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Dielectric-ion-conductive ZnNb2O6 layer enabling rapid desolvation and diffusion for dendrite-free Zn metal batteries

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Journal of Energy Chemistry 2025年第1期100卷 693-701页

作者： Haifeng Yang Jian Wang Panpan Zhang Xiaomin Cheng Qinghua Guan Jing Dong Bixian Chen Lujie Jia Jing Zhang Yongzheng Zhang Yunjian Liu Hongzhen Lin school of Materials science and engineering Jiangsu University i-Lab & CAS Key Laboratory of Nanophotonic Materials and Devices Suzhou Institute of Nano-Tech and Nano-Bionics Chinese Academy of Sciences Helmholtz Institute Ulm (HIU) Karlsruhe Institute of technology (KIT) school of Materials science and engineering Xi'an University of Technology State Key Laboratory of Chemical engineering East China University of Science and Technology

Rechargeable aqueous zinc-metal batteries （AZMBs） are promising candidates for large-scale energy storage systems due to their low cost and high ***,their performance and sustainability are significantly hindered by the sluggish desolvation kinetics at the electrode/electrolyte interface and the corresponding hydrogen evolution reaction where active water molecules tightly participate in the Zn（H2O）62+solvation ***,learnt from self-generated solid electrolyte interphase （SEI） in anodes,the dielectric but ion-conductive zinc niobate nanoparticles artificial layer is constructed on metallic Zn surface （ZNB@Zn）,acting as a rapid desolvation *** zincophilic and dielectric-conductive properties of ZNB layer accelerate interfacial desolvation/diffusion and suppress surface corrosion or dendrite formation,achieving uniform Zn plating/stripping behavior,as confirmed by electronic/optical microscopies and interface spectroscopical measurements together with theoretical ***,the as-prepared ZNB@Zn electrode exhibits excellent cycling stability of over 2000 h and robust reversibility （99.54%） even under high current density and depth of discharge ***,the assembled ZNB@Zn-based full cell displays high capacity-retention rate of 80.21%after 3000 cycles at 5 A g-1and outstanding rate performance up to 10 A *** large-areal pouch cell is stabilized for hundreds of cycles,highlighting the bright prospects of the dielectric but ion-conductive layer in further application of AZMBs.

关键词： Zn metal battery Dielectric artificial layer Rapid ion diffusion Zincophilic diffusion Active water inhibition

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Unraveling the significance of cobalt on transformation kinetics,crystallography and impact toughness in high-strength steels

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International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 380-390页

作者： Yishuang Yu Jingxiao Zhao Xuelin Wang Hui Guo Zhenjia Xie Chengjia Shang Collaborative Innovation Center of Steel technology University of Science and Technology BeijingBeijing 100083China school of Materials science and engineering Shanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory for Advanced Metals and Materials University of Science and Technology BeijingBeijing 100083China

This work reveals the significant effects of cobalt(Co)on the microstructure and impact toughness of as-quenched highstrength steels by experimental characterizations and thermo-kinetic *** results show that the Co-bearing steel exhibits finer blocks and a lower ductile-brittle transition temperature than the steel without ***,the Co-bearing steel reveals higher transformation rates at the intermediate stage with bainite volume fraction ranging from around 0.1 to *** improved impact toughness of the Co-bearing steel results from the higher dense block boundaries dominated by the V1/V2 variant ***,the addition of Co induces a larger transformation driving force and a lower bainite start temperature(BS),thereby contributing to the refinement of blocks and the increase of the V1/V2 variant *** findings would be instructive for the composition,microstructure design,and property optimization of high-strength steels.

关键词： high-strength steel cobalt transformation kinetics crystallography impact toughness

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Semantic Segmentation of Lumbar Vertebrae Using Meijering U-Net(MU-Net)on Spine Magnetic Resonance Images

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computer Modeling in engineering & sciences 2025年第1期142卷 733-757页

作者： Lakshmi S V V Shiloah Elizabeth Darmanayagam Sunil Retmin Raj Cyril Department of computer science and engineering College of Engineering GuindyAnna UniversityChennai600025India Department of Information technology Madras Institute of TechnologyAnna UniversityChrompetChennai600044India

Lower back pain is one of the most common medical problems in the world and it is experienced by a huge percentage of people *** to its ability to produce a detailed view of the soft tissues,including the spinal cord,nerves,intervertebral discs,and vertebrae,Magnetic Resonance Imaging is thought to be the most effective method for imaging the *** semantic segmentation of vertebrae plays a major role in the diagnostic process of lumbar *** is difficult to semantically partition the vertebrae in Magnetic Resonance Images from the surrounding variety of tissues,including muscles,ligaments,and intervertebral discs.U-Net is a powerful deep-learning architecture to handle the challenges of medical image analysis tasks and achieves high segmentation *** work proposes a modified U-Net architecture namely MU-Net,consisting of the Meijering convolutional layer that incorporates the Meijering filter to perform the semantic segmentation of lumbar vertebrae L1 to L5 and sacral vertebra ***-colour mask images were generated and used as ground truth for training the *** work has been carried out on 1312 images expanded from T1-weighted mid-sagittal MRI images of 515 patients in the Lumbar Spine MRI Dataset publicly available from Mendeley *** proposed MU-Net model for the semantic segmentation of the lumbar vertebrae gives better performance with 98.79%of pixel accuracy(PA),98.66%of dice similarity coefficient(DSC),97.36%of Jaccard coefficient,and 92.55%mean Intersection over Union(mean IoU)metrics using the mentioned dataset.

关键词： computer aided diagnosis(CAD) magnetic resonance imaging(MRI) semantic segmentation lumbar vertebrae deep learning U-Net model

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Regression analysis of squeezing-induced hybrid nanofluid flow in Darcy-Forchheimer porous medium

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Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 193-208页

作者： K.MUHAMMAD M.SARFRAZ Department of Humanities and sciences School of Electrical Engineering and Computer Science National University of Sciences and Technology Department of Mathematics Quaid-i-Azam University

This article presents a mathematical model addressing a scenario involving a hybrid nanofluid flow between two infinite parallel plates. One plate remains stationary, while the other moves downward at a squeezing velocity. The space between these plates contains a Darcy-Forchheimer porous medium. A mixture of water-based fluid with gold(Au) and silicon dioxide(Si O2) nanoparticles is formulated. In contrast to the conventional Fourier's heat flux equation, this study employs the Cattaneo-Christov heat flux equation. A uniform magnetic field is applied perpendicular to the flow direction, invoking magnetohydrodynamic(MHD) effects. Further, the model accounts for Joule heating, which is the heat generated when an electric current passes through the fluid. The problem is solved via NDSolve in MATHEMATICA. Numerical and statistical analyses are conducted to provide insights into the behavior of the nanomaterials between the parallel plates with respect to the flow, energy transport, and skin *** findings of this study have potential applications in enhancing cooling systems and optimizing thermal management strategies. It is observed that the squeezing motion generates additional pressure gradients within the fluid, which enhances the flow rate but reduces the frictional drag. Consequently, the fluid is pushed more vigorously between the plates, increasing the flow velocity. As the fluid experiences higher flow rates due to the increased squeezing effect, it spends less time in the region between the plates. The thermal relaxation, however, abruptly changes the temperature, leading to a decrease in the temperature fluctuations.

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Inspires effective alternatives to backpropagation:predictive coding helps understand and build learning

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Neural Regeneration Research 2025年第11期20卷 3215-3216页

作者： Zhenghua Xu Miao Yu Yuhang Song school of Health sciences and Biomedical engineering Hebei University of TechnologyTianjinChina Department of computer science University of OxfordOxfordUK

Artificial neural networks are capable of machine learning by simulating the hiera rchical structure of the human *** enable learning by brain and machine,it is essential to accurately identify and correct the prediction errors,referred to as credit assignment(Lillicrap et al.,2020).It is critical to develop artificial intelligence by understanding how the brain deals with credit assignment in neuroscience.

关键词： assignment learning enable

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Unlocking the stable interface in aqueous zinc-ion battery with multifunctional xylose-based electrolyte additives

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Journal of Energy Chemistry 2025年第1期100卷 770-778页

作者： Xiaoqin Li Jian Xiang Lu Qiu Xiaohan Chen Yinkun Zhao Yujue Wang Qu Yue Taotao Gao Wenlong Liu Dan Xiao Zhaoyu Jin Panpan Li Institute for Advanced Study Chengdu University school of Mechanical engineering Chengdu University College of Food and Biological engineering Chengdu University Institute of Fundamental and Frontier sciences University of Electronic Science and Technology of China College of Materials science and engineering Sichuan University

The growth of dendrites and the side reactions occurring at the Zn anode pose significant challenges to the commercialization of aqueous Zn-ion batteries（AZIBs）. These challenges arise from the inherent conflict between mass transfer and electrochemical kinetics. In this study, we propose the use of a multifunctional electrolyte additive based on the xylose（Xylo） molecule to address these issues by modulating the solvation structure and electrode/electrolyte interface, thereby stabilizing the Zn anode. The introduction of the additive alters the solvation structure, creating steric hindrance that impedes charge transfer and then reduces electrochemical kinetics. Furthermore, in-situ analyses demonstrate that the reconstructed electrode/electrolyte interface facilitates stable and rapid Zn2+ion migration and suppresses corrosion and hydrogen evolution reactions. As a result, symmetric cells incorporating the Xylo additive exhibit significantly enhanced reversibility during the Zn plating/stripping process, with an impressively long lifespan of up to 1986 h, compared to cells using pure ZnSO4electrolyte. When combined with a polyaniline cathode, the full cells demonstrate improved capacity and long-term cyclic stability. This work offers an effective direction for improving the stability of Zn anode via electrolyte design, as well as highperformance AZIBs.

关键词： Solvation

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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： Lithium-ion battery State-of-health estimation Data-driven Machine learning Ensemble learning Ensemble diversity

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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

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Zinc-based fiber-shaped rechargeable batteries:Insights into structures,electrodes,and electrolytes

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Nano Research 2025年第1期18卷 278-293页

作者： Xuan Zhang Hongcheng Zhang Mengxiang Chen Jingqi Lu Evgeny Zhuravlev Jing Jiang Pin Liu Shengyang Dong Du Yuan Guoyin Zhu Lianbo Ma Yizhou Zhang Institute of Advanced Materials and Flexible Electronics(IAMFE) School of Chemistry and Materials ScienceNanjing University of Information Science and TechnologyNanjing 210044China school of Materials science and engineering Anhui University of TechnologyMaanshan 243002China College of Materials science and engineering Changsha University of Science and TechnologyChangsha 410004China

The rapid evolution of flexible wearable electronics has spurred a growing demand for energy storage devices,characterized by low-cost manufacturing processes,high safety standards,exceptional electrochemical performance and robust mechanical *** novel flexible devices,fiber-shaped batteries(FSBs)have emerged as prominent solutions exceptionally suited to future applications,owing to their unique one-dimensional(1D)architecture,remarkable flexibility,potential for miniaturization,adaptability to deformation and compatibility with the conventional textile *** the forefront research on fiber-shaped batteries,zincbased FSBs(ZFSBs)have garnered significant attentions,featured by the promising electrochemical properties of metallic *** enthusiasm is driven by the impressive capacity of Zn(820 mAh·g^(-1))and its low redox potential(Zn/Zn^(2+):-0.76 V *** hydrogen electrode).This review aims to consolidate recent achievements in the structural design,fabrication processes and electrode materials of flexible ***,we highlight three representative structural configurations:parallel type,twisted type and coaxial *** also place special emphasis on electrode modifications and electrolyte ***,we delve into the promising development opportunities and anticipate future challenges associated with ZFSBs,emphasizing their potential roles in powering the next generation of wearable electronics.

关键词： zinc-based batteries fiber-shape parallel type twisted type coaxial type

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Cascade degradation and electrocatalytic upcycling of waste poly(ethylene terephthalate)to valued products

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Nano Research 2025年第1期18卷 76-93页

作者： Xin Li Zirui Jiang Zongkui Kou John Wang Shiyou Zheng school of Materials and Chemistry University of Shanghai for Science and TechnologyShanghai 200093China school of Materials science and engineering Wuhan University of TechnologyWuhan 430070China Department of Materials science and engineering National University of SingaporeSingapore 117574Singapore

The global annual production of poly(ethylene terephthalate)(PET)has reached 82 million tons,yet only a small fraction(less than 20%)is *** ultra-slow degradation rate of PET results in the accumulation of PET waste in the environment,causing serious plastic pollution and posing severe challenges to *** response,great efforts have been directed toward developing a cascade degradation and electrocatalytic upcycling strategy,which serves as a“waste-towealth”*** strategy involves electro-reforming PEThydrolyzed intermediates or using PET pyrolyzed products as electrocatalysts to generate high-value *** review provides an overview of the state-of-the-art strategies for the“degradation-electrocatalytic upcycling(De-eUp)”of PET ***,an introduction to the strategy is provided,categorizing it into two main frameworks:“pyrolysis-electrocatalytic upcycling”and“hydrolysis-electrocatalytic upcycling”.The section on“pyrolysis-electrocatalytic upcycling”delves into the degradation methods for designing derived carbon nanomaterials and their utilization as high-performance ***“hydrolysis-electrocatalytic upcycling”section discusses recent advancements in electro-reforming of PET hydrolyzed intermediates for the production of C_(1) and C_(2) *** review concludes by examining the challenges and future prospects in developing an efficient and economical PET upcycling *** is anticipated that this review will stimulate further progress in plastic waste valorization.

关键词： poly(ethylene terephthalate)waste electrocatalytic upcycling pyrolysis hydrolysis ethylene glycol oxidation reaction

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