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Energy Engineering 2025年第1期122卷 203-220页

作者： Yu Zhang Daoyu Zhang TiezhouWu School of Electrical and Electronic Engineering Hubei University of TechnologyWuhan430068China

Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery ***,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity ***,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model *** address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural ***,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity ***,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network *** validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging *** experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.

关键词： Lithium-ion battery state of health differential thermal voltammetry Sparrow Search Algorithm

An Iterated Greedy Algorithm with Memory and Learning Mechanisms for the Distributed Permutation Flow Shop Scheduling Problem

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Computers, Materials & Continua 2025年第1期82卷 371-388页

作者： Binhui Wang Hongfeng Wang College of Information science and Engineering Northeastern UniversityShenyang110819China

The distributed permutation flow shop scheduling problem(DPFSP)has received increasing attention in recent *** iterated greedy algorithm(IGA)serves as a powerful optimizer for addressing such a problem because of its straightforward,single-solution evolution ***,a potential draw-back of IGA is the lack of utilization of historical information,which could lead to an imbalance between exploration and exploitation,especially in large-scale *** a consequence,this paper develops an IGA with memory and learning mechanisms(MLIGA)to efficiently solve the DPFSP targeted at the ***,we incorporate a memory mechanism to make a more informed selection of the initial solution at each stage of the search,by extending,reconstructing,and reinforcing the information from previous *** addition,we design a twolayer cooperative reinforcement learning approach to intelligently determine the key parameters of IGA and the operations of the memory ***,to ensure that the experience generated by each perturbation operator is fully learned and to reduce the prior parameters of MLIGA,a probability curve-based acceptance criterion is proposed by combining a cube root function with custom *** last,a discrete adaptive learning rate is employed to enhance the stability of the memory and *** ablation experiments are utilized to verify the effectiveness of the memory mechanism,and the results show that this mechanism is capable of improving the performance of IGA to a large ***,through comparative experiments involving MLIGA and five state-of-the-art algorithms on 720 benchmarks,we have discovered that MLI-GA demonstrates significant potential for solving large-scale *** indicates that MLIGA is well-suited for real-world distributed flow shop scheduling.

关键词： Distributed permutation flow shop scheduling makespan iterated greedy algorithm memory mechanism cooperative reinforcement learning

Industrial Control Anomaly Detection Based on Distributed Linear Deep Learning

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Computers, Materials & Continua 2025年第1期82卷 1129-1150页

作者： Shijie Tang Yong Ding Huiyong Wang School of Computer science and Information Security Guilin University of Electronic TechnologyGuilin541004China School of Electronic Engineering and Automation Guilin University of Electronic TechnologyGuilin541004China Guangxi Engineering Research Center of Industrial Internet Security and Blockchain Guilin University of Electronic TechnologyGuilin541004China Institute of Cyberspace Technology HKCT Institute for Higher EducationHong Kong999077China School of Mathematics&Computing science Guilin University of Electronic TechnologyGuilin541004China

As more and more devices in Cyber-Physical Systems(CPS)are connected to the Internet,physical components such as programmable logic controller(PLC),sensors,and actuators are facing greater risks of network attacks,and fast and accurate attack detection techniques are *** key problem in distinguishing between normal and abnormal sequences is to model sequential changes in a large and diverse field of time *** address this issue,we propose an anomaly detection method based on distributed deep *** method uses a bilateral filtering algorithm for sequential sequences to remove noise in the time series,which can maintain the edge of discrete *** use a distributed linear deep learning model to establish a sequential prediction model and adjust the threshold for anomaly detection based on the prediction error of the validation *** method can not only detect abnormal attacks but also locate the sensors that cause *** conducted experiments on the Secure Water Treatment(SWAT)and Water Distribution(WADI)public *** experimental results show that our method is superior to the baseline method in identifying the types of attacks and detecting efficiency.

关键词： Anomaly detection CPS deep learning MLP(multi-layer perceptron)

Alternative Strategy for Development of Dielectric Calcium Copper Titanate‑Based Electrolytes for Low‑Temperature Solid Oxide Fuel Cells

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Nano-Micro Letters 2025年第1期17卷 310-332页

作者： Sajid Rauf Muhammad Bilal Hanif Zuhra Tayyab Matej Veis MAKYousaf Shah Naveed Mushtaq Dmitry Medvedev Yibin Tian Chen Xia Martin Motola Bin Zhu College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060People’s Republic of China Department of Inorganic Chemistry Faculty of Natural SciencesComenius University BratislavaIlkovicova684215 BratislavaSlovakia Energy Storage Joint Research Center School of Energy and EnvironmentSoutheast UniversityNanjing 210096People’s Republic of China Hydrogen Energy Laboratory Ural Federal University620002 EkaterinburgRussia Laboratory of Electrochemical Devices Based on Solid Oxide Proton Electrolytes Institute of High Temperature Electrochemistry620066 EkaterinburgRussia School of Microelectronics Hubei UniversityWuhan 430062People’s Republic of China

The development of low-temperature solid oxide fuel cells(LT-SOFCs)is of significant importance for realizing the widespread application of *** has stimulated a substantial materials research effort in developing high oxide-ion conductivity in the electrolyte layer of *** this context,for the first time,a dielectric material,CaCu_(3)Ti_(4)O_(12)(CCTO)is designed for LT-SOFCs electrolyte application in this *** individual CCTO and its heterostructure materials with a p-type Ni_(0.8)Co_(0.15)Al_(0.05)LiO_(2−δ)(NCAL)semiconductor are evaluated as alternative electrolytes in LT-SOFC at 450–550℃.The single cell with the individual CCTO electrolyte exhibits a power output of approximately 263 mW cm^(-2) and an open-circuit voltage(OCV)of 0.95 V at 550℃,while the cell with the CCTO–NCAL heterostructure electrolyte capably delivers an improved power output of approximately 605 mW cm^(-2) along with a higher OCV over 1.0 V,which indicates the introduction of high hole-conducting NCAL into the CCTO could enhance the cell performance rather than inducing any potential short-circuiting *** is found that these promising outcomes are due to the interplay of the dielectric material,its structure,and overall properties that led to improve electrochemical mechanism in CCTO–***,density functional theory calculations provide the detailed information about the electronic and structural properties of the CCTO and NCAL and their heterostructure CCTO–*** study thus provides a new approach for developing new advanced electrolytes for LT-SOFCs.

关键词： LT-SOFCs Dielectric CaCu_(3)Ti_(4)O_(12) Semiconductor Ni_(0.8)Co_(0.15)Al_(0.05)LiO_(2−δ) Ionic conductivity Heterostructure electrolyte

“Zero‑Strain” NiNb_(2)O_(6) Fibers for All‑Climate Lithium Storage

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Nano-Micro Letters 2025年第1期17卷 348-360页

作者： Yan Zhao Qiang Yuan Liting Yang Guisheng Liang Yifeng Cheng Limin Wu Chunfu Lin Renchao Che College of Physics Donghua UniversityShanghai 201620People’s Republic of China School of Materials science and Engineering Institute of Materials for Energy and EnvironmentQingdao UniversityQingdao 266071People’s Republic of China Laboratory of Advanced Materials Shanghai Key Laboratory of Molecular Catalysis and Innovative MaterialsAcademy for Engineering&TechnologyFudan UniversityShanghai 200438People’s Republic of China Zhejiang Laboratory Hangzhou 311100People’s Republic of China Inner Mongolia University Hohhot 010021People’s Republic of China

Niobates are promising all-climate Li^(+)-storage anode material due to their fast charge transport,large specific capacities,and resistance to electrolyte ***,their moderate unit-cellvolume expansion(generally 5%–10%)during Li^(+)storage causes unsatisfactory long-term ***,“zero-strain”NiNb_(2)O_(6) fibers are explored as a new anode material with comprehensively good electrochemical *** Li^(+)storage,the expansion of electrochemical inactive NiO_(6) octahedra almost fully offsets the shrinkage of active NbO_(6) octahedra through reversible O *** superior volume-accommodation capability of the NiO_(6) layers guarantees the“zero-strain”behavior of NiNb_(2)O_(6) in a broad temperature range(0.53%//0.51%//0.74%at 25//−10//60℃),leading to the excellent cyclability of the NiNb_(2)O_(6) fibers(92.8%//99.2%//91.1%capacity retention after 1000//2000//1000 cycles at 10C and 25//−10//60℃).This NiNb_(2)O_(6) material further exhibits a large reversible capacity(300//184//318 mAh g−1 at 0.1C and 25//−10//60℃)and outstanding rate performance(10 to 0.5C capacity percentage of 64.3%//50.0%//65.4%at 25//−10//60℃).Therefore,the NiNb_(2)O_(6) fibers are especially suitable for large-capacity,fast-charging,long-life,and all-climate lithium-ion batteries.

关键词： NiNb_(2)O_(6)porous fiber “Zero-strain”mechanism Electrochemical property Harsh-temperature operation Operando characterization

Advancements and Challenges in Organic–Inorganic Composite Solid Electrolytes for All‑Solid‑State Lithium Batteries

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Nano-Micro Letters 2025年第1期17卷 46-97页

作者： Xueyan Zhang Shichao Cheng Chuankai Fu Geping Yin Liguang Wang Yongmin Wu Hua Huo State Key Laboratory of Space Power‑Sources School of Chemistry and Chemical EngineeringHarbin Institute of TechnologyHarbin 150001People’s Republic of China College of Chemical and Biological Engineering Zhejiang UniversityHangzhou 310058People’s Republic of China State Key Laboratory of Space Power-Sources 2965 Dongchuan RoadMinhang DistrictShanghai 200240People’s Republic of China

To address the limitations of contemporary lithium-ion batteries,particularly their low energy density and safety concerns,all-solid-state lithium batteries equipped with solid-state electrolytes have been identified as an up-and-coming *** the various SEs,organic–inorganic composite solid electrolytes(OICSEs)that combine the advantages of both polymer and inorganic materials demonstrate promising potential for large-scale ***,OICSEs still face many challenges in practical applications,such as low ionic conductivity and poor interfacial stability,which severely limit their *** review provides a comprehensive overview of recent research advancements in ***,the influence of inorganic fillers on the main functional parameters of OICSEs,including ionic conductivity,Li+transfer number,mechanical strength,electrochemical stability,electronic conductivity,and thermal stability are systematically *** lithium-ion conduction mechanism of OICSE is thoroughly analyzed and concluded from the microscopic ***,the classic inorganic filler types,including both inert and active fillers,are categorized with special emphasis on the relationship between inorganic filler structure design and the electrochemical performance of ***,the advanced characterization techniques relevant to OICSEs are summarized,and the challenges and perspectives on the future development of OICSEs are also highlighted for constructing superior ASSLBs.

关键词： Composite solid electrolytes Inorganic filler Interfacial stability Li-ion conduction mechanism Characterization techniques

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

Dual‑Donor‑Induced Crystallinity Modulation Enables 19.23% Efficiency Organic Solar Cells

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Nano-Micro Letters 2025年第3期17卷 376-388页

作者： Anhai Liang Yuqing Sun Sein Chung Jiyeong Shin Kangbo Sun Chaofeng Zhu Jingjing Zhao Zhenmin Zhao Yufei Zhong Guangye Zhang Kilwon Cho Zhipeng Kan Center On Nanoenergy Research Institute of Science and Technology for Carbon Peak&NeutralitySchool of Physical Science&TechnologyGuangxi UniversityNanning 530004People’s Republic of China Department of Chemical Engineering Pohang University of Science and TechnologyPohang 37673South Korea College of New Materials and New Energies Shenzhen Technology UniversityShenzhen 518118People’s Republic of China Zhejiang Engineering Research Center for Fabrication and Application of Advanced Photovoltaic Materials School of Materials Science and EngineeringNingboTech UniversityNingbo 315100People’s Republic of China State Key Laboratory of Featured Metal Materials and Life-Cycle Safety for Composite Structures Nanning 530004People’s Republic of China

Trap-assisted charge recombination is one of the primary limitationsof restricting the performance of organic solar cells. However, effectivelyreducing the presence of traps in the photoactive layer remains ***, wide bandgap polymer donor PTzBI-dF is demonstrated as an effectivemodulator for enhancing the crystallinity of the bulk heterojunction active layerscomposed of D18 derivatives blended with Y6, leading to dense and orderedmolecular packings, and thus, improves photoluminescence quenching *** a result, the photovoltaic devices exhibit reduced trap-assisted charge recombinationlosses, achieving an optimized power conversion efficiency of over 19%.Besides the efficiency enhancement, the devices comprised of PTzBI-dF as athird component simultaneously attain decreased current leakage, improved chargecarrier mobilities, and suppressed bimolecular charge recombination, leading toreduced energy losses. The advanced crystalline structures induced by PTzBI-dFand its characteristics, such as well-aligned energy level, and complementaryabsorption spectra, are ascribed to the promising performance *** findings suggest that donor phase engineering is a feasible approach to tuning the molecular packings in the active layer, providingguidelines for designing effective morphology modulators for high-performance organic solar cells.

关键词： Trap-assisted charge recombination Photoluminescence Miscibility Current leakage Power conversion efficiency

Enhanced post-combustion CO2 capture and direct air capture by plasma surface functionalization of graphene adsorbent

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Journal of Energy Chemistry 2025年第1期100卷 653-664页

作者： Rahul Navik Eryu Wang Xiao Ding Huang Yunyi Yiyu Liu Jia Li Guangdong-Hong Kong Joint Laboratory for Carbon Neutrality Jiangmen Laboratory of Carbon and Science and Technology Guangzhou HKUST Fok Ying Tung Research Institute The Hong Kong University of science and Technology (Guangzhou) Carbon Neutrality and Climate Change Thrust Society Hub The Hong Kong University of Science and Technology (Guangzhou) Stoddart Institute of Molecular science Department of Chemistry Zhejiang University

Graphene has enormous potential to capture CO2due to its unique properties and ***,graphene-based adsorbents have drawbacks of lower CO2adsorption capacity and poor *** work demonstrates a one-step rapid and sustainable N2/H2plasma treatment process to prepare graphene-based sorbent material with enhanced CO2adsorption *** treatment directly enriches amine species,increases surface area,and improves textural *** CO2adsorption capacity increases from 1.6 to 3.3 mmol/g for capturing flue gas,and from 0.14 to 1.3 mmol/g for direct air capture （DAC）.Importantly,the electrothermal property of the plasma-modified aerogels has been significantly improved,resulting in faster heating rates and significantly reducing energy consumption compared to conventional external heating for regeneration of *** aerogels display improved selectivity of 42 and 87 after plasma modification for 5 and 10 min,*** plasma-treated aerogels display minimal loss between 17%and 19% in capacity after 40 adsorption/desorption cycles,rendering excellent *** N2/H2plasma treatment of adsorbent materials would lower energy expenses and prevent negative effects on the global economy caused by climate change.

关键词： Carbon neutrality CO 2 capture Climate change Plasma treatment Graphene aerogel

Boosting hydrocarbon conversion via Cu-doping induced oxygen vacancies on CeO2 in CO2 electroreduction

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Journal of Energy Chemistry 2025年第1期100卷 66-76页

作者： Lei Xue Tong Shi Chenhui Han Heng Zhang Fenrong Liu Haorun Li Yan Wang Xiaojun Gu Shanghong Zeng Inner Mongolia Key Laboratory of Chemistry and Physics of Rare Earth Materials School of Chemistry and Chemical Engineering Inner Mongolia University State Key Laboratory of Coal Conversion Institute of Coal Chemistry Chinese Academy of Sciences Institute of Catalysis Department of Chemistry Zhejiang University national Key Laboratory of Baiyunobo Rare Earth Resource Research and Comprehensive Utilization Baotou Research Institute of Rare Earths

Conversion of CO2back to hydrocarbons is the most direct way of closing the“carbon cycle”,and its significance is further enlarged if this process is driven by renewable energies such as ***,precisely controlling the product selectivity towards hydrocarbons against the competitive hydrogen evolution remains challenging,especially for Cu-based ***,we report a novel defect engineering strategy,by which Cu-doping-induced oxygen vacancies on CeO2nanorods were effectively created,with adjustable vacancy/Cu *** resulting optimum catalyst shows up to 79% catalytic current density to hydrocarbons （excluding CO）,with 49% faradaic efficiency to *** and density functional theory unveil that the ratio between oxygen vacancy and Cu affects significantly the formation of*CHO and activation of H2O,which leads to the following deep hydrogenation to *** findings may spur new insights for designing and developing more controllable chemical process relevant to CO2utilization.

关键词： Nanorods