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Geochemical characteristics and applications of 18α(H)-neohopanes and 17α(H)-diahopanes

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chinese Science Bulletin 2000年第19期45卷 1742-1748页

作者： wang Chunjiang, FU Jiamo, SHENG Guoying, XIAO Qianhua, li Jinyou, ZHANG Yali & PIAO mingzhi1. Slate key laboratory of organic geochemistry, guangzhou institute of geochemistry, chinese academy of sciences. Guang/hou {12., China 2. department of Geosciences, Petroleum University, Beijing 102.00, China 3. institute of Petroleum Exploration and Exploitation, liaohe Bureau of Petroleum Exploration, Panjin 2.0000, China state key {2. of organic geochemistry Guangzhou Institute of Geochemistry Chinese Academy of Sciences Guangzhou China department of Geosciences Petroleum University Beijing China institute of Petroleum Exploration and Exploitation Liaohe Bureau of Petroleum Exploration Panjin China

Distributions and geochemical significances of 18α(H)-neohopanes and of 17α(H)-diahopanes in oils from west Xialiaohe depression of the Bohai Bay Basin have been studied. Relative abundance of 18α(H)-neohopanes and of 17α(H)-diahopanes can be effectively used as maturity parameters, in a range of medium-high mature stage, based on consideration on sedimentary-organic facies of source rocks. With a dual geochemical significance of maturity and sedimentary-organic facies, neohopane and diahopane parameters can be well used in oil-source correlation and in petroleum population division. Formation, primary concentration and preservation of precursors of rearranged hopanes are closely related to depositional conditions such as Eh-pH and clays content. A series of probable diahopanes (series D) was detected in the oils, which exhibits a similar distribution pattern and geochemical behavior as that of 17α(H)-diahopanes (series B).

关键词： 18α(H)-neohopane 17α(H)-diahopane maturity sedimentary-organic facies.

Roadmap for rechargeable batteries:present and beyond

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Science China Chemistry 2024年第1期67卷 13-42页

作者： Sen xin Xu Zhang lin {2. Haijun Yu xin Chang Yu-ming Zhao Qinghai Meng Pan Xu Chen-Zi Zhao Jiahang Chen Huichao Lu Xirui Kong Jiulin {2. Kai Chen Gang Huang xinbo Zhang Yu Su Yao Xiao Shu-Lei Chou Shilin Zhang Zaiping Guo Aobing Du Guanglei Cui Gaojing Yang Qing Zhao liubing Dong Dong Zhou Feiyu Kang Hu Hong Chunyi Zhi Zhizhang Yuan Xianfeng li Yifei Mo Yizhou Zhu Dongfang Yu xincheng Lei Jianxiong Zhao Jiayi {2. Dong Su Yu-Guo Guo Qiang Zhang jun Chen li-jun Wan CAS key laboratory of Molecular Nanostructure and Nanotechnology CAS Research/Education Center for Excellence in Molecular SciencesBeijing National Laboratory for Molecular Sciences(BNLMS)Institute of ChemistryChinese Academy of Sciences(CAS)Beijing 100190China University of chinese academy of sciences.Beijing 100049 China institute of Advanced Battery Materials and devices Faculty of Materials and ManufacturingBeijing University of TechnologyBeijing 100124China key laboratory of Advanced Functional Materials Ministry of EducationBeijing University of TechnologyBeijing 100124China Beijing key laboratory of Green Chemical Reaction Engineering and Technology Department of Chemical EngineeringTsinghua UniversityBeijing 100084China state key {2. of Chemistry and Utilization of Carbon-Based Energy Resources College of ChemistryXinjiang UniversityUrumqi 830046China department of Chemical Engineering Shanghai Jiao Tong UniversityShanghai 200240China state key {2. of Rare Earth Resource Utilization Changchun Institute of Applied ChemistryChangchun 130022China institute for Carbon Neutralization College of Chemistry and Materials EngineeringWenzhou UniversityWenzhou 325035China School of Chemical Engineering and Advanced Materials The University of AdelaideAdelaide 5000Australia Qingdao Industrial Energy Storage Research institute Qingdao Institute of Bioenergy and Bioprocess TechnologyChinese Academy of SciencesQingdao 266101China Frontiers Science Center for New organic Matter Key Laboratory of Advanced Energy Materials Chemistry(Ministry of Education)College of ChemistryNankai UniversityTianjin 300071China College of Chemistry and Materials Science Jinan UniversityGuangzhou 511443China Tsinghua Shenzhen International Graduate School Tsinghua UniversityShenzhen 518055China department of Materials Science and Engineering City University of Hong KongHong Kong 999077China Division of Energy Storage Dalian National Laboratory for Clean Energy(DNL)Dalian Institute of Chem

Rechargeable batteries currently hold the largest share of the electrochemical energy storage market,and they play a major role in the sustainable energy transition and industrial decarbonization to respond to global climate *** to the increased popularity of consumer electronics and electric vehicles,lithium-ion batteries have quickly become the most successful rechargeable batteries in the past three decades,yet growing demands in diversified application scenarios call for new types of rechargeable *** efforts are made to developing the next-generation post-li-ion rechargeable batteries,which include,but are not limited to solid-state batteries,lithium–sulfur batteries,sodium-/potassium-ion batteries,organic batteries,magnesium-/zinc-ion batteries,aqueous batteries and flow *** the great achievements,challenges persist in precise understandings about the electrochemical reaction and charge transfer process,and optimal design of key materials and interfaces in a *** roadmap tends to provide an overview about the current research progress,key challenges and future prospects of various types of rechargeable *** computational methods for materials development,and characterization techniques will also be discussed as they play an important role in battery research.

关键词： energy storage rechargeable batteries battery materials electrochemistry

Biomolecular condensates and disease pathogenesis

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Science China(life sciences) 2024年第9期67卷 1792-1832页

作者： Ke Ruan Ge Bai Yanshan Fang Dan li Tingting li {2.gguo liu Boxun Lu Qing Lu Zhou Songyang Shuguo Sun Zheng wang {2. Zhang Wen Zhou Hong Zhang The First Affiliated Hospital&School of life {2. Ministry of Education Key Laboratory for Membrane-less Organelles&Cellular DynamicsHefei National Research Center for Interdisciplinary Sciences at the MicroscaleCenter for Advanced Interdisciplinary Science and Biomedicine of IHMDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefei 230027China Nanhu Brain-computer Interface institute Hangzhou 311100China department of Neurology of Second Affiliated Hospital and School of Brain Science and Brain Medicine Zhejiang University School of MedicineHangzhou 310058China Interdisciplinary Research Center on Biology and Chemistry Shanghai Institute of Organic ChemistryChinese Academy of SciencesShanghai 201210China University of chinese academy of sciences Beijing 100049China Bio-X institutes Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders(Ministry of Education)Shanghai Jiao Tong UniversityShanghai 200030China department of Biomedical Informatics School of Basic Medical SciencesPeking University Health Science CenterBeijing 100191China CAS key laboratory of Regenerative Biology Joint School of Life SciencesGuangzhou Institutes of Biomedicine and HealthChinese Academy of SciencesGuangzhou 510530China Joint School of life sciences Guangzhou Medical UniversityGuangzhou 510000China Neurology department at Huashan Hospital State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceInstitutes of Brain ScienceSchool of Life SciencesFudan UniversityShanghai 200433 China key laboratory for the Genetics of {2.velopmental and Neuropsychiatric Disor{2.rs Ministry of EducationBio-X InstitutesShanghai Jiao Tong UniversityShanghai 200030China state key {2. of Biocontrol MOE Key Laboratory of Gene Function and Regulation and Guangzhou Key Laboratory of Healthy Aging ResearchSchool of Life SciencesSun Yat-sen Memorial HospitalSun Yat-sen UniversityGuangzhou 510275China department of Human Anatomy Hist

Biomolecular condensates or membraneless organelles(MLOs)formed by liquid-liquid phase separation(LLPS)divide intracellular spaces into discrete compartments for specific *** of LLPS or aberrant phase transition that disturbs the formation or material states of MLOs is closely correlated with neurodegeneration,tumorigenesis,and many other pathological ***,we summarize the recent progress in development of methods to monitor phase separation and we discuss the biogenesis and function of MLOs formed through phase *** then present emerging proof-of-concept examples regarding the disruption of phase separation homeostasis in a diverse array of clinical conditions including neurodegenerative disorders,hearing loss,cancers,and immunological ***,we describe the emerging discovery of chemical modulators of phase separation.

关键词： liquid-liquid phase separation biomolecular condensate membraneless organelle

Mixing state of Particles by Single Particle Aerosol Mass Spectrometer in Urban Area of PRD

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Mixing State of Particles by Single Particle Aerosol Mass Sp...

家用燃煤及烟气中多环芳烃的GC-MS定量研究

第七届亚洲气溶胶会议

作者： xinhui Bi 1, Guohua Zhang1, Lei li 2. xinming wang 1, Guoying Sheng 1, Jiamo Fu 1, 2.and Zhen Zhou2.1 state key laboratory of organic geochemistry, Guangdong Province key laboratory of Utilization and Protection of Environmental Resource, guangzhou institute of geochemistry, chinese academy of sciences, guangzhou, 510640, P.R. China 2.School of Environmental and Chemical Engineering, Shanghai University, Shanghai 2.0444, P. R. China

Single particle aerosol mass spectrometer (SPAMS) was used to characterize the single particle size and chemical composition of submicron aerosols in the urban area of the Pearl River delta (PRD) region, China, for the period April 30 through May 2., 2.10. This is the first study for the mixing {2. of aerosols by direct observation in this region. 696,465 particles were sized and chemical analyzed with both positive and negative ion spectra, in which 141,338 biomass burning particles were identified representing a significant source of submicron particles ～2..3% by numbe, and carbonaceous particles accounted for as much as 5% of submicron particles by number. Up to 98% carbonaceous particles were found to internally mix with secondary inorganic species. Carbonaceous particles were clustered into three distinct particle groups, comprised of organic carbon (OC), elemental carbon (EC) and the mixture of both (OCEC). The OC specie was the most abundant, with concentrations of 43%. EC and OCEC followed with 32. and 2.%, respectively. Nitrate and ammonium traces between particle groups had negligible variance, while sulfate was found to prefer to associate with OC and OCEC rather than EC. The influence of aerodynamic diameter was substantial for mixing {2.s with nitrate and ammonium, with ratios lower in the condensation mode than droplet mode;whereas sulfate mixing ratios were nearly constant within 0.2.1.2.μm. Biomass burning particles were clustered into six distinct particle groups, comprising of Ca-rich, Na-rich, organic carbon (OC), elemental carbon (EC), the mixture of OC and EC (OCEC) and Secondary. OC was the largest contributor with a fraction of 2..9%, followed by Secondary type (2..4%) and OCEC (19.0%). Na-rich type was observed in 11.9% of the particles and 90% internally mixed with EC. The fraction of nitrate in biomass burning particles was higher 10% than in carbonaceous particles, which could be explained by the fact that the rich sodium and potassium

关键词： Biomass burning carbonaceous aerosol mixing state single particle nitrate sulfate SPAMS ATOFMS aerosol PRD.

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分析测试学报 2004年第5期23卷 85-88页

作者：陈颖军盛国英李正悦毕新慧麦碧娴傅家谟中国科学院广州地球化学研究所有机地球化学国家重点实验室广东广州510640

以一种烟煤和一种无烟煤制成的蜂窝煤为研究对象 ,采用一套稀释采样系统同时采集蜂窝煤燃烧烟气中颗粒相和气相中的有机物 ,利用GC -MS对其中的多环芳烃(PAHs)进行定量研究并对比原煤的二氯甲烷抽提物 ,发现烟煤不仅在原煤中就含有比无... 详细信息

以一种烟煤和一种无烟煤制成的蜂窝煤为研究对象 ,采用一套稀释采样系统同时采集蜂窝煤燃烧烟气中颗粒相和气相中的有机物 ,利用GC -MS对其中的多环芳烃(PAHs)进行定量研究并对比原煤的二氯甲烷抽提物 ,发现烟煤不仅在原煤中就含有比无烟煤高出很多倍的PAHs和苯并(a)芘致癌性当量 ,而且在家用煤炉中燃烧后会产生更多的PAHs和致癌性 ;而无烟煤在燃烧后PAHs和毒性当量均会大大减少。燃煤烟气中以气相形态存在的PAHs在总量上占相当比例 ,但在致癌性当量上以颗粒相占主要部分。因此 ,在选择家用燃煤时除了要尽量使用无烟煤外。

关键词：家用燃煤多环芳烃苯并(a)芘致癌性当量气相颗粒相 GC-MS

AI for organic and polymer synthesis

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Science China Chemistry 2024年第8期67卷 2461-2496页

作者： xin Hong Qi Yang Kuangbiao liao Jianfeng Pei Mao Chen Fanyang Mo Hua Lu Wen-Bin Zhang Haisen Zhou Jiaxiao Chen Lebin Su Shuo-Qing Zhang Siyuan liu Xu Huang Yi-Zhou Sun Yuxiang wang Zexi Zhang Zhunzhun Yu Sanzhong Luo Xue-Feng Fu Shu-li You Center of Chemistry for Frontier Technologies Department of ChemistryZhejiang UniversityHangzhou 310027China Center of Basic Molecular Science Department of ChemistryTsinghua UniversityBeijing 100084China guangzhou National laboratory Guangzhou 510005China Center for Quantitative Biology Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijing 100871China state key {2. of Molecular Engineering of Polymers Department of Macromolecular ScienceFudan UniversityShanghai 200433China School of Materials Science and Engineering Peking UniversityBeijing 100871China Beijing National laboratory for Molecular sciences Center for Soft Matter Science and EngineeringKey Laboratory of Polymer Chemistry and Physics of Ministry of EducationCollege of Chemistry and Molecular EngineeringPeking UniversityBeijing 100871China AI for Science(AI4S)-Preferred Program Shenzhen Graduate SchoolPeking UniversityShenzhen 518055China state key {2. of Chemical Biology Shanghai Institute of Organic ChemistryUniversity of Chinese Academy of SciencesChinese Academy of SciencesShanghai 200032China department of Chemical sciences National Natural Science Foundation of ChinaBeijing 100085China state key {2. of Organometallic Chemistry Shanghai Institute of Organic ChemistryChinese Academy of SciencesShanghai 200032China

Recent years have witnessed the transformative impact from the integration of artificial intelligence with organic and polymer synthesis. This synergy offers innovative and intelligent solutions to a range of classic problems in synthetic chemistry. These exciting advancements include the prediction of molecular property, multi-step retrosynthetic pathway planning, elucidation of the structure-performance relationship of single-step transformation, establishment of the quantitative linkage between polymer structures and their functions, design and optimization of polymerization process, prediction of the structure and sequence of biological macromolecules, as well as automated and intelligent synthesis platforms. Chemists can now explore synthetic chemistry with unprecedented precision and efficiency, creating novel reactions, catalysts, and polymer materials under the datadriven paradigm. despite these thrilling developments, the field of artificial intelligence(AI) synthetic chemistry is still in its infancy, facing challenges and limitations in terms of data openness, model interpretability, as well as software and hardware support. This review aims to provide an overview of the current progress, key challenges, and future development suggestions in the interdisciplinary field between AI and synthetic chemistry. It is hoped that this overview will offer readers a comprehensive understanding of this emerging field, inspiring and promoting further scientific research and development.

关键词： organic synthesis polymer synthesis machine learning prediction chemical database automated synthesis

Ecology and risks of the global plastisphere as a newly expanding microbial habitat

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The Innovation 2024年第1期5卷 49-58页

作者： Changchao li Michael RGillings Chao Zhang Qinglin Chen Dong Zhu Jie wang Kankan Zhao Qicheng Xu Polly Hangmei Leung Xiangdong li Jian liu ling Jin department of Civil and Environmental Engineering The Hong Kong Polytechnic UniversityKowloonHong KongChina Environment Research institute Shandong UniversityQingdao 266237China state key {2. of Marine Pollution City University of Hong KongKowloon TongHong KongChina ARC Centre of Excellence in Synthetic Biology Faculty of Science and EngineeringMacquarie UniversitySydneyNSW 2109Australia key laboratory of Urban Environment and Health Ningbo Urban Environment Observation and Research StationInstitute of Urban EnvironmentChinese Academy of SciencesXiamen 361021China Beijing key laboratory of Farmland Soil Pollution Prevention and Remediation College of Resources and Environmental SciencesChina Agricultural UniversityBeijing 100193China institute of Soil and Water Resources and Environmental Science College of Environmental and Resource SciencesZhejiang UniversityHangzhou 310058China Jiangsu Collaborative Innovation Center for Solid organic Waste Resource Utilization Nanjing Agricultural UniversityNanjing 210095China department of Health Technology and Informatics and Research institute for Future Food The Hong Kong Polytechnic UniversityKowloonHong KongChina Southern Marine Science and Engineering Guangdong laboratory(guangzhou) Guangzhou 511458China

Plastic offers a new niche for microorganisms,the *** everincreasing emission of plastic waste makes it critical to understand the microbial ecology of the plastisphere and associated ***,we present a global fingerprint of the plastisphere,analyzing samples collected from freshwater,seawater,and terrestrial *** plastisphere assembles a distinct microbial community that has a clearly higher heterogeneity and a more deterministically dominated assembly compared to natural *** coexistence patterns—loose and fragile networks with mostly specia{2.st {2.nkages among microorganisms that are rarely found in natural habitats—are seen in the *** microbiomes generally have a great potential to metabo{2.ze organic compounds,which could accelerate carbon *** involved in the nitrogen cycle are also altered in the plastisphere,especially in freshwater plastispheres,where a high abundance of denitrifiers may increase the release of nitrite(aquatic toxicant)and nitrous oxide(greenhouse gas).Enrichment of animal,plant,and human pathogens means that the plastisphere could become an increasingly mobile reservoir of harmful *** findings high{2.ght that if the trajectory of plastic emissions is not reversed,the expanding plastisphere could pose critical planetary health challenges.

关键词： reservoir mostly habitat

Mixing states and secondary formation processes of {2. nitrogen-containing single particles in guangzhou,China

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Journal of Environmental sciences 2024年第4期138卷 62-73页

作者： lijun Yun Chunlei Cheng Suxia Yang Zaihua {2. Mei li Qi En Zhong liyuanMao Sulin liu Xiaoya Cheng Duanying Chen Fan Yang Zhen Zhou institute of Mass Spectrometry and Atmospheric Environment Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollutionJinan UniversityGuangzhou 510632China Guangdong-Hongkong-Macao Joint laboratory of Collaborative Innovation for Environmental Quality Guangzhou 510632China state key {2. of Loess and Quaternary Geology Institute of Earth EnvironmentChinese Academy ScienceXi’an 710061China institute for Environment and Climate Research Jinan UniversityGuangzhou 510632China Guangdong academy of sciences Institute of Resources Utilization and Rare Earth DevelopmentGuangzhou 510650China Environmental Monitoring Station of Pudong New District Shanghai 201200China

organic nitrogen(ON)compounds play a significant role in the light absorption of brown carbon and the formation of organic aerosols,however,the mixing state,secondary formation processes,and influencing factors of ON compounds are still *** paper reports on the mixing state of ON-containing particles based on measurements obtained using a highperformance single particle aerosol mass spectrometer in January 2.2. in *** ON-containing particles accounted for 2.% of the total detected single particles,and the particle count and number fraction of the ON-containing particles were two times higher at night than during the *** prominent increase in the content of ON-containing particles with the enhancement of NO_xmainly occurred at night,and accompanied by high relative humidity and nitrate,which were associated with heterogeneous reactions between organics and gaseous NO_(x)and/or NO_(3)*** synchronous decreases in ON-containing particles and the mass absorption coefficient of water-soluble extracts at 365 nm in the afternoon may be associated with photo-bleaching of the ON species in the *** addition,the positive matrix factorization analysis found five factors dominated the formation processes of ON particles,and the nitrate factor(33%)mainly contributed to the production of ON particles at *** results of this study provide unique insights into the mixing states and secondary formation processes of the ON-containing particles.

关键词： organic nitrogen compounds Single particles Mixing state Secondary formation Nighttime chemistry

珠三角夏秋转换季臭氧污染成因及前体物减排策略分析

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环境科学 2024年第10期45卷 5695-5705页

作者：尉晴晴杨威强裴成磊王新明广东轻工职业技术学院轻化工技术学院广州510300 广东省环境科学研究院广州510045 粤港澳生态环境科学中心大气光化学联合研究实验室广州510045 中国科学院广州地球化学研究所有机地球化学国家重点实验室广州510640 广东省广州生态环境监测中心站广州510060

为分析夏秋转换季珠三角地区臭氧(O_(3))污染成因及防控策略,以珠三角中心城市广州为例,在综合观测基础上,使用盒子模型分析O_(3)生消路径及减排方案.结果表明,观测期间呈静稳气象条件且温度偏高,非常适宜O_(3)的二次生成,并导致出现大... 详细信息

为分析夏秋转换季珠三角地区臭氧(O_(3))污染成因及防控策略,以珠三角中心城市广州为例,在综合观测基础上,使用盒子模型分析O_(3)生消路径及减排方案.结果表明,观测期间呈静稳气象条件且温度偏高,非常适宜O_(3)的二次生成,并导致出现大范围长时间O_(3)污染.芳香烃类物质对O_(3)生成潜势(OFP)贡献最大,间/对-二甲苯、甲苯和邻-二甲苯是对OFP贡献最大的挥发性有机物(VOCs)物种.盒子模型分析发现污染期间O_(3)平均净生成速率为2..2.10^(-9) h^(-1),峰值可高达39.2.10^(-9) h^(-1);HO_(2.·+NO和NO_(2.+·OH反应途径分别对本地光化学O_(3)生成(51.2.)和去除(47.0%)贡献率最大,观测O_(3)体积分数受本地光化学O_(3)生成和以输出性为主的传输共同控制.相对增量反应活性(RIR)和经验动力学模型曲线(EKMA)分析可知,夏秋转换季广州市O_(3)生成主要受VOCs控制,芳香烃类对O_(3)生成敏感性最大,其中甲苯、间/对-二甲苯、邻-二甲苯、正丁烷和丙烯是影响O_(3)生成的5大关键组分.削减情景分析表明,单独减少人为源VOCs排放最有利降低O_(3)体积分数,但若在减排人为源VOCs后再强化NO_(x)排放管控,则会使O_(3)体积分数短时反弹,结果表明实施以VOCs减排为主的VOCs和NO_(x)协同减排策略才能使未来O_(3)体积分数持续降低.

关键词：珠三角(PRD) 盒子模型臭氧(O_(3))成因挥发性有机物(VOCs) 减排分析