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Interfacial Zn2+-solvation regulator towards reversible and stable Zn anode

Journal of Energy Chemistry 2025年第1期100卷 684-692页

作者： Miao Zhou Xiongbin Luo Hang Li Shan Guo Zhuang Tong Xiaotao Zhou Xu Li Zhaohui Hou Shuquan Liang Guozhao Fang college of Mechanical engineering Key Laboratory of Hunan Province for Advanced Carbon-based Functional Materials Hunan Institute of Science and Technology School of Materials Science and engineering Key Laboratory of Electronic Packaging and Advanced Functional Materials of Hunan Province Central South University college of Materials and Metallurgy Guizhou University National Energy Metal Resources and New Materials Key Laboratory Central South University

Aqueous zinc-ion batteries （AZIBs） are fundamentally challenged by the instability of the electrode/electrolyte interface,predominantly due to irreversible zinc （Zn） deposition and hydrogen ***,the intricate mechanisms behind the electrochemical discrepancies induced by interfacial Zn2+-solvation and deposition behavior demand comprehensive *** molecules endowed with special functional groups （such as hydroxyl,carboxyl,etc.） have the potential to significantly optimize the solvation structure of Zn2+and regulate the interfacial electric double layer （EDL）.By increasing nucleation overpotential and decreasing interfacial free energy,these functional groups facilitate a lower critical nucleation radius,thereby forming an asymptotic nucleation model to promote uniform Zn ***,this study presents a pioneering approach by introducing trace amounts of n-butanol as solvation regulators to engineer the homogenized Zn （H-Zn） anode with a uniform and dense *** interfacial reaction and structure evolution are explored by in/ex-situ experimental techniques,indicating that the H-Zn anode exhibits dendrite-free growth,no by-products,and weak hydrogen evolution,in sharp contrast to the bare ***,the H-Zn anode achieves a remarkable Zn utilization rate of approximately 20% and simultaneously sustains a prolonged cycle life exceeding 500 ***,the H-Zn//NH4V4O10（NVO） full battery showcases exceptional cycle stability,retaining 95.04%capacity retention after 400 cycles at a large current density of 5 A *** study enlightens solvation-regulated additives to develop Zn anode with superior utilization efficiency and extended operational lifespan.

关键词： Solvation

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Dynamic Regulation of Hydrogen Bonding Networks and Solvation Structures for Synergistic Solar‑Thermal Desalination of Seawater and Catalytic Degradation of Organic Pollutants

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Nano-Micro Letters 2025年第2期17卷 548-565页

作者： Ming‑Yuan Yu Jing Wu Guang Yin Fan‑Zhen Jiao Zhong‑Zhen Yu Jin Qu Beijing Key Laboratory of Advanced Functional Polymer Composites Beijing University of Chemical TechnologyBeijing 100029People’s Republic of China State Key Laboratory of Organic‑Inorganic Composites College of Materials Science and EngineeringBeijing University of Chemical TechnologyBeijing 100029People’s Republic of China

Although solar steam generation strategy is efficient in desalinating seawater,it is still challenging to achieve continuous solar-thermal desalination of seawater and catalytic degradation of organic ***,dynamic regulations of hydrogen bonding networks and solvation structures are realized by designing an asymmetric bilayer membrane consisting of a bacterial cellulose/carbon nanotube/Co_(2)(OH)_(2)CO_(3)nanorod top layer and a bacterial cellulose/Co_(2)(OH)_(2)CO_(3)nanorod(BCH)bottom ***,the hydrogen bonding networks inside the membrane can be tuned by the rich surface–OH groups of the bacterial cellulose and Co_(2)(OH)_(2)CO_(3)as well as the ions and radicals in situ generated during the catalysis ***,both SO_(4)^(2−)and HSO_(5)−can regulate the solvation structure of Na^(+)and be adsorbed more preferentially on the evaporation surface than Cl^(−),thus hindering the de-solvation of the solvated Na^(+)and subsequent nucleation/growth of ***,the heat generated by the solar-thermal energy conversion can accelerate the reaction kinetics and enhance the catalytic degradation *** work provides a flow-bed water purification system with an asymmetric solar-thermal and catalytic membrane for synergistic solar thermal desalination of seawater/brine and catalytic degradation of organic pollutants.

关键词： Solar steam generation Seawater desalination Catalytic degradation Bacterial cellulose Cobalt hydroxycarbonate nanorods

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High-precision tip positioning composite feedforward control of linear colocated motion systems with Bi-Loop iterative feedforward tuning

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Science China Technological Sciences 2025年

作者： Junyu HU Yourui TAO Shanhu LI Xu HAN college of Mechanical and Vehicle engineering Hunan University State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology

To enhance the tip positioning accuracy and robustness against disturbances of linear colocated motion systems, a novel composite feedforward (COMFF) control with Bi-Loop iterative feedforward tuning (IFFT) is proposed. The tip positioning error consists of the coupled tip residual vibration and linear motor tracking error. Given the influence of nonlinear friction and load flexibility, the topology of COMFF is designed as decoupled structures so that COMFF can suppress the tip residual vibration and compensate for the linear motor tracking error compatibly. Furthermore, Bi-Loop IFFT is built to improve the robustness of COMFF in high-precision motor tracking performance. In the state space of the linear motor tracking error based on the projection theorem, two loops are performed in parallel along the iteration direction. One is the P-type iteration loop that drives linear motor tracking errors to converge to the zero state. The other is the observation loop constructed by the recursive least square with forgetting factors to accelerate the P-type iteration loop. Driven by the P-type iteration loop with the aid of the observation loop, the proposed COMFF is integrated with fast convergence and high robustness when confronted with model disturbances. The effectiveness of the proposed COMFF combined with Bi-Loop IFFT is validated by experiments.

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Gradient‑Layered MXene/Hollow Lignin Nanospheres Architecture Design for Flexible and Stretchable Supercapacitors

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Nano-Micro Letters 2025年第2期17卷 447-462页

作者： Haonan Zhang Cheng Hao Tongtong Fu Dian Yu Jane Howe Kaiwen Chen Ning Yan Hao Ren Huamin Zhai Jiangsu Provincial Key Lab of Sustainable Pulp and Paper technology and Biomass Materials NanJing Forestry UniversityNanjing 210037People’s Republic of China Department of Chemical engineering and Applied Chemistry University of Toronto200 College StreetTorontoON M5S 3E5Canada Department of Materials Science and engineering University of Toronto184 College StreetTorontoON M5S 3E4Canada college of Materials Science and engineering Nanjing Forestry UniversityNanjing 210037People’s Republic of China

With the rapid development of flexible wearable electronics,the demand for stretchable energy storage devices has *** this work,a novel gradient-layered architecture was design based on single-pore hollow lignin nanospheres(HLNPs)-intercalated two-dimensional transition metal carbide(Ti_(3)C_(2)T_(x) MXene)for fabricating highly stretchable and durable *** depositing and inserting HLNPs in the MXene layers with a bottom-up decreasing gradient,a multilayered porous MXene structure with smooth ion channels was constructed by reducing the overstacking of MXene ***,the micro-chamber architecture of thin-walled lignin nanospheres effectively extended the contact area between lignin and MXene to improve ion and electron accessibility,thus better utilizing the pseudocapacitive property of *** these strategies effectively enhanced the capacitive performance of the *** addition,HLNPs,which acted as a protective phase for MXene layer,enhanced mechanical properties of the wrinkled stretchable electrodes by releasing stress through slip and deformation during the stretch-release cycling and greatly improved the structural integrity and capacitive stability of the *** electrodes and symmetric flexible all-solid-state supercapacitors capable of enduring 600%uniaxial tensile strain were developed with high specific capacitances of 1273 mF cm^(−2)(241 F g^(−1))and 514 mF cm^(−2)(95 F g^(−1)),***,their capacitances were well preserved after 1000 times of 600%stretch-release *** study showcased new possibilities of incorporating biobased lignin nanospheres in energy storage devices to fabricate stretchable devices leveraging synergies among various two-dimensional nanomaterials.

关键词： Hollow lignin nanospheres MXene Gradient-layered architecture Wrinkled electrodes Stretchable supercapacitors

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A general stabilizing strategy based on vitamin C for n-type organic semiconductors

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Science China Materials 2025年第01期 303-304页

作者： Hui Huang college of Materials Science and Opto-Electronic technology Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences

Organic semiconductors (OSCs), as an emerging next-generation semiconductor material, hold promising prospects in fields such as flexible displays, electronic skins, smart healthcare,and the Internet of Things, due to their excellent flexibility,solution processability, and tunable band structures [1,2]. These molecules are often classified into n-type and p-type, depending on whether the prevalent charge carriers are electrons or holes[3].

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High‑Entropy Electrode Materials:Synthesis,Properties and Outlook

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Nano-Micro Letters 2025年第1期17卷 472-506页

作者： Dongxiao Li Chang Liu Shusheng Tao Jieming Cai Biao Zhong Jie Li Wentao Deng Hongshuai Hou Guoqiang Zou Xiaobo Ji college of Chemistry and Chemical engineering Central South UniversityChangsha 410083People’s Republic of China School of Chemistry and Chemical engineering Hunan Institute of EngineeringXiangtan 411104People’s Republic of China

High-entropy materials represent a new category of high-performance materials,first proposed in 2004 and extensively investigated by researchers over the past two *** definition of high-entropy materials has continuously *** the last ten years,the discovery of an increasing number of high-entropy materials has led to significant advancements in their utilization in energy storage,electrocatalysis,and related domains,accompanied by a rise in techniques for fabricating high-entropy electrode ***,the research emphasis has shifted from solely improving the performance of high-entropy materials toward exploring their reaction mechanisms and adopting cleaner preparation ***,the current definition of high-entropy materials remains relatively vague,and the preparation method of high-entropy materials is based on the preparation method of single metal/low-or medium-entropy *** should be noted that not all methods applicable to single metal/low-or medium-entropy materials can be directly applied to high-entropy *** this review,the definition and development of high-entropy materials are briefly ***,the classification of high-entropy electrode materials is presented,followed by a discussion of their applications in energy storage and catalysis from the perspective of synthesis ***,an evaluation of the advantages and disadvantages of various synthesis methods in the production process of different high-entropy materials is provided,along with a proposal for potential future development directions for high-entropy materials.

关键词： High-entropy Energy storage Electrode materials

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Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

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Computer Modeling in engineering & Sciences 2025年第1期142卷 155-183页

作者： Suganya Athisayamani A.Robert Singh Gyanendra Prasad Joshi Woong Cho School of Computing Sastra Deemed to be UniversityThanjavur613401India Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203India Department of AI and Software engineering Kangwon National UniversitySamcheok25913Republic of Korea Department of Electronics Information and Communication EngineeringKangwon National UniversitySamcheok25913Republic of Korea

In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological *** is particularly effective for detecting soft tissue ***,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of *** address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI *** manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning *** are three stages for learning;in the first stage,the whole dataset is used to learn the *** the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented *** method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical engineering of Southern Medical University(SMU-dataset),and The National Institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for *** hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning ***-dataset registers maximum classification *** evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

关键词： MRI tumors classification AlexNet50 transfer learning hyperparameter tuning optimizer

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Multi boron-doping effects in hard carbon toward enhanced sodium ion storage

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Journal of Energy Chemistry 2025年第1期100卷 730-738页

作者： Peng Zheng Wang Zhou Ying Mo Biao Zheng Miaomiao Han Qin Zhong Wenwen Yang Peng Gao Lezhi Yang Jilei Liu college of Materials Science and engineering Hunan Joint International Laboratory of Advanced Materials and Technology for Clean Energy Hunan Province Key Laboratory for Advanced Carbon Materials and Applied Technology Hunan University Greater Bay Area Institute for Innovation Hunan University Changsha Research Institute of Mining & Metallurgy Co. LTD.

Hard carbon （HC） has been considered as promising anode material for sodium-ion batteries （SIBs）.The optimization of hard carbon’s microstructure and solid electrolyte interface （SEI） property are demonstrated effective in enhancing the Na+storage capability,however,a one-step regulation strategy to achieve simultaneous multi-scale structures optimization is highly ***,we have systematically investigated the effects of boron doping on hard carbon’s microstructure and interface chemistry.A variety of structure characterizations show that appropriate amount of boron doping can increase the size of closed pores via rearrangement of carbon layers with improved graphitization degree,which provides more Na+storage ***-situ Fourier transform infrared spectroscopy/electrochemical impedance spectroscopy （FTIR/EIS） and X-ray photoelectron spectroscopy （XPS） analysis demonstrate the presence of more BC3and less B–C–O structures that result in enhanced ion diffusion kinetics and the formation of inorganic rich and robust SEI,which leads to facilitated charge transfer and excellent rate *** a result,the hard carbon anode with optimized boron doping content exhibits enhanced rate and cycling *** general,this work unravels the critical role of boron doping in optimizing the pore structure,interface chemistry and diffusion kinetics of hard carbon,which enables rational design of sodium-ion battery anode with enhanced Na+storage performance.

关键词： X ray photoelectron spectroscopy

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Steel surface defect detection based on lightweight YOLOv7

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Optoelectronics Letters 2025年

作者： Shi Tao Wu Rongxin Zhu Wenxu Ma Qingliang School of Electrical engineering and Automation， Tianjin University of technology North China University of Science and technology， college of Electrical engineering Guangzhou Institute of measurement and Testing technology

Aiming at the problems of low detection efficiency and difficult positioning of traditional steel surface defect detection methods， a lightweight steel surface defect detection model based on YOLOv7 is proposed. First， a CSS Block module is proposed， which uses more lightweight operations to obtain redundant information in the feature map， reduces the amount of computation， and effectively improves the detection speed. Secondly， the improved SPPCSPC structure is adopted to ensure that the model can also pay attention to the defect location information while predicting the defect category information， obtain richer defect features. In addition， the convolution operation in the original model is simplified， which significantly reduces the size of the model and helps to improve the detection speed. Finally， using EIOU Loss to focus on high-quality Anchors， speed up convergence and improve positioning accuracy. Experiments were carried out on the NEU-DET steel surface defect dataset. Compared with the original YOLOv7 model， the number of parameters of this model was reduced by 40%， the FPS reached 112， and the average accuracy reached 79.1%.， the detection accuracy and speed have been improved， which can meet the needs of steel surface defect detection.

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Hybrid Deep Learning Approach for Automating App Review Classification:Advancing Usability Metrics Classification with an Aspect-Based Sentiment Analysis Framework

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Computers, Materials & Continua 2025年第1期82卷 949-976页

作者： Nahed Alsaleh Reem Alnanih Nahed Alowidi Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science College of Computer Science and EngineeringUniversity of HailHail81451Saudi Arabia

App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their *** the analysis of these reviews is vital for efficient review *** traditional machine learning(ML)models rely on basic word-based feature extraction,deep learning(DL)methods,enhanced with advanced word embeddings,have shown superior *** research introduces a novel aspectbased sentiment analysis(ABSA)framework to classify app reviews based on key non-functional requirements,focusing on usability factors:effectiveness,efficiency,and *** propose a hybrid DL model,combining BERT(Bidirectional Encoder Representations from Transformers)with BiLSTM(Bidirectional Long Short-Term Memory)and CNN(Convolutional Neural Networks)layers,to enhance classification *** analysis against state-of-the-art models demonstrates that our BERT-BiLSTM-CNN model achieves exceptional performance,with precision,recall,F1-score,and accuracy of 96%,87%,91%,and 94%,*** contributions of this work include a refined ABSA-based relabeling framework,the development of a highperformance classifier,and the comprehensive relabeling of the Instagram App Reviews *** advancements provide valuable insights for software developers to enhance usability and drive user-centric application development.

关键词： Requirements engineering(RE) app review analysis usabilitymetrics hybrid deep learning BERT-BiLSTM-CNN

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