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Roadmap for rechargeable batteries:present and beyond

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

作者： Sen Xin Xu Zhang Lin Wang Haijun Yu Xin Chang Yu-Ming Zhao Qinghai Meng Pan Xu chen-Zi Zhao Jiahang chen Huichao Lu Xirui Kong Jiulin Wang 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 Wang 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 Laboratory 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 Laboratory 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 change.Due 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 batteries.Tremendous 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 batteries.Despite 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 battery.This roadmap tends to provide an overview about the current research progress,key challenges and future prospects of various types of rechargeable batteries.New 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

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Link Prediction Method Fusion with Local Structural Entropy for Directed Network

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Chinese Journal of Electronics 2024年第1期33卷 204-216页

作者： Shuxin LIU Hongchang chen Lan WU kai WANG Xing LI People’s Liberation Army Strategic Support Force Information Engineering University

Link prediction utilizes accessible network information to complement or predict the network links.Similarity is an important prerequisite for link prediction which means links more likely occurs between two similar nodes. Existing methods utilize the similarity of nodes but neglect of network structure. However the link direction leads to a far more complex structure and contains more information useful than the undirected networks. Most classic methods are difficult to depict the distribution of the network structure with incidental direction so the similarity characteristics of the network structure itself are lost. In this respect, a new method of local structure entropy is proposed to depict the directed structural distribution characteristics, which can be used to evaluate the degree of local structural similarity of nodes and then applied to link prediction methods. Experimental results on 8 real directed networks show that this method is effective for both area under the receiver operating characteristic curve(AUC)and ranking-score measures, and improved predictive capacity of the baseline methodology.

关键词： Local structural entropy Structural complexity Similar nodes Link prediction

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Sound event localization and detection based on deep learning

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Journal of Systems Engineering and Electronics 2024年第2期35卷 294-301页

作者： ZHAO Dada DING kai QI Xiaogang chen Yu FENG Hailin School of Mathematics and Statistics Xidian UniversityXi’an 710071China Science and Technology on Near-Surface Detection Laboratory Wuxi 214035China

Acoustic source localization(ASL)and sound event detection(SED)are two widely pursued independent research fields.In recent years,in order to achieve a more complete spatial and temporal representation of sound field,sound event localization and detection(SELD)has become a very active research topic.This paper presents a deep learning-based multioverlapping sound event localization and detection algorithm in three-dimensional space.Log-Mel spectrum and generalized cross-correlation spectrum are joined together in channel dimension as input features.These features are classified and regressed in parallel after training by a neural network to obtain sound recognition and localization results respectively.The channel attention mechanism is also introduced in the network to selectively enhance the features containing essential information and suppress the useless features.Finally,a thourough comparison confirms the efficiency and effectiveness of the proposed SELD algorithm.Field experiments show that the proposed algorithm is robust to reverberation and environment and can achieve higher recognition and localization accuracy compared with the baseline method.

关键词： sound event localization and detection(SELD) deep learning convolutional recursive neural network(CRNN) channel attention mechanism

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Quantum Spin Exchange Interactions to Accelerate the Redox Kinetics in Li–S Batteries

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Nano-Micro Letters 2024年第5期16卷 370-383页

作者： Yu Du Weijie chen Yu Wang Yue Yu kai Guo Gan Qu Jianan Zhang Key Laboratory of Advanced Energy Catalytic and Functional Materials Preparation of Zhengzhou City College of Materials Science and EngineeringZhengzhou UniversityZhengzhou 450001People’s Republic of China

Spin-engineering with electrocatalysts have been exploited to suppress the“shuttle effect”in Li–S batteries.Spin selec-tion,spin-dependent electron mobility and spin potentials in activation barriers can be optimized as quantum spin exchange interactions lead-ing to a significant reduction of the electronic repulsions in the orbitals of catalysts.Herein,we anchor the MgPc molecules on fluorinated carbon nanotubes(MgPc@FCNT),which exhibits the single active Mg sites with axial displacement.According to the density functional theory calculations,the electronic spin polarization in MgPc@FCNT not only increases the adsorption energy toward LiPSs intermediates but also facilitates the tunneling process of electron in Li–S batter-ies.As a result,the MgPc@FCNT provides an initial capacity of 6.1 mAh cm^(-2) even when the high sulfur loading is 4.5 mg cm^(-2),and still maintains 5.1 mAh cm^(-2) after 100 cycles.This work provides a new perspective to extend the main group single-atom catalysts enabling high-performance Li–S batteries.

关键词： Metal phthalocyanines Spin polarization Electrocatalysis Li–S batteries

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Causal roles of gut microbiota in cholangiocarcinoma etiology suggested by genetic study

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World Journal of Gastrointestinal Oncology 2024年第4期16卷 1319-1333页

作者： Zhi-Tao chen chen-chen Ding kai-Lei chen Yang-Jun Gu Chi-cheng Lu Qi-Yong Li Division of Hepatobiliary and Pancreatic Surgery Shulan(Hangzhou)Hospital Affiliated to Zhejiang Shuren University Shulan International Medical CollegeHangzhou 310000Zhejiang ProvinceChina Pediatric Psychology The Affiliated Mental Health Centre&Hangzhou Seventh People’s HospitalZhejiang University School of MedicineHangzhou 310000Zhejiang ProvinceChina School of Medicine Zhejiang Shuren UniversityHangzhou 310000Zhejiang ProvinceChina School of Medicine Zhejiang Chinese Medical University Zhejiang Shuren CollegeHangzhou 310000Zhejiang ProvinceChina

BACKGROUND Cholangiocarcinoma(CCA)is a highly malignant biliary tract cancer with poor prognosis.Previous studies have implicated the gut microbiota in CCA,but evidence for causal mechanisms is lacking.AIM To investigate the causal relationship between gut microbiota and CCA risk.METHODS We performed a two-sample mendelian randomization study to evaluate potential causal associations between gut microbiota and CCA risk using genome-wide association study summary statistics for 196 gut microbial taxa and CCA.Genetic variants were used as instrumental variables.Multiple sensitivity analyses assessed result robustness.RESULTS Fifteen gut microbial taxa showed significant causal associations with CCA risk.Higher genetically predicted abundance of genus Eubacteriumnodatum group,genus Ruminococcustorques group,genus Coprococcus,genus Dorea,and phylum Actinobacteria were associated with reduced risk of gallbladder cancer and extrahepatic CCA.Increased intrahepatic CCA risk was associated with higher abundance of family Veillonellaceae,genus Alistipes,order Enterobacteriales,and phylum Firmicutes.Protective effects against CCA were suggested for genus Collinsella,genus Eisenbergiella,genus Anaerostipes,genus Paraprevotella,genus Parasutterella,and phylum Verrucomicrobia.Sensitivity analyses indicated these findings were reliable without pleiotropy.CONCLUSION This pioneering study provides novel evidence that specific gut microbiota may play causal roles in CCA risk.Further experimental validation of these candidate microbes is warranted to consolidate causality and mechanisms.

关键词： Cholangiocarcinoma Mendelian randomization Gut microbiota Instrumental variables Sensitivity analyses

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Research progress on intelligent operation and maintenance of bridges

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Journal of Traffic and Transportation Engineering(English Edition) 2024年第2期11卷 173-187页

作者： Wanshui Han Gan Yang Shizhi chen kai Zhou Xin Xu School of Highway Chang'an UniversityXi'an 710064China

In the context of the increasing scale of bridges and the increasing service life of bridges,it is very important to carry out efficient,accurate and intelligent bridge operation and maintenance.In recent years,advanced equipment,technology and intelligent algorithms have developed rapidly.It is necessary to apply advanced equipment and algorithms to bridge operation and maintenance business to facilitate the digitalization and intelligence of bridge operation and maintenance.To grasp the research progress on the bridge intelligent operation and maintenance,this paper summarizes the research progress in recent years from the aspects of intelligent detection equipment and technology,intelligent monitoring equipment and technology,intelligent data analysis,intelligent evaluation and early warning,and intelligent repair and maintenance.According to the review,more and more smart devices have been used to replace human beings to detect dangerous and hidden bridge components.At the same time,image processing,radar and other technologies have been used to analyze component damage more objectively and quantitatively.To solve the shortcomings of traditional sensors such as short life and low robustness,more non-contact measurement methods have been proposed.Scholars have proposed various intelligent algorithms to process the massive amount of bridge health monitoring data to improve the quality of the data.To achieve the rapid perception of bridge status and timely early warning of structural abnormalities,different from traditional theoretical calculations,scholars have tried to use data-driven methods to intelligently evaluate and early warning of bridge structural status.In terms of intelligent repair and maintenance,more intelligent algorithms have been used to optimize structural maintenance strategies and determine the best maintenance time by integrating multisource heterogeneous data.All these provide strong support for the automation,digitization and intelligence of bridge operation and maintenance.

关键词： Bridge engineering Bridge intelligent operation and maintenance Intelligent equipment Technology and algorithms

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A data-driven method for feature assessment of historical settlements: A case study of Northeast Hubei, China

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Frontiers of Architectural Research 2024年第2期13卷 387-405页

作者： Gangyi Tan Zhanxiang chen Jiangkun Zhu kai Wang School of Architecture&Urban Planning Huazhong University of Science and TechnologyWuhan 430074China Hubei Engineering and Technology Research Center of Urbanization Wuhan 430074China Hubei Rural Construction Center Wuhan 430074China HUST Built Heritage Research Center Wuhan 430074China

Formulating criteria for the assessment system of historic settlements is challenging due to complex geographical conditions and evaluator knowledge limitations, leading to subjective bias in the assessment process. To address this issue, this study proposes a data-driven method for assessing the features of historical settlements to carry out scientific and refined assessment and result analysis. Focusing on Northeast Hubei as the study area, this paper selects 3 historical settlements for validation and analysis. The results of the study show that (1) the data-driven method expands the methodological chain of assessing historical settlement features, and improves the assessment efficiency and scientificity of the assessment results by applying it to the new assessment process;(2) Through comparing the assessment results of the validation cases and data samples, the study establishes a comprehensive quantitative ranking of the assessment of historical settlement features and identifies the main influencing factors, thus enhancing the precision of result analysis;(3) By comparing the resulting assessment framework with the current assessment system, this study confirms the advantages of the proposed framework in identifying nuanced features and aligning with geographical conditions, thereby verifying the effectiveness of the data-driven method.

关键词： Historical settlement Feature assessment Data-driven method Northeast Hubei

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Synthesis of uniform two-dimensional MoS_(2) films via thermal evaporation

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Nano Research 2024年第4期17卷 3217-3223页

作者： Xue-Wei Lu Zhewei Li chen-kai Yang Weijia Mou Liying Jiao Key Laboratory of Organic Optoelectronics and Molecular Engineering of the Ministry of Education Department of ChemistryTsinghua UniversityBeijing 100084China

Two-dimensional(2D)molybdenum disulfide(MoS_(2))holds great potential for various applications such as electronic devices,catalysis,lubrication,anti-corrosion and so on.Thermal evaporation is a versatile thin film deposition technique,however,the conventional thermal evaporation techniques face challenges in producing uniform thin films of MoS_(2) due to its high melting temperature of 1375℃.As a result,only thick and rough MoS_(2) films can be obtained using these methods.To address this issue,we have designed a vacuum thermal evaporation system specifically for large-scale preparation of MoS_(2) thin films.By using K2MoS4 as the precursor,we achieved reliable deposition of uniform polycrystalline MoS_(2) thin films with a size of 50 mm×50 mm and controllable thickness ranging from 0.8 to 2.4 nm.This approach also allows for patterned deposition of MoS_(2) using shadow masks and sequential deposition of MoS_(2) and tungsten disulfide(WS_(2)),similar to conventional thermal evaporation techniques.Moreover,we have demonstrated the potential applications of the obtained MoS_(2) thin films in field effect transistors(FETs),memristors and electrocatalysts for hydrogen evolution reaction(HER).

关键词： thermal evaporation molybdenum disulfide two-dimensional memristors hydrogen evolution reaction

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KLF4 Inhibits the Activation of Human Hepatic Stellate Cell In Vitro

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Current Medical Science 2024年第3期44卷 512-518页

作者： Xing-yu YANG Zhe chen Jun TAN Yin-kai XUE Hai ZHENG Department of Emergency Surgery Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan430022China Department of Thoracic Surgery The First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an710061China Department of Thoracic Surgery Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan430022China

Objective Hepatic stellate cells(HSCs)play a crucial role in liver fibrosis.Early-stage liver fibrosis is reversible and intimately associated with the state of HSCs.Kruppel-like factor 4(KLF4)plays a pivotal role in a wide array of physiological and pathological processes.This study aimed to investigate the effect of KLF4 on the proliferation,apoptosis and phenotype of quiescent HSCs Methods We designed a KLF4 lentiviral vector and a KLF4 siRNA lentiviral vector,to upregulate and silence KLF4 expression in human HSC LX-2 cells via transfection.Cell proliferation was assessed using the CCK-8 assay.Flow cytometry was used to detect the cell cycle distribution and apoptosis rate.Western blotting was used to determine the levels of some quiescence and activation markers of HSCs Results Overexpression of KLF4 significantly increased the levels of E-cadherin and ZO-1,which are quiescent HSC markers,while significantly decreased the levels of N-cadherin and a-SMA,known activated HSC markers.In contrast,cell proliferation and apoptosis rates were elevated in LX-2 cells in which KLF4 expression was silenced Conclusion KLF4 inhibits the proliferation and activation of human LX-2 HSCs.It might be a key regulatory protein in the maintenance of HSC quiescence and may serve as a target for the inhibition of hepatic fibrosis.

关键词： Kruppel-like factor 4 hepatic stellate cells LX-2 cells liver fibrosis

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Quantum Neural Network for Quantum Neural Computing

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Research 2024年第1期2023卷 71-80页

作者： Min-Gang Zhou Zhi-Ping Liu Hua-Lei Yin chen-Long Li Tong-kai Xu Zeng-Bing chen National Laboratory of Solid State Microstructures School of PhysicsCollaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210093China MatricTime Digital Technology Co.Ltd. Nanjing 211899China

Neural networks have achieved impressive breakthroughs in both industry and academia.How to effectively develop neural networks on quantum computing devices is a challenging open problem.Here,we propose a new quantum neural network model for quantum neural computing using(classically controlled)single-qubit operations and measurements on real-world quantum systems with naturally occurring environment-induced decoherence,which greatly reduces the difficulties of physical implementations.Our model circumvents the problem that the state-space size grows exponentially with the number of neurons,thereby greatly reducing memory requirements and allowing for fast optimization with traditional optimization algorithms.We benchmark our model for handwritten digit recognition and other nonlinear classification tasks.The results show that our model has an amazing nonlinear classification ability and robustness to noise.Furthermore,our model allows quantum computing to be applied in a wider context and inspires the earlier development of a quantum neural computer than standard quantum computers.

关键词： quantum thereby breakthrough

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