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Disordered hyperuniformity and thermal transport in monolayer amorphous carbon

Science China(Physics,Mechanics & Astronomy) 2025年第2期68卷 145-152页

作者： Nianjie Liang Yuxi Wang Bai Song department of Energy and Resources engineering Peking UniversityBeijing 100871China department of Advanced manufacturing and Robotics Peking UniversityBeijing 100871China

Disordered hyperuniformity(DHU)is a recently discovered novel state of amorphous systems characterized by strongly suppressed density fluctuations at large length scales as in crystalline materials,which offers great potential for achieving unusual mechanical,electronic,and photonic ***,despite the fundamental and technological importance of thermal transport in amorphous solids,the effect of DHU remains largely ***,we theoretically study thermal transport in a class of two-dimensional DHU materials—monolayer amorphous carbon(MAC).Beginning with a perfect graphene lattice,we continuously apply Stone-Wales transformations to generate a series of MAC models with varied degrees of disorder and defects,which are quantified through comprehensive structural analysis including the so-called hyperuniformity index(H),where a smaller H indicates a higher degree of ***,we conduct molecular dynamics simulations to obtain the thermal conductivity(κ).A significant correlation between the thermal transport behavior and degree of hyperuniformity is observed,with the room-temperatureκdecreasing from 26.3 to 5.3 W m^(-1)K^(-1)while H is tuned from 0.0004 to ***,two distinct transport regimes are identified,including a nearly-DHU regime at small H(<0.005)whereκdrops sharply and a non-DHU region at larger H whereκbecomes relatively ***-resolved analysis reveals longer lifetime and higher participation ratio for the heat carriers in nearly-DHU MAC,implying that the hidden long-range correlations could support extended modes that enhance *** work highlights the impact of DHU on the thermal properties of amorphous materials and represents a conceptual advancement that is worthy of future exploration.

关键词： disordered hyperuniformity thermal transport amorphous material two-dimensional monolayer amorphous carbon

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GPIO-Based Continuous Sliding Mode Control for Networked Control Systems Under Communication Delays With Experiments on Servo Motors

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 99-113页

作者： Kamal Rsetam Zhenwei Cao Zhihong Man Xian-Ming Zhang the School of Software and Electrical engineering Swinburne University of Technology the department of Automated manufacturing Al Khwarizmi College of Engineering University of Baghdad IEEE

To handle input and output time delays that commonly exist in many networked control systems(NCSs), a new robust continuous sliding mode control(CSMC) scheme is proposed for the output tracking in uncertain single input-single-output(SISO) networked control systems. This scheme consists of three consecutive steps. First, although the network-induced delay in those systems can be effectively handled by using Pade approximation(PA), the unmatched disturbance cames out as another difficulty in the control design. Second, to actively estimate this unmatched disturbance, a generalized proportional integral observer(GPIO) technique is utilized based on only one measured state. Third, by constructing a new sliding manifold with the aid of the estimated unmatched disturbance and states, a GPIO-based CSMC is synthesized, which is employed to cope with not only matched and unmatched disturbances, but also networkinduced delays. The stability of the entire closed-loop system under the proposed GPIO-based CSMC is detailedly *** promising tracking efficiency and feasibility of the proposed control methodology are verified through simulations and experiments on Quanser's servo module for motion control under various test conditions.

关键词： Continuous sliding mode control (CSMC) generalized proportional integral observer (GPIO) networked control systems (NCSs) pade approximation (PA) time-delay unsmatched disturbances

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Stress anisotropy regulated wrinkling pattern evolution on a core-shell soft cylinder

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Science China(Physics,Mechanics & Astronomy) 2025年第2期68卷 132-144页

作者： Yan Zhao Zhipan Jie Yilong Zhang Guo-Yang Li Yanping Cao Chao Jiang State Key Laboratory of Advanced Design and manufacturing for Vehicle Body College of Mechanical and Vehicle EngineeringHunan UniversityChangsha 410082China department of Mechanics and engineering Science College of EngineeringPeking UniversityBeijing 100871China Institute of Biomechanics and Medical engineering AMLDepartment of Engineering MechanicsTsinghua UniversityBeijing100084China

Diverse wrinkling patterns can occur on curved bilayer systems under differential growth or *** such systems,stress anisotropy is frequently encountered,and the coupling effect of curvature and stress anisotropy on the pattern evolution remains largely *** this study,we investigate the evolution of wrinkling patterns on a cylinder core-shell system with stress anisotropy leveraging both theoretical analysis and finite element *** buckling analysis has identified three distinct critical buckling modes regulated by the stress anisotropy,i.e.,axial sinusoidal mode,checkerboard mode,and circumferential sinusoidal *** finite element simulations,along with post-buckling analysis,reveal seven distinct evolutionary paths stemming from the three critical buckling *** present phase diagrams for both the critical buckling modes and their evolutionary paths,which are determined by dimensionless curvature and stress *** results not only expand the theoretical research on surface wrinkling of a core-shell soft cylinder but also introduce stress anisotropy as a significant parameter for regulating the wrinkling patterns and their evolutionary paths in curved bilayer *** revelation of a multitude of wrinkling patterns and their evolutionary pathways holds great potential for advancing applications that leverage tunable wrinkle surfaces.

关键词： wrinkling pattern evolutionary path stress anisotropy dimensionless curvature core-shell soft cylinder

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Physics-informed battery degradation prediction:Forecasting charging curves using one-cycle data

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Journal of Energy Chemistry 2025年第2期101卷 825-836页

作者： Aihua Tang Yuchen Xu Jinpeng Tian Xing Shu Quanqing Yu Key Laboratory of Advanced manufacturing Technology for Automobile Parts Ministry of Education Chongqing University of Technology department of Electrical and Electronic engineering and Research Centre for Grid Modernization The Hong Kong Polytechnic University School of Automotive engineering Harbin Institute of Technology

Accurately predicting battery degradation is crucial for battery system ***,due to the complexities of aging mechanisms and limitations of historical data,comprehensively indicating battery degradation solely through maximum capacity loss assessment is *** machine learning offers promising solutions,it often overlooks domain knowledge,resulting in reduced accu racy,increased computational burden and decreased ***,this study proposes a method to predict the voltage-capacity（V-Q） curve during battery degradation with limited historical *** process is achieved through two physically interpretable components:a lightweight interpretable physical model and a physics-informed neural *** components incorporate domain knowledge into machine learning to improve V-Q curve prediction performance and enhance *** validation was conducted on 52 batteries of different types under different testing *** proposed method can accurately predict future *** for hundreds of cycles using only one-present-cycle V-Q curve,with root mean square error and mean absolute error basically less than 0.035 Ah and R2basically less than 98.5%.This means that incremental capacity curves can be extracted from the predicted results for a more comprehensive and accurate battery degradation ***,the method can flexibly adjust prediction length and density to cater to the practical needs of long-cycle prediction and data *** study provides a viable method for rapid degradation prediction and is expected to be generalized to in-vehicle implementations.

关键词： Degradation prediction Lightweight interpretable physical model Lithium-ion battery Physics-informed neural network Voltage-capacity curve

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Ultrasonic vibration-assisted cutting of titanium alloys:A state-of-the-art review

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Chinese Journal of Aeronautics 2025年第1期38卷 3-42页

作者： Ahmar KHAN Xin WANG Biao ZHAO Wenfeng DING Muhammad JAMIL Aqib Mashood KHAN Syed Hammad ALI Sadam HUSSAIN Jiong ZHANG Raj DAS National Key Laboratory of Science and Technology on Helicopter Transmission Nanjing University of Aeronautics and AstronauticsNanjing 210016China department of Mechanical engineering College of EngineeringCity University of Hong KongHong Kong 999077China Centre for Additive manufacturing School of EngineeringAerospace Engineering and AviationRMIT UniversityVictoria 3083Australia

The remarkable ability of titanium alloys to preserve their superior physical and chemical characteristics when subjected to extreme conditions significantly enhances their importance in the aerospace,military,and medical ***,conventional machining of titanium alloys leads to elevated tool wear,development of surface defects,and reduced machining efficiency due to their low heat conductivity,and chemical *** issues can be somewhat counteracted by integrating ultrasonic vibration in the conventional machining of titanium alloys and also enhance *** review article offers a holistic evaluation of the influence of ultrasonic vibration-assisted milling and turning on cutting forces,temperature,tool wear,and surface integrity,encompassing surface morphology,surface roughness,surface residual stress,surface hardness,and surface tribological properties during titanium alloys ***,it investigates the sustainability aspect that has not been previously *** on the performance of ultrasonic-assisted cutting revealed several advantages,including decreased cutting forces and cutting temperature,improved tool life,and a better-machined surface during ***,the sustainability factor is improved due to minimized energy consumption and residual *** conclusion,the key challenges and future prospects in the ultrasonic-assisted cutting of titanium alloys are also *** review article provides beneficial knowledge for manufactur-ers and researchers regarding ultrasonic vibration-assisted cutting of titanium alloy and will play an important role in achieving sustainability in the industry.

关键词： Ultrasonic vibration-assisted cutting Titanium alloys Material removal mechanism Machinability Sustainability

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Recent developments in MQL machining of aeronautical materials:A comparative review

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Chinese Journal of Aeronautics 2025年第1期38卷 43-69页

作者： Syed Hammad ALI Yu YAO Bangfu WU Biao ZHAO Wenfeng DING Muhammad JAMIL Ahmar KHAN Asra BAIG Qi LIU Dongdong XU National Key Laboratory of Science and Technology on Helicopter Transmission Nanjing University of Aeronautics and AstronauticsNanjing 210016China department of Mechanical engineering NED University of Engineering and TechnologyKarachi 75270Pakistan Centre for Precision manufacturing University of StrathclydeGlasgow G11XQUK School of Mechanical engineering Tongji UniversityShanghai 200092China

Minimum quantity lubrication(MQL),as a new sustainable and eco-friendly alternative cooling/lubrication technology that addresses the limitations of dry and wet machining,utilizes a small amount of lubricant or coolant to reduce friction,tool wear,and heat during cutting *** technique has witnessed significant developments in recent years,such as combining MQL with other sustainable techniques to achieve optimum results,using biodegradable lubricants,and innovations in nozzle designs and delivery *** review presents an in-depth analysis of machining characteristics(e.g.,cutting forces,temperature,tool wear,chip morphology and surface integrity,etc.)and sustainability characteristics(e.g.,energy consumption,carbon emissions,processing time,machining cost,etc.)of conventional MQL and hybrid MQL techniques like cryogenic MQL,Ranque-Hilsch vortex tube MQL,nanofluids MQL,hybrid nanofluid MQL and ultrasonic vibration assisted MQL in machining of aeronautical ***,the latest research and developments are analyzed and summarized in the field of MQL,and provide a detailed comparison between each technique,considering advantages,challenges,and limitations in practical *** addition,this review serves as a valuable source for researchers and engineers to optimize machining processes while minimizing environmental impact and operational ***,the potential future aspects of MQL for research and industrial execution are discussed.

关键词： Aerospace materials Minimum Quantity Lubrication(MQL) Cryogenic Nanofluid Grinding Milling Sustainability

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Spherical Magnetic Fe-Alginate Microgels Fabricated by Droplet-Microfluidics Combining with an External Crosslinking Approach and the Study of Their pH Dependent Fe^(3+) Release Behaviors

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Chinese Journal of Polymer Science 2025年第2期43卷 289-302页

作者： Jie Chen Run-Yu Yu ai-Qi Wang Zhe-Yu Zhang Arezoo Ardekani Yuan-Du Hu department of Materials Science and engineering School of Physics Science and EngineeringBeijing Jiaotong UniversityBeijing100044China Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced manufacturing South China University of TechnologyGuangzhou510641China State Key Laboratory of Molecular engineering of Polymers Fudan UniversityShanghai200438China department of Mathematics School of Mechanical EngineeringPurdue University585 Purdue MallWest LafayetteIN47907-2088USA

Due to the rapid development and potential applications of iron(Ⅲ)-alginate(Fe-Alg)microgels in biomedical as well as environmental engineering,this study explores the preparation and characterization of spherical Fe-Alg microgels using droplet microfluidics combined with an external ionic crosslinking *** study focused on the role of Fe^(3+)and examined its effects on the physical/chemical properties of microgels under different ionic conditions and reduced or oxidized *** pH-dependent release behavior of Fe^(3+)from these microgels demonstrates their potential biomedical and environmental ***,the microgels can exhibit magnetism simply by utilizing in situ oxidation,which can be further used for targeted drug delivery and magnetic separation technologies.

关键词： Fe-alginate microgels Droplet microfluidics In situ oxidation Magnetism

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Recent advancements of nonlinear dynamics in mode coupled microresonators: a review

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Applied Mathematics and Mechanics(English Edition) 2025年第2期46卷 209-232页

作者： Xuefeng WANG Zhan SHI Qiqi YANG Yuzhi CHEN Xueyong WEI Ronghua HUAN department of engineering Mechanics MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University department of Mechanics Key Laboratory of Soft Machines and Smart Devices of Zhejiang Province Zhejiang University State Key Laboratory for manufacturing Systems engineering Xi'an Jiaotong University

Due to scale effects, micromechanical resonators offer an excellent platform for investigating the intrinsic mechanisms of nonlinear dynamical phenomena and their potential applications. This review focuses on mode-coupled micromechanical resonators,highlighting the latest advancements in four key areas: internal resonance, synchronization, frequency combs, and mode localization. The origin, development, and potential applications of each of these dynamic phenomena within mode-coupled micromechanical systems are investigated, with the goal of inspiring new ideas and directions for researchers in this field.

关键词： mode coupling micro-electro-mechanical system (MEMS) resonator nonlinear dynamics O32

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Combined anisotropic and cyclic constitutive model for laser powder bed fusion fabricated aluminum alloy

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Chinese Journal of Aeronautics 2025年第1期38卷 165-184页

作者： Fei-Fan LI Jihong ZHU Weihong ZHANG Shifeng WEN Jingwen SONG Jun MA Gang FANG State IJR Center of Aerospace Design and Additive manufacturing School of Mechanical EngineeringNorthwestern Polytechnical UniversityXi’an 710072China Research&Development Institute of Northwestern Polytechnical university in Shenzhen Shenzhen 518063China School of Materials Science and engineering Northwestern Polytechnical UniversityXi'an 710072China department of Mechanical and Industrial engineering Norwegian University of Science and TechnologyTrondheim 7491Norway State Key Laboratory of Tribology in Advanced Equipment Department of Mechanical EngineeringTsinghua UniversityBeijing 100084China

This study presents new methods to effectively model the anisotropic yielding and hardening behavior of laser powder bed fusion fabricated aluminum alloy under both monotonic and cyclic loading *** proposed model combines the yield surface-interpolation method to accurately describe the anisotropic hardening rates in various directions,with the Chaboche kinematic hardening rule to precisely reflect the cyclic *** numerical implementation of the combined anisotropic and cyclic constitutive model,a fully implicit stress integration algorithm based on return mapping method is ***,the multiple parameters associated with the model are categorized and identified in an uncoupled *** isotropic and cyclic hardening parameters are determined by an inverse method,and the stability of the optimization outcomes is validated by applying different starting points for the ***,the back-stress effect on the identification of anisotropic parameters associated with the stress invariant-based Hill48 yield function is considered for the first *** consideration leads to an improved prediction accuracy compared to the identification of anisotropic parameters without considering back-stress *** combined anisotropic and cyclic constitutive model,along with the calibrated parameters,are proven capable of accurately reproducing the intricate deformation behavior of laser powder bed fusion fabricated AlSi10Mg.

关键词： Constitutive models Anisotropy Kinematic hardening Laser powder bed fusion Aluminum alloys

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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 UniversityXi’an 710049ShaanxiChina Shaanxi Key Laboratory of Intelligent Robots School of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049ShaanxiChina department of Electrical engineering and Automation Luoyang Institute of Science and TechnologyLuoyang 471023HenanChina School of Mechanical engineering Hangzhou Dianzi UniversityHangzhou 310018ZhejiangChina

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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