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Advances in Graphene‑Based Electrode for Triboelectric Nanogenerator

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Nano-Micro Letters 2025年第1期17卷 378-403页

作者： Bin Xie Yuanhui Guo Yun Chen Hao Zhang Jiawei Xiao Maoxiang Hou Huilong Liu Li Ma Xin Chen Chingping Wong State Key Laboratory of Precision Electronic Manufacturing technology and Equipment Guangdong University of TechnologyGuangzhou 510006People’s Republic of China School of Electromechanical engineering Guangdong University of TechnologyGuangzhou 510006People’s Republic of China School of Materials Science and engineering Georgia Institute of TechnologyAtlantaGA 30332USA

With the continuous development of wearable electronics,wireless sensor networks and other micro-electronic devices,there is an increasingly urgent need for miniature,flexible and efficient nanopower generation *** nanogenerator(TENG)technology can convert small mechanical energy into electricity,which is expected to address this *** the core component of TENG,the choice of electrode materials significantly affects its *** metal electrode materials often suffer from problems such as durability,which limits the further application of ***,as a novel electrode material,shows excellent prospects for application in TENG owing to its unique structure and excellent electrical *** review systematically summarizes the recent research progress and application prospects of TENGs based on graphene *** precision processing methods of graphene electrodes are introduced,and the applications of graphene electrode-based TENGs in various scenarios as well as the enhancement of graphene electrodes for TENG performance are *** addition,the future development of graphene electrode-based TENGs is also prospectively discussed,aiming to promote the continuous advancement of graphene electrode-based TENGs.

关键词： Triboelectric nanogenerator Precision processing Graphene electrode Self-powered sensor

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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 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

Preparation and Performance of Ternary Early Strength Agent and Quercetin Composite Cement Sealing Material

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Journal of Wuhan university of technology(Materials Science) 2025年第1期40卷 130-140页

作者： LIU Jian CHEN Meiting JI Xiaoli XU Chao WANG Chunmei Department of Safety Science and engineering Anhui University of Science and TechnologyHuainan 232001China Key Laboratory of Mine Safety and High Efficient Mining Jointly Built by Province and Education Ministry Anhui University of Science and TechnologyHuainan 232001China Department of Chemical engineering and Explosives Anhui University of Science and TechnologyHuainan 232001China

A ternary early-strengthening agent consisting of calcium formate+triethanolamine+lithium sulfate was compounded with quercetin to shorten the setting time of cementitious materials while ensuring their early *** optimum ratio of the three early-strengthening agents was determined as 0.5%calcium formate+0.04%triethanolamine+0.4%lithium sulfate by response surface *** effects of the ternary early-strengthening agent composed of calcium formate+triethanolamine(TEA)+lithium sulfate on cementitious pore sealing materials under the synergistic effect of quercetin were studied by means of the performance tests of compressive strength,fluidity,and setting time,and the microstructural characterizations of X-ray powder diffractometer(XRD),thermogravimetry(TG-DSC)and scanning electron microscopy(SEM).The study shows that the synergistic effect of ternary early-strengthening agent and quercetin forms a multi-performance composite admixture for cementitious *** best performance was obtained with the compounding scheme of 0.5%calcium formate+0.04%triethanolamine+0.4%lithium sulfate ternary early-strengthening agent and 0.05%*** compressive strength of 1,3,7,and 28 d are 94.8%,39.8%,42%,and 28%higher than those of the blank group,*** initial time and final setting time are 41 and 57 minutes,*** to the microscopic analysis,the network and fibrous C-S-H gels generated by ternary early-strengthening agents are attached to the surface promoted by quercetin,which forms skeleton support while thickening and solidifying the cement slurry,which enhances the early compressive strength of the cement-based materials.

关键词： sealing material ternary early-strengthening agent quercetin synergetic effect response surface methodology

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Metal nanoparticles decorated Cofe-(oxy)hydroxysulfides nanosheets fabricated by a general strategy for electrocatalytic water splitting

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Journal of Energy Chemistry 2025年第1期100卷 26-38页

作者： Xiaodong Yang Haochen Shen Xiaoming Xiao Zhichao Li Qi Zhou Wei Yang Bin Jiang Yongli Sun Luhong Zhang Zhenhua Yan School of Chemical engineering and technology Tianjin University Key Laboratory of Advanced Energy Materials Chemistry (Ministry of Education) Nankai University

This study presents a novel method to fabricate metal-decorated,sulfur-doped layered double hydroxides （M/SLDH） through spontaneous redox and sulfurization *** developed Ag/SLDH and Pt/SLDH catalysts with abundant heterogeneous interfaces and hierarchical nanostructures demonstrated outstanding oxygen evolution reaction （oER） and hydrogen evolution reaction （HER） performance,achieving low overpotentials of 212 and 35 mV at 10 mA cm-2in 1 M KoH,*** both anode and cathode in water splitting,they required only 1.47 V to reach 10 mA cm-2and exhibited high structural robustness,maintaining stability at 1000 mA cm-2for 300 ***-situ Raman analysis revealed that the synergistic effects of metal nanoparticles and S doping significantly promote the transformation into the S-Co1-xfexooH layer,which serves as the active phase for water ***,ultraviolet photoelectron spectroscopy （UPS） and density functional theory （DfT） analyses indicated that incorporating metal nanoparticles and S doping increase electron density near the fermi level and reduce reaction energy barriers,thus enhancing intrinsic oER and HER *** study provides a scalable strategy for synthesizing high-performance electrocatalysts for water splitting,with promising potential for broader applications.

关键词： Ultraviolet photoelectron spectroscopy

Dielectric-ion-conductive ZnNb2o6 layer enabling rapid desolvation and diffusion for dendrite-free Zn metal batteries

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Journal of Energy Chemistry 2025年第1期100卷 693-701页

作者： Haifeng Yang Jian Wang Panpan Zhang Xiaomin Cheng Qinghua Guan Jing Dong Bixian Chen Lujie Jia Jing Zhang Yongzheng Zhang Yunjian Liu Hongzhen Lin School of Materials Science and engineering Jiangsu University i-Lab & CAS Key Laboratory of Nanophotonic Materials and Devices Suzhou Institute of Nano-Tech and Nano-Bionics Chinese Academy of Sciences Helmholtz Institute Ulm (HIU) Karlsruhe Institute of technology (KIT) School of Materials Science and engineering Xi'an University of Technology State Key Laboratory of Chemical engineering East China University of Science and Technology

Rechargeable aqueous zinc-metal batteries （AZMBs） are promising candidates for large-scale energy storage systems due to their low cost and high ***,their performance and sustainability are significantly hindered by the sluggish desolvation kinetics at the electrode/electrolyte interface and the corresponding hydrogen evolution reaction where active water molecules tightly participate in the Zn（H2o）62+solvation ***,learnt from self-generated solid electrolyte interphase （SEI） in anodes,the dielectric but ion-conductive zinc niobate nanoparticles artificial layer is constructed on metallic Zn surface （ZNB@Zn）,acting as a rapid desolvation *** zincophilic and dielectric-conductive properties of ZNB layer accelerate interfacial desolvation/diffusion and suppress surface corrosion or dendrite formation,achieving uniform Zn plating/stripping behavior,as confirmed by electronic/optical microscopies and interface spectroscopical measurements together with theoretical ***,the as-prepared ZNB@Zn electrode exhibits excellent cycling stability of over 2000 h and robust reversibility （99.54%） even under high current density and depth of discharge ***,the assembled ZNB@Zn-based full cell displays high capacity-retention rate of 80.21%after 3000 cycles at 5 A g-1and outstanding rate performance up to 10 A *** large-areal pouch cell is stabilized for hundreds of cycles,highlighting the bright prospects of the dielectric but ion-conductive layer in further application of AZMBs.

关键词： Zn metal battery Dielectric artificial layer Rapid ion diffusion Zincophilic diffusion Active water inhibition

An Improved Practical Byzantine fault-Tolerant Algorithm Based on XGBoost Grouping for Consortium Chains

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Computers, Materials & Continua 2025年第1期82卷 1295-1311页

作者： Xiaowei Wang Haiyang Zhang Jiasheng Zhang Yingkai Ge Kexin Cui Zifu Peng Zhengyi Li Lihua Wang College of Electronic and Information engineering Shandong University of Science and TechnologyQingdao266590China

In response to the challenges presented by the unreliable identity of the master node,high communication overhead,and limited network support size within the Practical Byzantine fault-Tolerant(PBfT)algorithm for consortium chains,we propose an improved PBfT algorithm based on XGBoost grouping called XG-PBfT in this ***-PBfT constructs a dataset by training important parameters that affect node performance,which are used as classification indexes for *** XGBoost algorithm then is employed to train the dataset,and nodes joining the system will be grouped according to the trained grouping *** them,the nodes with higher parameter indexes will be assigned to the consensus group to participate in the consensus,and the rest of the nodes will be assigned to the general group to receive the consensus *** order to reduce the resource waste of the system,XG-PBfT optimizes the consensus protocol for the problem of high complexity of PBfT ***,we evaluate the performance of *** experimental results show that XG-PBfT can significantly improve the performance of throughput,consensus delay and communication complexity compared to the original PBfT algorithm,and the performance enhancement is significant compared to other algorithms in the case of a larger number of *** results demonstrate that the XG-PBfT algorithm is more suitable for large-scale consortium chains.

关键词： Consortium chain PBfT grouping reputation XGBoost

optimal Scheduling of an Independent Electro-Hydrogen System with Hybrid Energy Storage Using a Multi-objective Standardization fusion Method

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Energy engineering 2025年第1期122卷 63-84页

作者： SuliangMa ZeqingMeng Mingxuan Chen Yuan Jiang School of Electrical and Control engineering North China University of TechnologyBeijing100144China ChinaThree Gorges technology Co. Ltd.Beijing100032China School of Automation and Electrical engineering University of Science and Technology BeijingBeijing100083China

In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is ***,it presents a challenge due to the significant deviations in values ofmultiple optimization objective functions caused by their physical *** deviations seriously affect the scheduling process.A novel standardization fusion method has been established to address this issue by analyzing the variation process of each objective function’s *** optimal scheduling results of IEHS with HESS indicate that the economy and overall energy loss can be improved 2–3 times under different optimization *** proposed method better balances all optimization objective functions and reduces the impact of their *** the cost of BESS decreases by approximately 30%,its participation deepens by about 1 ***,if the price of the electrolyzer is less than 15￥/kWh or if the cost of the fuel cell drops below 4￥/kWh,their participation will increase *** study aims to provide a more reasonable approach to solving multi-objective optimization problems.

关键词： Electro-hydrogen system multi-objective optimization standardization method hybrid energy storage system

Advances in the Development of Gradient Scaffolds Made of Nano‑Micromaterials for Musculoskeletal Tissue Regeneration

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Nano-Micro Letters 2025年第3期17卷 455-500页

作者： Lei fang Xiaoqi Lin Ruian Xu Lu Liu Yu Zhang feng Tian Jiao Jiao Li Jiajia Xue Beijing Laboratory of Biomedical Materials Beijing University of Chemical TechnologyBeijing 100029People’s Republic of China State Key Laboratory of organic‑Inorganic Composites Beijing University of Chemical TechnologyBeijing 100029People’s Republic of China School of Biomedical engineering Faculty of Engineering and ITUniversity of Technology SydneySydneyNSW 2007Australia

The intricate hierarchical structure of musculoskeletal tissues,including bone and interface tissues,necessitates the use of complex scaffold designs and material structures to serve as tissue-engineered *** has led to growing interest in the development of gradient bone scaffolds with hierarchical structures mimicking the extracellular matrix of native tissues to achieve improved therapeutic *** on the anatomical characteristics of bone and interfacial tissues,this review provides a summary of current strategies used to design and fabricate biomimetic gradient scaffolds for repairing musculoskeletal tissues,specifically focusing on methods used to construct compositional and structural gradients within the *** latest applications of gradient scaffolds for the regeneration of bone,osteochondral,and tendon-to-bone interfaces are ***,the current progress of testing gradient scaffolds in physiologically relevant animal models of skeletal repair is discussed,as well as the challenges and prospects of moving these scaffolds into clinical application for treating musculoskeletal injuries.

关键词： Gradient scaffolds Musculoskeletal tissues Advanced manufacturing Biomaterials Tissue regeneration

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Stochastic Augmented-Based Dual-Teaching for Semi-Supervised Medical Image Segmentation

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Computers, Materials & Continua 2025年第1期82卷 543-560页

作者： Hengyang Liu Yang Yuan Pengcheng Ren Chengyun Song fen Luo School of Computer Science and engineering Chongqing University of TechnologyChongqing400054China College of Artificial Intelligence Chongqing Technology and Business UniversityChongqing400067China

Existing semi-supervisedmedical image segmentation algorithms use copy-paste data augmentation to correct the labeled-unlabeled data distribution ***,current copy-paste methods have three limitations:(1)training the model solely with copy-paste mixed pictures from labeled and unlabeled input loses a lot of labeled information;(2)low-quality pseudo-labels can cause confirmation bias in pseudo-supervised learning on unlabeled data;(3)the segmentation performance in low-contrast and local regions is less than *** design a Stochastic Augmentation-Based Dual-Teaching Auxiliary Training Strategy(SADT),which enhances feature diversity and learns high-quality features to overcome these *** be more precise,SADT trains the Student Network by using pseudo-label-based training from Teacher Network 1 and supervised learning with labeled data,which prevents the loss of rare labeled *** introduce a bi-directional copy-pastemask with progressive high-entropy filtering to reduce data distribution disparities and mitigate confirmation bias in *** the mixed images,Deep-Shallow Spatial Contrastive Learning(DSSCL)is proposed in the feature spaces of Teacher Network 2 and the Student Network to improve the segmentation capabilities in low-contrast and local *** this procedure,the features retrieved by the Student Network are subjected to a random feature perturbation *** two openly available datasets,extensive trials show that our proposed SADT performs much better than the state-ofthe-art semi-supervised medical segmentation *** only 10%of the labeled data for training,SADT was able to acquire a Dice score of 90.10%on the ACDC(Automatic Cardiac Diagnosis Challenge)dataset.

关键词： Semi-supervised medical image segmentation contrastive learning stochastic augmented