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Wafer‑Scale Ag_(2)S‑Based Memristive Crossbar Arrays with Ultra‑Low Switching‑Energies Reaching Biological Synapses

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Nano-Micro Letters 2025年第3期17卷 328-339页

作者： Yuan Zhu Tomas Nyberg Leif Nyholm Daniel Primetzhofer Xun Shi Zhen Zhang Division of Solid‑State electronics Department of Electrical EngineeringUppsala University75121 UppsalaSweden department of Chemistry Uppsala UniversityUppsalaSweden department of Physics and Astronomy Uppsala UniversityUppsalaSweden State Key Laboratory of High Performance Ceramics and Superfine Microstructure Shanghai Institute of CeramicsChinese Academy of SciencesShanghai 200050People’s Republic of China

Memristive crossbar arrays(MCAs)offer parallel data storage and processing for energy-efficient neuromorphic ***,most wafer-scale MCAs that are compatible with complementary metal-oxide-semiconductor(CMOS)technology still suffer from substantially larger energy consumption than biological synapses,due to the slow kinetics of forming conductive paths inside the memristive *** we report wafer-scale Ag_(2)S-based MCAs realized using CMOS-compatible processes at temperatures below 160℃.Ag_(2)S electrolytes supply highly mobile Ag+ions,and provide the Ag/Ag_(2)S interface with low silver nucleation barrier to form silver filaments at low energy *** further enhancing Ag+migration in Ag_(2)S electrolytes via microstructure modulation,the integrated memristors exhibit a record low threshold of approximately−0.1 V,and demonstrate ultra-low switching-energies reaching femtojoule values as observed in biological *** low-temperature process also enables MCA integration on polyimide substrates for applications in flexible ***,the intrinsic nonidealities of the memristive units for deep learning can be compensated by employing an advanced training *** impressive accuracy of 92.6%in image recognition simulations is demonstrated with the MCAs after the *** demonstrated MCAs provide a promising device option for neuromorphic computing with ultra-high energy-efficiency.

关键词： Wafer-scale Ag_(2)S films Reactive sputter Silver nucleation Ag^(+)migration Energy-efficient neuromorphic computing

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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

Secure Channel Estimation Using Norm Estimation Model for 5G Next Generation Wireless Networks

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Computers, Materials & Continua 2025年第1期82卷 1151-1169页

作者： Khalil Ullah Song Jian Muhammad Naeem Ul Hassan Suliman Khan Mohammad Babar Arshad Ahmad Shafiq Ahmad Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650500China department of Computer Science Abbottabad University of Science and TechnologyHavelianAbbottabad22500Pakistan department of Computing and electronics Engineering Middle East CollegeMuscat124Oman department of CS&IT Pak-Austria Fachhochschule Institute of Applied Sciences and Technology MangHaripur22621Pakistan Industrial Engineering department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile *** networks are sufficiently scaled to interconnect billions of users and *** in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous *** continuously improves its network functionality to support these *** input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in *** article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial *** technique aims to create long-lasting and secure NextG networks using this extended *** viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this ***,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.

关键词： Next generation networks massive mimo communication network artificial intelligence 5G adversarial attacks channel estimation information security

Boosting aqueous nickel-zinc battery stability with bimetallic ion-integrated 1D metal-organic nanowires

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Science China Chemistry 2025年

作者： Yihao Chen Jin Liang Yichun Su Guoyin Zhu Hengyue Xu Hongye Ding Guangxun Zhang Dianheng Yu Zizhou Shen Yizhou Zhang Wei Huang Huan Pang School of Chemistry and Chemical Engineering Yangzhou University Key Laboratory of Flexible electronics (KLoFE) & Institute of Advanced Materials (IAM) School of Flexible Electronics (Future Technologies) Nanjing Tech University (NanjingTech) Institute of Advanced Materials and Flexible electronics (IAMFE) School of Chemistry and Materials Science Nanjing University of Information Science & Technology department of Chemistry Tsinghua University State Key Laboratory of Coordination Chemistry Nanjing University

Limited by low conductivity,designing cathode materials with excellent electron transfer efficiency for high-performance nickel-zinc batteries （NZBs） remains *** this study,a series of bimetallic metal-organic nanowires were fabricated by doping M ions in NiNTA,resulting in NiMNTA (M=Mg2+,Mn2+,Co2+,Zn2+,Ag+),and NixCo6-xNTA （x=1,2,3,4,5）.The proportions and types of metal ions can be modified without altering the initial coordination structure.X-ray absorption fine structure spectroscopy （XAFS） revealed that only M–O bonds,not metal bonds,were present in the *** performance of Ni2Co4NTA as the cathode for aqueous NZBs was significantly improved,achieving the maximum energy density of 279.17Wh kg-1with the high cycle stability （retention rate of 72.0%after 1,000 cycles）.The flexible Ni2Co4NTA//Zn@carbon cloth battery employing gel electrolyte also exhibits the excellent Coulombic efficiency of 96%after 350 *** approach shows considerable potential for designing one-dimensional materials with bimetallic modifications,providing new strategies for developing cathode materials for NZBs with high specific capacity and cycle stability.

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Data-Driven Healthcare:The Role of Computational Methods in Medical Innovation

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 1-48页

作者： Hariharasakthisudhan Ponnarengan Sivakumar Rajendran Vikas Khalkar Gunapriya Devarajan Logesh Kamaraj department of Mechanical Engineering Dr.Mahalingam College of Engineering and TechnologyPollachiCoimbatoreTamil Nadu642003India department of Mechanical Engineering JKKN College of Engineering and TechnologyKumarapalayamNamakkalTamil Nadu637209India department of Mechanical Engineering Gharda Institute of TechnologyLavelMaharashtra415708India department of Electrical and electronics Engineering Sri Eshwar College of EngineeringCoimbatoreTamilnadu641202India department of Mechanical Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai600062India

The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical *** review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health *** findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and *** synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment ***,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease *** review emphasizes the need for interdisciplinary collaboration to further advance this *** research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and *** fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.

关键词： Computational models biomedical engineering bioinformatics machine learning wearable technology

Impact of Pollutant Concentration and Particle Deposition on the Radiative Flow of Casson-Micropolar Fluid between Parallel Plates

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 665-690页

作者： Ghaliah Alhamzi Badr Saad T.Alkahtani Ravi Shanker Dubey Vinutha Kalleshachar Neelima Nizampatnam department of Mathematics and Statistics College of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11564Saudi Arabia department of Mathematics College of ScienceKing Saud UniversityRiyadh11989Saudi Arabia department of Mathematics Amity School of Applied SciencesAmity University RajasthanJaipur302002RajasthanIndia department of Studies in Mathematics Davangere UniversityDavangere577002India department of electronics and communication Engineering Amrita School of EngineeringAmrita Vishwa VidyapeethamBengaluru560035India

Assessing the behaviour and concentration of waste pollutants deposited between two parallel plates is essential for effective environmental *** the effectiveness of treatment methods in reducing pollution scales is made easier by analysing waste discharge *** waste discharge concentration analysis is useful for assessing how effectively wastewater treatment techniques reduce pollution *** study aims to explore the Casson micropolar fluid flow through two parallel plates with the influence of pollutant concentration and thermophoretic particle *** explore the mass and heat transport features,thermophoretic particle deposition and thermal radiation are *** governing equations are transformed into ordinary differential equations with the help of suitable similarity *** Runge-Kutta-Fehlberg’s fourthfifth order technique and shooting procedure are used to solve the reduced set of equations and boundary *** integration of a neural network model based on the Levenberg-Marquardt algorithm serves to improve the accuracy of predictions and optimize the analysis of *** outcomes are displayed to analyze the characteristics of the relevant dimensionless parameters in the current *** reveal that concentration upsurges as the micropolar parameter *** concentration reduces with an upsurge in the thermophoretic *** upsurge in the external pollutant source variation and the local pollutant external source parameters enhances mass *** surface drag force declines for improved values of porosity and micropolar parameters.

关键词： Micropolar fluid thermal radiation porous medium thermophoretic particle deposition waste discharge concentration

Nanoimprint lithography-assisted block copolymer self-assembly for hyperfine fabrication of magnetic patterns based on L10-FePt nanoparticles

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Science China Chemistry 2025年

作者： Jie Zhang Yi Chen Guijun Li Zelin Sun Zhengong Meng Wai-Yeung Wong department of Applied Biology and Chemical Technology and Research Institute for Smart Energy The Hong Kong Polytechnic University The Hong Kong Polytechnic University Shenzhen Research Institute Division of Integrative Systems and Design and Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology School of Flexible electronics (Future Technology) and Institute of Advanced Materials (IAM) Nanjing Tech University

L10-FePt-type bit-patterned media has provided a promising alternative for ultrahigh-density magnetic recording systems in the current digital era, but rapid fabrication of magnetic patterns with hyperfine bit islands is still challenging, especially with the target for miniaturization and scalable production simultaneously. Herein, Fe,Pt-containing block copolymers were utilized as single-source precursors for solution-processable patterning and subsequent generation of the demanding magnetic FePt dots by in situ pyrolysis. High-throughput nanoimprint lithography was initially employed to fabricate the predefined bit cells precisely,and then the intrinsic self-assembly of phase-separated block copolymers further drove the formation of accurate bit *** from the synergistic effect of top-down lithographic approach and bottom-up self-assembly, the customizable patterns could be achieved for large-scale mass production in targeted areas, but high-density isolated dots could also be accurately aligned along the patterned features after subsequent self-assembly. This reliable strategy would provide a good avenue to precisely construct ultrahigh-density magnetic data storage devices.

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A Rapid Adaptation Approach for Dynamic Air‑Writing Recognition Using Wearable Wristbands with Self‑Supervised Contrastive Learning

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Nano-Micro Letters 2025年第2期17卷 417-431页

作者： Yunjian Guo Kunpeng Li Wei Yue Nam‑Young Kim Yang Li Guozhen Shen Jong‑Chul Lee department of Electronic Convergence Engineering Kwangwoon UniversitySeoul 01897South Korea Radio Frequency Integrated Circuit(RFIC)Bio Centre Kwangwoon UniversitySeoul 01897South Korea department of Electronic Engineering Kwangwoon UniversitySeoul 01897South Korea School of Microelectronics Shandong UniversityJinan 250101People’s Republic of China State Key Laboratory of Integrated Chips and Systems Fudan UniversityShanghai 200433People’s Republic of China School of Integrated Circuits and electronics Beijing Institute of TechnologyBeijing 100081People’s Republic of China

Wearable wristband systems leverage deep learning to revolutionize hand gesture recognition in daily *** existing approaches that often focus on static gestures and require extensive labeled data,the proposed wearable wristband with selfsupervised contrastive learning excels at dynamic motion tracking and adapts rapidly across multiple *** features a four-channel sensing array composed of an ionic hydrogel with hierarchical microcone structures and ultrathin flexible electrodes,resulting in high-sensitivity capacitance *** wireless transmission from a Wi-Fi module,the proposed algorithm learns latent features from the unlabeled signals of random wrist ***,only few-shot labeled data are sufficient for fine-tuning the model,enabling rapid adaptation to various *** system achieves a high accuracy of 94.9%in different scenarios,including the prediction of eight-direction commands,and air-writing of all numbers and *** proposed method facilitates smooth transitions between multiple tasks without the need for modifying the structure or undergoing extensive task-specific *** utility has been further extended to enhance human–machine interaction over digital platforms,such as game controls,calculators,and three-language login systems,offering users a natural and intuitive way of communication.

关键词： Wearable wristband Self-supervised contrastive learning Dynamic gesture Air-writing Human-machine interaction

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Identification of earthquake induced structural damage based on synchroextracting transform

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Earthquake Engineering and Engineering Vibration 2024年第2期23卷 475-487页

作者： Roshan Kumar Gaurav Kumar Wei Zhao Arvind R Yadav Gang Yu Jayendra Kumar Evans Amponsah department of Electronic and Information Technology Miami College of Henan UniversityHenan 475004China Alliance University Alliance College of Engineering and DesignBanglore 562106India department of electronics and comm Parul UniversityVadodra 391760India School of Electrical Engineering University of JinanJinan 250022China department of electronics and comm NIT JamshedpurJamshedpur 831014India department of Civil engineering Kwame Nkrumah University of Science and TechnologyKumasi 10959Ghana

Several popular time-frequency techniques,including the Wigner-Ville distribution,smoothed pseudo-Wigner-Ville distribution,wavelet transform,synchrosqueezing transform,Hilbert-Huang transform,and Gabor-Wigner transform,are investigated to determine how well they can identify damage to *** this work,a synchroextracting transform(SET)based on the short-time Fourier transform is proposed for estimating post-earthquake structural *** performance of SET for artificially generated signals and actual earthquake signals is examined with existing *** other tested techniques,SET improves frequency resolution to a great extent by lowering the influence of smearing along the time-frequency ***,interpretation and readability with the proposed method are improved,and small changes in the time-varying frequency characteristics of the damaged buildings are easily detected through the SET method.

关键词： cross-term damage detection earthquake signal synchroextracting transform time-frequency

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