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Aerodynamic Optimization and Flow Mechanism for a Compressor Cascade at Low Reynolds Number

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Journal of Thermal Science 2025年第1期34卷 92-109页

作者： LI lin ZHANG Jianshe CHEN Caiyan TAN Wei ZHANG Yanfeng Key Laboratory of Light-Duty Gas-Turbine Institute of Engineering ThermophysicsChinese Academy of Sciences University of Chinese Academy of Sciences National Key Laboratory of Science and Technology on Advanced Light-duty Gas-turbine

Low-Reynolds-number effect is an important factor affecting the performance of compressors and other main components of high-altitude long-endurance unmanned aerial *** improve the flow condition and reduce flow loss under the condition of high altitude and low Reynolds number(Re),this paper proposes an optimization process based on a surrogate model,which combines the class-shape transformation method(CST),the Latin hypercube sampling(LHS) method,the light gradient-boosting machine algorithm(LightGBM),and a genetic algorithm(GA) to optimize a high-subsonic compressor *** surrogate model is verified to be accurate and can be used in the optimization *** accuracy of the GA is higher than the other algorithms under common test *** optimization results are verified by numerical simulation,and the flow differences before and after optimization are compared,especially the flow within the boundary *** changing the blade shape,the optimization process adjusts the loading distribution to delay the transition of the optimized blade on the suction surface,which changes the turbulent reattachment in the laminar separation bubble(LSB) into laminar ***,the mixing loss induced by the turbulent reattachment of the LSB and the wake loss of turbulent separation at the trailing edge are significantly reduced,and the performance of the compressor profile is finally *** addition,turbulent separation of the optimized profile is delayed reducing the range of the wake region on the suction *** this optimization process,the reduction of total pressure loss coefficient at Re of 2.5×10～5,3.5×10～5,and 4.5×10～5 are 16.32%,20.76%,and 22.16%,respectively.

关键词： Reynolds number

Boosting bidirectional sulfur conversion enabled by introducing boron-doped atoms and phosphorus vacancies in Ni2P for lithium-sulfur batteries

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Journal of Energy Chemistry 2025年第1期100卷 760-769页

作者： lin Peng Yu Bai Hang Li Meixiu Qu Zhenhua Wang Kening Sun Advanced Research Institute of Multidisciplinary Science Beijing Institute of Technology Beijing Key Laboratory of Chemical Power Source and Green Catalysis School of Chemistry and Chemical Engineering Beijing Institute of Technology

Lithium-sulfur （Li-S） batteries have gained great attention due to the high theoretical energy density and low cost,yet their further commercialization has been obstructed by the notorious shuttle effect and sluggish redox ***,we supply a strategy to optimize the electron structure of Ni2P by concurrently introducing B-doped atoms and P vacancies in Ni2P （Vp-B-Ni2P）,thereby enhancing the bidirectional sulfur *** study indicates that the simultaneous introduction of B-doped atoms and P vacancies in Ni2P causes the redistribution of electron around Ni atoms,bringing about the upward shift of d-band center of Ni atoms and effective d-p orbital hybridization between Ni atoms and sulfur species,thus strengthening the chemical anchoring for lithium polysulfides （LiPSs） as well as expediting the bidirectional conversion kinetics of sulfur ***,theoretical calculations reveal that the incorporation of B-doped atoms and P vacancies in Ni2P selectively promotes Li2S dissolution and nucleation ***,the Li-S batteries with Vp-B-Ni2P-separators present outstanding rate ability of 777 m A h g-1at 5 C and high areal capacity of 8.03 mA h cm-2under E/S of 5μL mg-1and sulfur loading of 7.20 mg *** work elucidates that introducing heteroatom and vacancy in metal phosphide collaboratively regulates the electron structure to accelerate bidirectional sulfur conversion.

关键词： Lithium sulfur batteries

Electrocatalytic cleavage of a lignin β-O-4 model compound and coupling with nitrogen-containing aromatics using Prussian blue analogue-derived nickel–cobalt spinel

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Journal of Energy Chemistry 2025年第1期100卷 628-636页

作者： Yi Qi Xueying Chen Bowen Liu Xuliang lin Xueqing Qiu Yanlin Qin Guangdong Provincial Key Laboratory of Plant Resources Biorefinery School of Chemical Engineering and Light Industry Guangdong University of Technology Guangdong Provincial Laboratory of Chemistry and Fine Chemical Engineering Jieyang Center Guangdong Basic Research Center of Excellence for Ecological Security and Green Development Guangdong University of Technology

Electrochemical conversion of lignin for the production of high-value heterocyclic aromatic compounds has great *** demonstrate the targeted synthesis and cation modulation of NiCo2O4spinel nanoboxes,synthesized via cation exchange and calcination *** catalysts exhibit excellent efficacy in the electrocatalytic conversion of lignin model compounds,specifically 2-phenoxy-1-phenylethanol,into nitrogen-containing aromatics,achieving high conversion rates and *** catalysts were synthesized via a cation exchange and calcination oxidation process,using Prussian blue nanocubes as *** porous architecture and polymetallic composition of the NiCo2O4spinel demonstrated superior performance in electrocatalytic oxidative coupling,achieving a 99.2 wt%conversion rate of the 2-phenoxy-1-phenylethanol with selectivities of 37.5 wt%for quinoline derivatives and 31.5 wt%for *** innovations include the development of a sustainable one-pot synthesis method for quinoline derivatives,the elucidation of a multistage reaction pathway involving CAO bond cleavage,hydroxyaldol condensation,and CAN bond formation,and a deeper mechanistic understanding derived from DFT *** work establishes a new strategy for lignin valorization,offering a sustainable route to produce high-value nitrogen-containing aromatics from renewable biomass under mild conditions,without the need for additional reagents.

关键词： Spinel Biomass valorization Electrocatalysis Lignin oxidation Coupling

Wafer‑Scale Vertical 1D GaN Nanorods/2D MoS_(2)/PEDOT:PSS for Piezophototronic Effect‑Enhanced Self‑Powered Flexible Photodetectors

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Nano-Micro Letters 2025年第3期17卷 102-116页

作者： Xin Tang Hongsheng Jiang Zhengliang lin Xuan Wang Wenliang Wang Guoqiang Li State Key Laboratory of Luminescent Materials and Devices South China University of TechnologyGuangzhou 510640People’s Republic of China Department of Electronic Materials School of Materials Science and EngineeringSouth China University of TechnologyGuangzhou 510640People’s Republic of China

van der Waals(vdW)heterostructures constructed by lowdimensional(0D,1D,and 2D)materials are emerging as one of the most appealing systems in next-generation flexible ***,hand-stacked vdW-type photodetectors are not compatible with large-areaarray fabrication and show unimpressive performance in self-powered ***,vertical 1D GaN nanorods arrays(NRAs)/2D MoS_(2)/PEDOT:PSS in wafer scale have been proposed for self-powered flexible photodetectors arrays *** as-integrated device without external bias under weak UV illumination exhibits a competitive responsivity of 1.47 A W^(−1)and a high detectivity of 1.2×10^(11)Jones,as well as a fast response speed of 54/71μs,thanks to the strong light absorption of GaN NRAs and the efficient photogenerated carrier separation in type-II ***,the strain-tunable photodetection performances of device have been ***,the device at−0.78%strain and zero bias reveals a significantly enhanced photoresponse with a responsivity of 2.47 A W^(−1),a detectivity of 2.6×10^(11)Jones,and response times of 40/45μs,which are superior to the state-of-the-art self-powered flexible *** work presents a valuable avenue to prepare tunable vdWs heterostructures for self-powered flexible photodetection,which performs well in flexible sensors.

关键词： Vertical nanorod arrays van der Waals heterostructure Piezophototronic effect Self-powered photodetection Flexible sensors

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PD-YOLO:Colon Polyp Detection Model Based on Enhanced Small-Target Feature Extraction

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Computers, Materials & Continua 2025年第1期82卷 913-928页

作者： Yicong Yu Kaixin lin Jiajun Hong Rong-Guei Tsai Yuanzhi Huang New Engineering Industry College Putian UniversityPutian351100China Engineering Research Center of Big Data Application in Private Health Medicine(Putian University) Fujian Province UniversityPutian351100China Computer College Guangdong University of Science&TechnologyDongguan523668China

In recent years,the number of patientswith colon disease has increased *** polyps are the precursor lesions of colon *** not diagnosed in time,they can easily develop into colon cancer,posing a serious threat to patients’lives and health.A colonoscopy is an important means of detecting colon ***,in polyp imaging,due to the large differences and diverse types of polyps in size,shape,color,etc.,traditional detection methods face the problem of high false positive rates,which creates problems for doctors during the diagnosis *** order to improve the accuracy and efficiency of colon polyp detection,this question proposes a network model suitable for colon polyp detection(PD-YOLO).This method introduces the self-attention mechanism CBAM(Convolutional Block Attention Module)in the backbone layer based on YOLOv7,allowing themodel to adaptively focus on key information and ignore the unimportant *** help themodel do a better job of polyp localization and bounding box regression,add the SPD-Conv(Symmetric Positive Definite Convolution)module to the neck layer and use deconvolution instead of *** results indicate that the PD-YOLO algorithm demonstrates strong robustness in colon polyp *** to the original YOLOv7,on the Kvasir-SEG dataset,PD-YOLO has shown an increase of 5.44 percentage points in AP@0.5,showcasing significant advantages over other mainstream methods.

关键词： Polyp detection YOLOv7 SPD-Conv CBAM deconvolution

A facile route to tungsten oxide nanomaterials with controlled morphology and structure

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Particuology 2011年第5期9卷 517-521页

作者： Hsuan-ching lin Cherng-Yuh Su Zhong-Kun Yang chung-Kwei lin Keng-Liang Ou Institute of Atomic and Molecular Sciences Academia Sinica Taipei Taiwan China Institute of ManufacturingEngineering National Taipei University of Technology Taipei 106 Taiwan China Department of Materials Science and Engineering Feng-Chia University Taichung 407 Taiwan China Department of Oral Medicine Taipei Medical University Taipei 110 Taiwan China

Various tungsten oxide-based nanomaterials have been prepared by a modified plasma arc gas condensation technique without the use of catalysts or substrates. These products could be obtained by controlling the processing parameters during experiment. All the as-obtained samples were characterized by field emission gun scanning electron microscopy, high-resolution transmission electron microscopy, and X- ray diffraction techniques. The results revealed that as-prepared tungsten oxide nanomaterials （WO3, W190s5 and WsO14） with different phases and morphologies could be obtained by decreasing the oxygen content in the chamber. In addition, W18049 nanotubes and nanorod bundles were fabricated by con- trolling the Ar/O2 ratio under He plasma gas. W18Q9/TiO2 core-shell nanoparticles were also prepared by evaporating a dual target. The experimental results showed that the present technique is unique and feasible for the fabrication of nanomaterials for use in different applications.

关键词： Plasma arc gas condensation Titanium oxide Tungsten oxide Nanoparticle Nanorods

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Mainchain conformation ordering self-assembly tailored room temperature phosphorescence emission

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Science China Chemistry 2025年第1期68卷 329-336页

作者： Yuzhu Li Yumeng Gao Feng Tian Yu Wang Yuan Yao Shaoliang lin Xiang Ma Binbin Xu Shanghai Key Laboratory of Advanced Polymeric Materials Key Laboratory for Ultrafine Materials of Ministry of Education School of Materials Science and Engineering East China University of Science and Technology Shanghai Synchrotron Radiation Facility Shanghai Advanced Research Institute Chinese Academy of Sciences Key Laboratory for Advance Materials and Feringa Noble Prize Scientist Joint Research Centre Frontiers Science for Materiobiology and Dynamic Chemistry School of Chemistry and Molecular Engineering East China University of Science & Technology

Developing organic room-temperature phosphorescence （RTP） materials with a wide range of tunable-emission is significant in expanding the applications of RTP ***,we rationally designed amphiphilic alternating copolymers poly(1,2-bis（4-alkoxyphenyl）ethane-1,2-dione-alt-（ethylene glycol）x)(P（Bz-alt-EGx）) that combined the advantage of alternating benzil and EGxskeleton,and tunable mainchain *** a mainchain conformation ordering assembly （COA） process,P（Bz-alt-EGx） self-assembled into well-defined platelets,and such assemblies emitted blue RTP at ca.425 nm due to the ordered folded-chain conformation and confined *** contrast,traditional self-assembly （TA） of P（Bz-alt-EGx） obtained less ordered aggregates,such as asymmetric worms,vesicles,and rod-like *** resultant less ordered aggregates exhibited yellow-green RTP at ca.550 *** wide-tuning RTP emission in solution （between blue and yellow-green,over125 nm） is realized using the P（Bz-alt-EGx） alternating copolymers under the treatment of different self-assembly *** study uncovers a new strategy to tailor the RTP emission through different self-assembly pathways and holds great promise for the fabrication of advanced optical materials.

关键词： self-assembly conformation ordering alternating copolymer phosphorescence emission

Multi-model ensemble learning for battery state-of-health estimation:Recent advances and perspectives

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Journal of Energy Chemistry 2025年第1期100卷 739-759页

作者： Chuanping lin Jun Xu Delong Jiang Jiayang Hou Ying Liang Zhongyue Zou Xuesong Mei State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Shaanxi Key Laboratory of Intelligent Robots School of Mechanical Engineering Xi'an Jiaotong University Department of Electrical Engineering and Automation Luoyang Institute of Science and Technology School of Mechanical Engineering Hangzhou Dianzi University

The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ens

关键词： Contrastive Learning

A General Association Test for High-Dimensional Random Vectors

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Acta Mathematica Sinica,English Series 2025年

作者： Yongshuai Chen Peng lin Baoxue Zhang School of Statistics Capital University of Economics and Business

Testing the association of two high-dimensional random vectors is of fundamental importance in the statistical theory and applications. In this paper, we propose a new test statistic based on the Frobenius norm and subtracting bias technique, which is generally applicable to high-dimensional data without restricting the distributional assumptions. The limiting null distribution of the proposed test is shown to be a random variable combining a finite chi-squared-type mixture with a normal approximation. Our proposed test method can also be a normal approximation or a finite chi-squared-type mixtures under additional regularity conditions. To make the test statistic applicable, we introduce a wild bootstrap method and demonstrate its validity. The finite-sample performance of the proposed test via Monte Carlo simulations reveals that it performs better at controlling the empirical size than some existing tests, even when the normal approximation is invalid. Real data analysis is devoted to illustrating the proposed test.

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