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Permian carbonates of Baoshan block, Western Yunnan and their paleoclimatic implications

Science china earth sciences 2004年第5期47卷 385-392页

作者： yan jiaxin1, liang dingyi1 & wu ming2.1. faculty of earth sciences, china university of geosciences, wuhan 430074, china 2. College of Chemistry and Life sciences, South-Central university for Nationalities, wuhan 430074, china china Univ Geosci Fac Earth Sci Wuhan 430074 Peoples R China S Cent Univ National Coll Chem & Life Sci Wuhan 430074 Peoples R China

Recently, much attention has been paid to the climatic significance of carbonates originating in shallow water. Permian carbonates of shallow shelf origin are present in the upper part of the Dingjiazhai Formation, the upper part of the Yongde Formation, and the Shazipo Formation on the Baoshan block of Western Yunnan. Their skeleton and non-skeleton grain as-sociations have been investigated in this study. The carbonates of the Dingjiazhai Formation indicate a Bryonoderm (bryozoans-echinoderm) association without non-skeleton grains. The carbonates of Yongde and Shazipo formations show Chloroforam (green algae-foraminifers) association with peloids. Oolites develop in the Shazipo Formation. Based on the comparisons of grain association with coeval carbonates formed in different paleolatitudes (i.e. various paleo-climatic zones), the carbonates of the Dingjiazhai Formation were thought to have been accu-mulated in shelf environments of warm-temperate zone, and those of the Yongde and Shazipo formations in shelf environments of warm-water.

关键词： Early Permian, carbonate, paleoclimate, Western Yunnan.

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Interface defect induced upgrade of K-storage properties in KFeSO4Fcathode: From lowered Fe-3d orbital energy level to advancedpotassium-ion batteries

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Green Energy & Environment 2024年第11期9卷 1724-1733页

作者： yan Liu Zhen-Yi Gu Yong-Li Heng Jin-Zhi Guo Miao Du Hao-Jie liang Jia-Lin yang Kai-yang Zhang Kai Li Xing-Long wu MOE Key Laboratory for UV Light-Emitting Materials and Technology Northeast Normal UniversityChangchunJilin130024China faculty of Chemistry Northeast Normal UniversityChangchunJilin130024China State Key Laboratory of Rare earth Resource Utilization Changchun Institute of Applied ChemistryChinese Academy of SciencesChangchun130022China

KFeSO_(4)F(KFSF)is considered a potential cathode due to the large capacity and low ***,the inferior electronic conductivity leads to poor electrochemical *** engineering can facilitate the electron/ion transfer by tuning electronic structure,thus providing favorable electrochemical ***,through the regulation of surface defect engineering in reduced graphene oxide(rGO),the Fe–C bonds were formed between KFSF and *** Fe–C bonds formed work in regulating the Fe-3d orbital as well as promoting the migration ability of K ions and increasing the electronic conductivity of ***,the KFSF@rGO delivers a high capacity of 119.6 mAh g^(-1).When matched with a graphite@pitch-derived S-doped carbon anode,the full cell delivers an energy density of 250.5 Wh kg^(-1) and a capacity retention of 81.5%after 400 *** work offers a simple and valid method to develop high-performance cathodes by tuning defect sites.

关键词： Potassium-ion batteries Cathode Defect chemistry KFeSO4F Fe–C bond

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Deep learning projects future warming-induced vegetation growth changes under SSP scenarios

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Advances in Climate Change Research 2022年第2期13卷 251-257页

作者： Zhi-Ting CHEN Hong-yan LIU Chong-yang XU Xiu-Chen wu Bo-Yi liang Jing CAO Deliang CHEN College of Urban and Environmental sciences and MOE Laboratory for earth Surface Processes Peking UniversityBeijing 100871China faculty of Geographical sciences Beijing Normal UniversityBeijing 100875China Department of earth sciences University of GothenburgGothenburg 40530Sweden

Climate warming has been projected to enhance vegetation growth more strongly in higher latitudes than in lower latitudes,but different projections show distinct regional *** employing big data analysis(deep learning),we established gridded,global-scale,climate-driven vegetation growth models to project future changes in vegetation growth under SSP *** projected no substantial trends of vegetation growth change under the sustainable development scenario(SSP1-1.9)by the end of the 21st ***,the increase of vegetation growth driven by climate warming shows distinct regional variability under the scenario representing high carbon emissions and severe warming(SSP5-8.5),especially in Northeast Asia where growth could increase by(6.00%±4.21%).This may be attributed to the high temperature sensitivities of the deciduous needleleaf forests and permanent wetlands in these *** the temperature sensitivity that is defined as permutation importance in deep learning is greater than 0.05,the increase in vegetation growth will be more *** addition,an extreme temperature increase across grasslands,as well as changing land-use management in northern china may also influence the vegetation growth in the *** results suggest that the sustainable development scenario can maintain stable vegetation growth,and it may be a reliable way to mitigate global warming due to potential climate feedbacks driven by vegetation changes in boreal *** needleleaf forests will be a centre of greening in the future,and it should become the focus of future vegetation dynamics modelling studies and projections.

关键词： Vegetation growth Climate change Deep learning Climate sensitivity Future projection

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Sub-percent precision measurement of neutrino oscillation parameters with JUNO

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Chinese Physics C 2022年第12期46卷 28-49页

作者： Angel Abusleme Thomas Adam Shakeel Ahmad Rizwan Ahmed Sebastiano Aiello Muhammad Akram Abid Aleem Fengpeng An Qi An Giuseppe Andronico Nikolay Anfimov Vito Antonelli Tatiana Antoshkina Burin Asavapibhop João Pedro Athayde Marcondes de André Didier Auguste Weidong Bai Nikita Balashov Wander Baldini Andrea Barresi Davide Basilico Eric Baussan Marco Bellato Antonio Bergnoli Thilo Birkenfeld Sylvie Blin David Blum Simon Blyth Anastasia Bolshakova Mathieu Bongrand Clément Bordereau Dominique Breton Augusto Brigatti Riccardo Brugnera Riccardo Bruno Antonio Budano Jose Busto Ilya Butorov Anatael Cabrera Barbara Caccianiga Hao Cai Xiao Cai yanke Cai Zhiyan Cai Riccardo Callegari Antonio Cammi Agustin Campeny Chuanya Cao Guofu Cao Jun Cao Rossella Caruso Cédric Cerna Chi Chan Jinfan Chang Yun Chang Guoming Chen Pingping Chen Po-An Chen Shaomin Chen Xurong Chen Yixue Chen Yu Chen Zhiyuan Chen Zikang Chen Jie Cheng Yaping Cheng Yu Chin Cheng Alexey Chetverikov Davide Chiesa Pietro Chimenti Artem Chukanov Gérard Claverie Catia Clementi Barbara Clerbaux Selma Conforti Di Lorenzo Daniele Corti Flavio Dal Corso Olivia Dalager Christophe De La Taille Zhi Deng Ziyan Deng Wilfried Depnering Marco Diaz Xuefeng Ding Yayun Ding Bayu Dirgantara Sergey Dmitrievsky Tadeas Dohnal Dmitry Dolzhikov Georgy Donchenko Jianmeng Dong Evgeny Doroshkevich Marcos Dracos Frédéric Druillole Ran Du Shuxian Du Stefano Dusini Martin Dvorak Timo Enqvist Heike Enzmann Andrea Fabbri Donghua Fan Lei Fan Jian Fang Wenxing Fang Marco Fargetta Dmitry Fedoseev Zhengyong Fei Li-Cheng Feng Qichun Feng Richard Ford Amélie Fournier Haonan Gan Feng Gao Alberto Garfagnini Arsenii Gavrikov Marco Giammarchi Nunzio Giudice Maxim Gonchar Guanghua Gong Hui Gong Yuri Gornushkin Alexandre Göttel Marco Grassi Vasily Gromov minghao Gu Xiaofei Gu Yu Gu Mengyun Guan Yuduo Guan Nunzio Guardone Cong Guo Jingyuan Guo Wanlei Guo Xinheng Guo Yuhang Guo Paul Hackspacher Caren Hagner Ran Han yang Han Miao He Wei He Tobias Heinz Patrick Hellmuth Yuekun Heng Rafael Herrera YuenKeung Ho Yerevan Physics Institute YerevanArmenia UniversiéLibre de Bruxelles BrusselsBelgium Universidade Estadual de Londrina LondrinaBrazil Pontificia Universidade Catolica do Rio de Janeiro Rio de JaneiroBrazil Pontificia Universidad Católica de Chile SantiagoChile Universidad Tecnica Federico Santa Maria ValparaisoChile Beijing Institute of Spacecraft Environment Engineering BeijingChina Beijing Normal university BeijingChina china Institute of Atomic Energy BeijingChina Institute of High Energy Physics BeijingChina North china Electric Power university BeijingChina School of Physics Peking UniversityBeijingChina Tsinghua university BeijingChina university of Chinese Academy of sciences BeijingChina Jilin university ChangchunChina College of Electronic Science and Engineering National University of Defense TechnologyChangshaChina Chongqing university ChongqingChina Dongguan university of Technology DongguanChina Jinan university GuangzhouChina Sun Yat-Sen university GuangzhouChina Harbin Institute of Technology HarbinChina university of Science and Technology of china HefeiChina The Radiochemistry and Nuclear Chemistry Group in university of South china HengyangChina wuyi university JiangmenChina Shandong university JinanChinaand Key Laboratory of Particle Physics and Particle Irradiation of Ministry of EducationShandong UniversityQingdaoChina Institute of Modern Physics Chinese Academy of SciencesLanzhouChina Nanjing university NanjingChina Guangxi university NanningChina East china university of Science and Technology ShanghaiChina School of Physics and Astronomy Shanghai Jiao Tong UniversityShanghaiChina Tsung-Dao Lee Institute Shanghai Jiao Tong UniversityShanghaiChina Institute of Hydrogeology and Environmental Geology Chinese Academy of Geological SciencesShijiazhuangChina Nankai university TianjinChina wuhan university WuhanChina Xi'an Jiaotong university Xi'anChina Xiamen university XiamenChina School of Physics and Microelectronics Zhengzhou UniversityZhengzhou

JUNO is a multi-purpose neutrino observatory under construction in the south of *** publication presents new sensitivity estimates for the measurement of the △m_(31)^(2),△m_(21)^(2),sin^(2)θ_(12),and sin^(2)θ_(13) oscillation parameters using reactor antineutrinos,which is one of the primary physics goals of the *** sensitivities are obtained using the best knowledge available to date on the location and overburden of the experimental site,the nuclear reactors in the surrounding area and beyond,the detector response uncertainties,and the reactor antineutrino spectral shape constraints expected from the TAO satellite *** is found that the △m_(21)^(2) and sin^(2)θ_(12) oscillation parameters will be determined to 0.5%precision or better in six years of data *** the same period,the △m_(31)^(2) parameter will be determined to about 0.2%precision for each mass ordering *** new precision represents approximately an order of magnitude improvement over existing constraints for these three parameters.

关键词： neutrino oscillation reactor antineutrino precision measurement JUNO

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