,due to the complexity of the physical mechanisms of precipitation processes,the uncertainties of PSs result in a lower QPF performance than their prediction of the basic meteorological variables such as air temperature,wind,geopotential height,and *** study proposes a deep learning model named QPFNet,which uses basic meteorological variables in the ERA5 dataset by fitting a non-linear mapping relationship between the basic variables and *** variables forecasted by the highest-resolution model(HRES)of the European Centre for Medium-Range Weather Forecasts(ECMWF)were fed into QPFNet to forecast *** results show that QPFNet achieved better QPF performance than ECMWF HRES *** threat score for 3-h accumulated precipitation with depths of 0.1,3,10,and 20 mm increased by 19.7%,15.2%,43.2%,and 87.1%,respectively,indicating the proposed performance QPFNet improved with increasing levels of *** sensitivities of these meteorological variables for QPF in different pressure layers were analyzed based on the output of the QPFNet,and its performance limitations are also *** DL to extract features from basic meteorological variables can provide an important reference for QPF,and avoid some uncertainties of PSs.

关键词： deep learning quantitative precipitation forecast permutation importance numerical weather prediction

人工冰场用跨临界CO_(2)并联压缩制冷试验研究

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流体机械 2023年第12期51卷 16-22,35页

作者：吴小华魏闻天宋衍昌李晓琼张振涛郑康辉杨俊玲北京石油化工学院机械工程学院深水油气管线关键技术与装备北京市重点实验室北京102617 中国科学院理化技术研究所中国轻工业食品药品保质加工储运装备与节能技术重点实验室北京100190 中科碳冷(无锡)高科技有限公司江苏无锡214104

为了研究应用于人工冰场的跨临界CO_(2)并联压缩制冷系统性能,搭建了跨临界CO_(2)并联压缩制冷系统,试验研究了单压缩机独立运行以及双压缩机并联运行时,蒸发温度与压缩机运行频率对系统COP、制冷量、压缩机功率、制冷剂流量、压比的影... 详细信息

为了研究应用于人工冰场的跨临界CO_(2)并联压缩制冷系统性能,搭建了跨临界CO_(2)并联压缩制冷系统,试验研究了单压缩机独立运行以及双压缩机并联运行时,蒸发温度与压缩机运行频率对系统COP、制冷量、压缩机功率、制冷剂流量、压比的影响。结果表明,随蒸发温度升高,COP、制冷量、压缩机功率和制冷剂流量均增大,压比减小,蒸发温度为-9.4℃时,COP达到本试验的最大值2.00;在试验工况40~60 Hz范围内,随着压缩机运行频率增加,制冷量、压缩机功率、制冷剂流量和压比均增大;单台压缩机独立运行和并联压缩时,COP均在50 Hz达到最大,且并联压缩COP随压缩机运行频率差的增加而降低,最大可相差26.67%。建立了系统COP预测模型,通过蒸发温度与排气压力对COP进行预测,并与并联压缩试验结果进行了对比,所构建模型预测结果与同频率并联压缩系统试验测得COP平均误差为3.7%。研究结果可为并联压缩制冷系统设计提供借鉴和指导。

关键词：并联压缩 CO_(2) 人工冰场预测模型

近20年登陆湛江市的热带气旋致灾力和危险度分析

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防灾科技学院学报 2021年第2期23卷 62-69页

作者：郑康慧尚志海梁其胜杨舒惠周铭毅岭南师范学院地理科学学院广东湛江524048

湛江市热带气旋灾害频发且损失严重,以2000—2019年登陆的热带气旋资料为基础,以热带气旋中心最低气压、近中心最大风速和过程最大日降雨量为因子,构建单个热带气旋致灾力评价模型,并通过热带气旋登陆次数、大风影响次数、暴雨影响次数... 详细信息

湛江市热带气旋灾害频发且损失严重,以2000—2019年登陆的热带气旋资料为基础,以热带气旋中心最低气压、近中心最大风速和过程最大日降雨量为因子,构建单个热带气旋致灾力评价模型,并通过热带气旋登陆次数、大风影响次数、暴雨影响次数等评价区域热带气旋灾害危险度,以此分析湛江市热带气旋灾害特征。结果表明:登陆湛江市的热带气旋强度以热带风暴和台风为主;热带气旋登陆频次呈上升趋势;热带气旋登陆地点集中在湛江市海岸线东段和南段;单个热带气旋致灾力最大的热带气旋是威马逊;湛江市热带气旋灾害危险度呈现由东南向西北递减的分布规律。

关键词：热带气旋致灾力危险度湛江市大风暴雨

Forecasting Different Types of Convective Weather: A Deep Learning Approach

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Journal of Meteorological Research 2019年第5期33卷 797-809页

作者： kanghui ZHOU Yongguang zheng Bo LI Wansheng DONG Xiaoling ZHANG Chinese Academy of Meteorological Sciences China Meteorological AdministrationBeijing 100081China University of Chinese Academy of Sciences Beijing 100049China National Meteorological Center China Meteorological AdministrationBeijing 100081China University of Illinois at Urbana-Champaign ChampaignIL 61820USA

A deep learning objective forecasting solution for severe convective weather(SCW) including short-duration heavy rain(HR), hail, convective gusts(CG), and thunderstorms based on numerical weather prediction(NWP) data was developed. We first established the training datasets as follows. Five years of severe weather observations were utilized to label the NCEP final(FNL) analysis data. A large number of labeled samples for each type of weather were then selected for model training. The local temperature, pressure, humidity, and winds from 1000 to 200 h Pa, as well as dozens of convective physical parameters, were taken as predictors in our model. A six-layer convolutional neural network(CNN) model was then built and trained to obtain optimal model weights. After that, the trained model was used to predict SCW based on the Global Forecast System(GFS) forecast data as input. The performances of the CNN model and other traditional methods were compared. The results show that the deep learning algorithm had a higher classification accuracy on HR and hail than support vector machine, random forests, and other traditional machine learning algorithms. The objective forecasts by use of the deep learning algorithm also showed better forecasting skills than the subjective forecasts by the forecasters. The threat scores(TSs) of thunderstorm, HR, hail, and CG were increased by 16.1%, 33.2%, 178%, and 55.7%, respectively. The deep learning forecast model is currently used in the National Meteorological Center of China to provide guidance for the operational SCW forecasting over China.

关键词： deep learning convolutional neural network convective weather forecasting

Progress in Severe Convective Weather Forecasting in China since the 1950s

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Journal of Meteorological Research 2020年第4期34卷 699-719页

作者： Xiaoling ZHANG Jianhua SUN Yongguang zheng Yuanchun ZHANG Ruoyun MA Xinlin YANG kanghui ZHOU Xuqing HAN National Meteorological Center China Meteorological AdministrationBeijing 100081 Key Laboratory of Cloud–Precipitation Physics and Severe Storms Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029 University of Chinese Academy of Sciences Beijing 100049

Located in the Asian monsoon region, China frequently experiences severe convective weather(SCW), such as short-duration heavy rainfall(SDHR), thunderstorm high winds, hails, and occasional tornadoes. Progress in SCW forecasting in China is closely related to the construction and development of meteorological observation networks,especially weather radar and meteorological satellite networks. In the late 1950 s, some county-level meteorological bureaus began to conduct empirical hail forecasting based on observations of clouds and surface meteorological variables. It took over half a century to develop a modern comprehensive operational monitoring and warning system for SCW forecast nationwide since the setup of the first weather radar in 1959. The operational SCW forecasting, including real-time monitoring, warnings valid for tens of minutes, watches valid for several hours, and outlooks covering lead times of up to three days, was established in 2009. Operational monitoring and forecasting of thunderstorms,SDHR, thunderstorm high winds, and hails have been carried out. The performance of operational SCW forecasting will be continually improved in the future with the development of convection-resolving numerical models(CRNMs), the upgrade of weather radar networks, the launch of new-generation meteorological satellites, better understanding of meso-γ and microscale SCW systems, and further application of artificial intelligence technology and CRNM predictions.

关键词： severe convective weather(SCW) forecasting radar meteorological satellite artificial intelligence convection-resolving numerical model(CRNM)

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我国中东部雷暴活动特征分析

气象 2020年第2期46卷 189-199页

作者：王婷波周康辉郑永光中国气象局气象干部培训学院北京100081 国家气象中心北京100081

基于2010—2014年国家闪电监测网的云-地闪电定位数据,利用雷暴识别与追踪算法获得了505257个雷暴系统,进而统计分析了我国中东部地区的雷暴发生发展特征。考虑地形和气候差异,将我国中东部划分为东北、华北、华中与华东、西南、华南五... 详细信息

基于2010—2014年国家闪电监测网的云-地闪电定位数据,利用雷暴识别与追踪算法获得了505257个雷暴系统,进而统计分析了我国中东部地区的雷暴发生发展特征。考虑地形和气候差异,将我国中东部划分为东北、华北、华中与华东、西南、华南五个区域,对比了上述区域的雷暴中地闪活动持续时间、移动距离、移动速度等特征,并进一步对雷暴发生的环境物理量特征进行了统计分析,最后讨论了雷暴发生与地形的相关关系。结果显示:雷暴具有局地性强、快速生消的特性,超过70%的雷暴移动速度低于60 km·h-1,超过80%的雷暴持续时间低于2 h,超过90%的雷暴移动距离低于60 km;东北地区雷暴移动速度相对更快,西南地区移速较慢且雷暴移动距离更短。华中与华东、华南地区雷暴发生的整层可降水量与对流有效位能值最高,西南次之,东北与华北地区最低,而0~6 km垂直风切变则反之;广东、海南等地为雷暴发生最活跃区域,江南、西南地区东部、华南地区西部、华北地区太行山一带等地为雷暴发生较为活跃的地区;雷暴发生与地形密切相关,四川盆地西麓与珠江三角洲地区明显呈现出随地形抬升而导致雷暴触发的情况。

关键词：雷暴闪电追踪统计