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

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

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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

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Merging bound states in the continuum in an open acoustic resonator

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 124-131页

作者： Lujun Huang Bin Jia Artem S.Pilipchuk Sibo Huang Chen Shen Almas F.Sadreev Yong Li Andrey E.Miroshnichenko School of Physics and Electronic Sciences East China Normal University institute of Acoustics Tongji University L.V.Kirensky institute of Physics department of mechanical engineering Rowan University School of engineering and Technology University of New South Wales at Canberra

Bound states in the continuum （BICs） are perfectly localized resonances despite embedding in the continuum ***,an isolated BIC is very sensitive to the structure ***,we report merging acoustic BICs in a single open resonator,robust against the structure *** find that both symmetry-protected BIC and Friedrich-Wintgen BIC are sustained in a single coupled waveguide-resonator *** varying the height and length of the resonator,these two BICs move toward each other and merge into a single one at a critical *** to an individual BIC,the merged BIC is robust against fabrication error because its Q-factor is proportional to ΔL-4,whereΔL embodies the structure *** essence of this extraordinary phenomenon is perfectly explained by the two-and three-level approximations of the effective nonHermitian ***,we present direct experimental demonstrations of the moving and merging of BICs in a coupled 3D waveguide-resonator,which are evidenced by the vanishing of the linewidth of Fano resonance in the transmission *** results may find exciting applications in designing high-quality acoustic sources,sensors and filters.

关键词： acoustic resonances bound state in the continuum high-Q resonances

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Market Drivers in India’s Smart Grid:Responsibilities and Roles of Stakeholders

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Energy engineering 2025年第1期122卷 101-128页

作者： Abhay Sanatan Satapathy Suresh Kumar Sahoo Asit Mohanty Yasser Fouad Manzoore ElahiMohammad Soudagar Erdem Cuce Faculty of Management Studies Sri Sri UniversityCuttack754006India institute of Power engineering National Energy UniversityJalan Ikram-UnitenKajangSelangor43000Malaysia Centre of Research Impact and Outcome Chitkara UniversityRajpura140417PunjabIndia department of Applied mechanical engineering College of Applied EngineeringMuzahimiyah BranchKing Saud UniversityRiyadh11421Saudi Arabia College of engineering Lishui UniversityLishui323000China department of mechanical engineering Graphic Era(Deemed to be University)Dehradun248002UttarakhandIndia department of mechanical engineering Faculty of EngineeringUniversity of MalayaKuala Lumpur50603Malaysia department of mechanical engineering Faculty of Engineering and ArchitectureRecep Tayyip Erdogan UniversityZihni Derin CampusRize53100Turkey Center for Research Impact&Outcome Chitkara UniversityRajpura140401PunjabIndia University Centre for Research and Development Chandigarh UniversityMohali140413PunjabIndia

The emergence of smart grids in India is propelled by an intricate interaction of market dynamics,regulatory structures,and stakeholder *** study analyzes the primary factors that are driving the widespread use of smart grid technologies and outlines the specific roles and obligations of different stakeholders,such as government entities,utility companies,technology suppliers,and *** activities and regulations are crucial in facilitating the implementation of smart grid technology by offering financial incentives,regulatory assistance,and strategic *** firms have the responsibility of implementing and integrating smart grid infrastructure,with an emphasis on improving the dependability of the grid,minimizing losses in transmission and distribution,and integrating renewable energy *** companies offer the essential hardware and software solutions,which stimulate creativity and enhance *** actively engage in the energy ecosystem by participating in demand response,implementing energy saving measures,and adopting distributed energy resources like solar panels and electric *** study examines the difficulties and possibilities in India’s smart grid industry,highlighting the importance of cooperation among stakeholders to build a strong,effective,and environmentally friendly energy future.

关键词： Smart grid stakeholders smart grid technology market drivers

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Nano-Enhanced Dairy Scum Biodiesel Blends:Unleashing the Power of Aluminium Oxide for Sustainable and Efficient Engine Performance

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Journal of Thermal Science 2025年第1期 283-302页

作者： Veeranna MODI Prasad B.RAMPURE Sunil Kumar SHETTY Madeva NAGARAL Channa Keshava NAIK N Johar MGM Muhammad Irsyad ABDULLAH Abdullah I.AL-MANSOUR Shamshad ALAM KLE College of engineering and Technology ChikodiVisvesvaraya Technological University Nitte (Deemed to be University) NMAM Institute of Technology (NMAMIT)Department of Mechanical Engineering Aircraft Research and Design Centre HAL department of mechanical engineering BGS College of Engineering and TechnologyBengaluruAffiliated to Visvesvaraya Technological University Management and Science University department of Civil engineering College of EngineeringKing Saud University

This study investigates the effect of aluminium oxide nanoparticlesaddition to biodiesel blends made from dairy milk scum on performance and combustion characteristics of the diesel *** dispersion of Al2O3nanoparticles in B20 blends at different concentrations was done with the help of *** number of blends were prepared for the *** Machine learning algorithms(Random Forest（RF）and CatBoost) was used for the *** results show that in comparison to biodiesel blends without nanoparticles,the kinematic viscosity and density is higher for fuel blends with *** these Fuel blends have higher calorific *** blends exhibited reduced Brake Specific Fuel Consumption（BSFC） of2.85% than the blends without nano particles(Dairy Scum Methyl Ester Biodiesel 20%+Neat Diesel 80%（in volume）,DSMEB20),57.14% less CO,40.8% less hydrocarbon,and increased NOxemissions compared to conventional diesel,contributing to the development of environmentally friendly and renewable biofuel blends with *** B20NP30 is the optimal blend for performance and emission *** study concludes with findings on enhanced Brake Thermal Efficiency（BTE） of 26.29% in 3×10-5（in volume） Al2O3nanoparticle-blended DSME B20 and other DSME B20 fuel blends,emphasizing the importance of optimal nanoparticle *** correlation matrix shows how engine load,efficiency measures（BTE,BSFC）,and emissions（CO,CO2,NOx,Smoke） are connected in complex *** results help us understand the complicated dynamics of engine performance and emission characteristics ***'s diagram for BTE and BSFC shows that CatBoost-based BTE models perform superior to RF-based models during the training as well as testing *** results were obtained for CO and CO2emission results.

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Tuning the interfacial reaction environment via pH-dependent and induced ions to understand C–N bonds coupling performance in NO3- integrated CO2 reduction to carbon and nitrogen compounds over dual Cu-based N-doped carbon catalyst

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Journal of Energy Chemistry 2025年第1期100卷 273-285页

作者： Tianhang Zhou Chen Shen Zhenghao Wu Xingying Lan Yi Xiao College of Carbon Neutrality Future Technology State Key Laboratory of Heavy Oil Processing China University of Petroleum (Beijing) institute of Materials Science TU Darmstadt department of Chemistry Xi'an Jiaotong-Liverpool University department of mechanical and Mechatronics engineering and Waterloo Institute of Nanotechnology University of Waterloo Waterloo

Dual atomic catalysts （DAC）,particularly copper （Cu2）-based nitrogen （N） doped graphene,show great potential to effectively convert CO2and nitrate （NO3-） into important industrial chemicals such as ethylene,glycol,acetamide,and urea through an efficient catalytical process that involves C–C and C–N ***,the origin of the coupling activity remained unclear,which substantially hinders the rational design of Cu-based catalysts for the N-integrated CO2reduction reaction （CO2RR）.To address this challenge,this work performed advanced density functional theory calculations incorporating explicit solvation based on a Cu2-based N-doped carbon (Cu2N6C10) catalyst for *** calculations are aimed to gain insight into the reaction mechanisms for the synthesis of ethylene,acetamide,and urea via coupling in the interfacial reaction *** to the sluggishness of CO2,the formation of a solvation electric layer by anions （F-,Cl-,Br-,and I-） and cations (Na+,Mg2+,K+,and Ca2+) leads to electron transfer towards the Cu *** process significantly accelerates the reduction of *** results reveal that*CO intermediates play a pivotal role in N-integrated ***,the Cu2-based N-doped carbon catalyst examined in this study has demonstrated the most potential for C–N coupling to *** findings reveal that through the process of a condensation reaction between*CO and NH2OH for urea synthesis,*NO3-is reduced to*NH3,and*CO2to*CCO at dual Cu atom *** dual-site reduction facilitates the synthesis of acetamide through a nucleophilic reaction between NH3and the ketene ***,we found that the I-and Mg2+ions,influenced by pH,were highly effective for acetamide and ammonia synthesis,except when F-and Ca2+were ***,the mechanisms of C–N bond formation were investigated via ab-initio molecular dynamics simulations,and we found that adjusting the micro-environment can change the dominant side reaction,shift

关键词： Condensation reactions

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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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Catalyst–Support Interaction in Polyaniline‑Supported Ni_(3)Fe Oxide to Boost Oxygen Evolution Activities for Rechargeable Zn‑Air Batteries

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Nano-Micro Letters 2025年第1期17卷 176-190页

作者： Xiaohong Zou Qian Lu Mingcong Tang Jie Wu Kouer Zhang Wenzhi Li Yunxia Hu Xiaomin Xu Xiao Zhang Zongping Shao Liang An department of mechanical engineering The Hong Kong Polytechnic UniversityHung HomKowloonHong Kong SARPeople’s Republic of China Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environmental Science and TechnologyNanjing University of Information Science and TechnologyNanjing 210044People’s Republic of China department of Chemistry The Chinese University of Hong KongMa Lin BuildingShatinHong Kong SAR 999077People’s Republic of China WA School of Mines:Minerals Energy and Chemical Engineering(WASM‑MECE)Curtin UniversityPerthWA 6102Australia Research institute for Advanced Manufacturing The Hong Kong Polytechnic UniversityHung HomKowloonHong Kong SARPeople’s Republic of China Research institute for Smart Energy The Hong Kong Polytechnic UniversityHung HomKowloonHong Kong SARPeople’s Republic of China

Catalyst–support interaction plays a crucial role in improving the catalytic activity of oxygen evolution reaction(OER).Here we modulate the catalyst–support interaction in polyaniline-supported Ni_(3)Fe oxide(Ni_(3)Fe oxide/PANI)with a robust hetero-interface,which significantly improves oxygen evolution activities with an overpotential of 270 mV at 10 mA cm^(-2)and specific activity of 2.08 mA cm_(ECSA)^(-2)at overpotential of 300 mV,3.84-fold that of Ni_(3)Fe *** is revealed that the catalyst–support interaction between Ni_(3)Fe oxide and PANI support enhances the Ni–O covalency via the interfacial Ni–N bond,thus promoting the charge and mass transfer on Ni_(3)Fe *** the excellent activity and stability,rechargeable Zn-air batteries with optimum Ni_(3)Fe oxide/PANI are assembled,delivering a low charge voltage of 1.95 V to cycle for 400 h at 10 mA cm^(-2).The regulation of the effect of catalyst–support interaction on catalytic activity provides new possibilities for the future design of highly efficient OER catalysts.

关键词： Catalyst-support interaction Supported catalysts Heterointerface Oxygen evolution reaction Zn-air batteries

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Targets capture by distributed active swarms via bio-inspired reinforcement learning

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 210-221页

作者： Kun Xu Yue Li Jun Sun Shuyuan Du Xinpeng Di Yuguang Yang Bo Li institute of Biomechanics and Medical engineering Applied Mechanics Laboratory Department of Engineering MechanicsTsinghua University institute of Nuclear and New Energy Technology Tsinghua University Shanghai Aerospace Control Technology institute Shanghai Key Laboratory of Aerospace Intelligent Control Technology College of Automation engineering Nanjing University of Aeronautics and Astronautics

Natural swarms arranged from cells to herds are usually decentralized but display intriguing collective intelligence in coordinating individuals across large scales to efficiently achieve their common goals. Learning from nature may provide new strategies for controlling collective dynamics of synthetic swarms to accomplish specific functions. Here, we present a bioinspired computational framework that steers distributed active swarms to collectively capture and merge targets via reinforcement learning. We exploit collective milling structures of natural herds to cage the targets, and adopt a switching control policy inspired by sperms' chiral dynamics to optimize the trajectories of individuals, through which the active swarms can selforganize to enclose single or multiple distant targets in a dynamical, adaptive and scalable manner. There exists a critical swarm size, beyond which the excessive competition between agents would generate large mechanical forces, leading to capture instability but enabling the transition from short-distance to long-distance merging capture of multiple targets. This work provides physical insights into distributed active swarms and could offer a multilevel, decentralized strategy toward controlling swarm robotics in wide applications such as bio-medical devices, machine immunity, and target clearance.

关键词： swarm intelligence robotics multi-tasks artificial intelligence bionics

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Modeling tactile perceived intensity for vibration from a coin eccentric rotating mass motor

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Science China Technological Sciences 2025年

作者： Yun FANG Jingchen HUANG Yujun WU Jiaqi DONG Weichao GUO Xinjun SHENG State Key Laboratory of mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Meta Robotics institute Shanghai Jiao Tong University

Establishing the relationship between vibrotactile parameters and perceived intensity（PI） is of great significance in the regulation of desired sensations, which contribute to haptic interfaces in practical applications. Coin eccentric rotating mass（ERM） motors are routinely utilized due to their lightweight design and efficient ability to evoke strong tactile sensations. By adjusting input voltages, ERMs can yield different stimuli, but the effects of their physical properties on PI remain ***, we developed the physical model of the ERM-skin system and optimized the parameters affecting PI. Moreover, the relationship between stimulus and perception was derived based on Fechner?s law. Three experiments were conducted on fifteen subjects（ten males and five females, aged 24.40 ± 2.87 years） to identify the vibration parameters and corresponding PI to verify the proposed PI model. ERMs in this study were attached to phantom skin/forearm with slim adhesive tape to minimize the interference. Experiment 1 performed vibration calibration with ERM attached to the skin phantom to simulate the actual configuration. Then, the relative and absolute PI of subjects on specific stimuli were acquired in Experiments 2 and *** fitting reliability of the proposed PI model was evaluated on fifteen subjects with R2of 0.73 ± 0.07 and root mean squared error（RMSE） of 1.35 ± 0.28. Overall, the proposed PI model established the quantitative relationship between stimulus parameters（vibration parameters and physical parameters） and subjective PI, which provided theoretical support for ERM optimization and vibrotactile modulation.

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