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Enhanced hydrogen evolution performance by 3D ordered macroporous Ru-CoP@NC electrocatalysts

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Rare Metals 2024年第3期43卷 1095-1107页

作者： chen-chen zhang Sheng Wei Li-Xian Sun Yi-Fang Ouyang Fen Xu Hai-Liang Chu Hong-GePan Li-Xin chen Xue-zhang Xiao School of Material Science and Engineering Guilin University of Electronic TechnologyGuilin541004China School of Chemistry and Chemical Engineering Guangxi UniversityNanning530004China Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhen518055GuangdongChina Institute of Science and Technology for New Energy Xi'an Technological UniversityXi'an710021China School of Materials Science and Engineering Zhejiang UniversityHangzhou310058China

Electrocatalytic water splitting coupled with sustainable energies is identified as an environmentally friendly and renewable strategy to generate high-quality hydrogen for the fuel ***,the main challenge is to develop high performance,low cost and chemically stable electrocatalysts to decline the energy barriers and enhance the sluggish kinetics of hydrogen evolution reaction(HER).Herein,a three-dimensional hierarchically ordered macroporous Ru-CoP@NC electrocatalyst(3DOM Ru-CoP@NC)derived from ordered macro-microporous metal-organic frameworks has been prepared using the precursor@template and double-solvent *** prepared 3DOM Ru-CoP@NC catalyst exhibits an overpotential of 15 mV(j=10 mA·cm^(-2))and a reaction Tafel slope of 38 mV·dec^(-1)in alkaline electrolyte,which are superior to commercial Pt@C ***,the overpotential and reaction Tafel slope of this catalyst in acidic media are 45 mV and 50 mV·dec^(-1),*** outstanding HER activities of 3DOM Ru-CoP@NC catalysts are ascribed to the 3D highly interconnectedreticular nanospaces that can increase effective reaction active *** N dope d carbon framework improves the electronic properties and ***,the strong interaction of Ru and CoP nanoparticles also boosts the HER *** results indicate that 3DOM Ru-CoP@NC catalysts with high catalytic activities have a broad application prospect in the future.

关键词： Hydrogen evolution reaction Template method 3D ordered macroporous Ru-CoP@NC

Automated Identification of Ordered Phases for Simulation Studies of Block Copolymers

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Chinese Journal of Polymer Science 2024年第5期42卷 683-692,I0011页

作者： Yu-chen zhang Wei-Ling Huang Yi-Xin Liu State Key Laboratory of Molecule Engineering of Polymers Department of Macromolecular ScienceFudan UniversityShanghai200433China

In unit cell simulations,identification of ordered phases in block copolymers(BCPs)is a tedious and time-consuming task,impeding the advancement of more streamlined and potentially automated research *** this study,we propose a scattering-based automated identification strategy(SAIS)for characterization and identification of ordered phases of BCPs based on their computed scattering *** approach leverages the scattering theory of perfect crystals to efficiently compute the scattering patterns of periodic morphologies in a unit *** the first stage of the SAIS,phases are identified by comparing reflection conditions at a sequence of Miller *** confirm or refine the identification results of the first stage,the second stage of the SAIS introduces a tailored residual between the test phase and each of the known candidate ***,our strategy incorporates a variance-like criterion to distinguish background species,enabling its extension to multi-species BCP *** has been demonstrated that our strategy achieves exceptional accuracy and robustness while requiring minimal computational ***,the approach allows for real-time expansion and improvement to the candidate phase library,facilitating the development of automated research workflows for designing specific ordered structures and discovering new ordered phases in BCPs.

关键词： Block copolymer Phase identification Scattering function

Theoretical understanding of correlation between magnetic phase transition and the superconducting dome in high-Tc cuprates

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Science China(Physics,Mechanics & Astronomy) 2024年第2期67卷 167-173页

作者： chen zhang Cai-Xin zhang Su-Huai Wei Haiqing Lin Hui-Xiong Deng State Key Laboratory of Superlattices and Microstructures Institute of SemiconductorsChinese Academy of SciencesBeijing 100083China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Beijing Computational Science Research Center Beijing 100193China

Many issues concerning the origin of high-temperature superconductivity(HTS)are still under *** example,how the magnetic order varies with doping and its relationship with the superconducting temperature(Tc);and why Tcalways peaks near the quantum critical *** this paper,taking hole-doped La_(2)CuO_(4)as a classical example,we employ the first-principles band structure and total energy calculations with Monte Carlo simulations to explore how the symmetry-breaking magnetic ground state evolves with hole doping and the origin of a dome-shaped superconductivity region in the phase *** demonstrate that the local antiferromagnetic order and doping play key roles in determining the electron-phonon coupling,thus ***,the La_(2)CuO_(4)possesses a checkerboard local antiferromagnetic ground *** the hole doping increases,Tcincreases with the enhanced electron-phonon coupling *** as the doping increases further,the strength of the antiferromagnetic interaction weakens and spin fluctuation *** the critical doping level,a magnetic phase transition occurs that reduces the local antiferromagnetism-assisted electron-phonon coupling,thus diminishing the *** superconductivity disappears in the heavily overdoped region when the ferromagnetic order *** observations could account for why cuprates have a dome-shaped superconductivity region in the phase *** study,thus,contributes to a fundamental understanding of the correlation between doping,local magnetic order,and superconductivity of HTS.

关键词： high-temperature superconductivity antiferromagnetic order electron-phonon coupling doping effect cuprates

ConvNeXt-UperNet-Based Deep Learning Model for Road Extraction from High-Resolution Remote Sensing Images

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Computers, Materials & Continua 2024年第8期80卷 1907-1925页

作者： Jing Wang chen zhang Tianwen Lin Geographic Information and Tourism College Chuzhou UniversityChuzhou239000China Anhui Province Key Laboratory of Physical Geographic Environment Chuzhou UniversityChuzhou239000China

When existing deep learning models are used for road extraction tasks from high-resolution images,they are easily affected by noise factors such as tree and building occlusion and complex backgrounds,resulting in incomplete road extraction and low *** propose the introduction of spatial and channel attention modules to the convolutional neural network ***,ConvNeXt is used as the backbone network,which cooperates with the perceptual analysis network UPerNet,retains the detection head of the semantic segmentation,and builds a new model ConvNeXt-UPerNet to suppress noise *** on the open-source DeepGlobe and CHN6-CUG datasets and introducing the DiceLoss on the basis of CrossEntropyLoss solves the problem of positive and negative sample *** results show that the new network model can achieve the following performance on the DeepGlobe dataset:79.40%for precision(Pre),97.93% for accuracy(Acc),69.28% for intersection over union(IoU),and 83.56% for mean intersection over union(MIoU).On the CHN6-CUG dataset,the model achieves the respective values of 78.17%for Pre,97.63%for Acc,65.4% for IoU,and 81.46% for *** with other network models,the fused ConvNeXt-UPerNet model can extract road information better when faced with the influence of noise contained in high-resolution remote sensing *** also achieves multiscale image feature information with unified perception,ultimately improving the generalization ability of deep learning technology in extracting complex roads from high-resolution remote sensing images.

关键词： Deep learning semantic segmentation remote sensing imagery road extraction

Click chemistry and natural products

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Chinese Journal of Natural Medicines 2024年第2期22卷 97-99页

作者： zhang chen WU Jianbing zhang Yihua HUANG zhangjian State Key Laboratory of Natural Medicines Jiangsu Key Laboratory of Drug Discovery for Metabolic DiseasesCenter of Drug DiscoveryChina Pharmaceutical UniversityNanjing 210009China State Key Laboratory of Pathogenesis Prevention and Treatment of High Incidence Diseases in Central AsiaXinjiang Key Laboratory of Natural Medicines Active Components and Drug Release TechnologySchool of PharmacyXinjiang Medical UniversityUrumqi 830054China

The 2022 Nobel Prize in Chemistry was awarded to American scientists Carolyn Bertozzi,*** Sharpless,and Danish scientist Morten *** for their contributions to the development of click chemistry and bioorthogonal chemi... 详细信息

关键词： Click chemistry Natural product Target identification Drug discovery

Rapid characterization of non-volatile phenolic compounds reveals the reliable chemical markers for authentication of traditional Chinese medicine Xiang-ru among confusing Elsholtzia species

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Chinese Journal of Natural Medicines 2024年第4期22卷 375-384页

作者： ZENG Zhen zhang chen HU Jiadong WANG Feiyan WU Ziding WANG Jing zhang Jun YANG Shuda chen Junfeng LI Mingming TONG Qi QIU Shi chen Wansheng The SATCM Key Laboratory for New Resources&Quality Evaluation of Chinese Medicine Institute of Chinese Materia MedicaShanghai University of Traditional Chinese MedicineShanghai 201203China Department of Pharmacy Second Affiliated Hospital of Navy Medical UniversityShanghai 200003China Kunming Plant Classification Biotechnology Co. Ltd.Kunming 650500China School of Pharmaceutical Sciences and Yunnan Key Laboratory of Pharmacology for Natural Products Kunming Medical UniversityKunming 650500China State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs Beijing100700China

The aerial parts of Mosla chinensis *** Mosla chinensis cv.'Jiangxiangru'(MCJ)are widely utilized in traditional Chinese medicine(TCM),known collectively as ***,due to clinical effectiveness concerns and frequent misidentification,the original plants have increasingly been substituted by various species within the genera Elsholtzia and *** challenge in distinguishing between these genera arises from their similar morphological and metabolic *** address this issue,our study introduced a rapid method for metabolic characterization,employing high-resolution mass spectrometry-based *** detailed biosynthetic and chemometric analyses,we pinpointed five phenolic compounds—salviaflaside,cynaroside,scutellarein-7-O-D-glucoside,rutin,and vicenin-2—among 203 identified compounds,as reliable chemical markers for distinguishing Xiang-ru from closely related Elsholtzia *** methodology holds promise for broad application in the analysis of plant aerial parts,especially in verifying the authenticity of aromatic traditional medicinal *** findings underscore the importance of non-volatile compounds as dependable chemical markers in the authentication process of aromatic traditional medicinal plants.

关键词： Genus Elsholtzia Genus Mosla Traditional Chinese medicine Xiang-ru Non-volatile phenolic compounds Liquid chromatography-mass spectrometry

Quantitative prediction model for the depth limit of oil accumulation in the deep carbonate rocks:A case study of Lower Ordovician in Tazhong area of Tarim Basin

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Petroleum Science 2024年第1期21卷 115-124页

作者： Wen-Yang Wang Xiong-Qi Pang Ya-Ping Wang zhang-Xin chen Fu-Jie Jiang Ying chen State Key Laboratory of Lithospheric Evolution Institute of Geology and GeophysicsChinese Academy of SciencesBeijing100029China State Key Laboratory of Petroleum Resources and Prospecting China University of Petroleum(Beijing)Beijing102249China College of Geosciences China University of Petroleum(Beijing)Beijing102249China Research Institute of Exploration and Development PetroChina Southwest Oil&Gas Field CompanyChengdu610041SichuanChina Chemical and Petroleum Engineering Schulich School of EngineeringUniversity of CalgaryCalgaryT2N 1N4Canada

With continuous hydrocarbon exploration extending to deeper basins,the deepest industrial oil accumulation was discovered below 8,200 m,revealing a new exploration ***,the extent to which oil exploration can be extended,and the prediction of the depth limit of oil accumulation(DLOA),are issues that have attracted significant attention in petroleum *** it is difficult to characterize the evolution of the physical properties of the marine carbonate reservoir with burial depth,and the deepest drilling still cannot reach the ***,the DLOA cannot be predicted by directly establishing the relationship between the ratio of drilling to the dry layer and the *** this study,by establishing the relationships between the porosity and the depth and dry layer ratio of the carbonate reservoir,the relationships between the depth and dry layer ratio were obtained *** depth corresponding to a dry layer ratio of 100%is the *** on this,a quantitative prediction model for the DLOA was finally *** results indicate that the porosity of the carbonate reservoir,Lower Ordovician in Tazhong area of Tarim Basin,tends to decrease with burial depth,and manifests as an overall low porosity reservoir in deep *** critical porosity of the DLOA was 1.8%,which is the critical geological condition corresponding to a 100%dry layer ratio encountered in the *** depth of the DLOA was 9,000 *** study provides a new method for DLOA prediction that is beneficial for a deeper understanding of oil accumulation,and is of great importance for scientific guidance on deep oil drilling.

关键词： Deep layer Tarim Basin Hydrocarbon accumulation Depth limit of oil accumulation Prediction model

An Opposition-Based Learning-Based Search Mechanism for Flying Foxes Optimization Algorithm

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Computers, Materials & Continua 2024年第6期79卷 5201-5223页

作者： chen zhang Liming Liu Yufei Yang Yu Sun Jiaxu Ning Yu zhang Changsheng zhang Ying Guo Software College Northeastern UniversityShenyang110169China School of Information Science and Engineering Shenyang Ligong UniversityShenyang110159China China Telecom Digital Intelligence Technology Co. Ltd.Beijing100035China College of Computer Science and Engineering Ningxia Institute of Science and TechnologyShizuishan753000China

The flying foxes optimization(FFO)algorithm,as a newly introduced metaheuristic algorithm,is inspired by the survival tactics of flying foxes in heat wave *** preferentially selects the best-performing *** tendency will cause the newly generated solution to remain closely tied to the candidate optimal in the search *** address this issue,the paper introduces an opposition-based learning-based search mechanism for FFO algorithm(IFFO).Firstly,this paper introduces niching techniques to improve the survival list method,which not only focuses on the adaptability of individuals but also considers the population’s crowding degree to enhance the global search ***,an initialization strategy of opposition-based learning is used to perturb the initial population and elevate its ***,to verify the superiority of the improved search mechanism,IFFO,FFO and the cutting-edge metaheuristic algorithms are compared and analyzed using a set of test *** results prove that compared with other algorithms,IFFO is characterized by its rapid convergence,precise results and robust stability.

关键词： Flying foxes optimization(FFO)algorithm opposition-based learning niching techniques swarm intelligence metaheuristics evolutionary algorithms

FIBTNet: Building Change Detection for Remote Sensing Images Using Feature Interactive Bi-Temporal Network

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Computers, Materials and Continua 2024年第3期80卷 4621-4641页

作者： Wang, Jing Lin, Tianwen zhang, chen Peng, Jun School of Geographic Information and Tourism Chuzhou University Chuzhou 239000 China Anhui Province Key Laboratory of Physical Geographic Environment Chuzhou University Chuzhou 239000 China

In this paper, a feature interactive bi-temporal change detection network (FIBTNet) is designed to solve the problem of pseudo change in remote sensing image building change detection. The network improves the accuracy of change detection through bi-temporal feature interaction. FIBTNet designs a bi-temporal feature exchange architecture (EXA) and a bi-temporal difference extraction architecture (DFA). EXA improves the feature exchange ability of the model encoding process through multiple space, channel or hybrid feature exchange methods, while DFA uses the change residual (CR) module to improve the ability of the model decoding process to extract different features at multiple scales. Additionally, at the junction of encoder and decoder, channel exchange is combined with the CR module to achieve an adaptive channel exchange, which further improves the decision-making performance of model feature fusion. Experimental results on the LEVIR-CD and S2Looking datasets demonstrate that iCDNet achieves superior F1 scores, Intersection over Union (IoU), and Recall compared to mainstream building change detection models, confirming its effectiveness and superiority in the field of remote sensing image change detection. Copyright © 2024 The Authors. Published by Tech Science Press.

关键词： Change detection