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Defects‑Rich Heterostructures Trigger Strong Polarization Coupling in Sulfides/Carbon Composites with Robust Electromagnetic Wave Absorption

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Nano-Micro Letters 2025年第1期17卷 528-547页

作者： Jiaolong Liu Siyu Zhang Dan Qu Xuejiao Zhou Moxuan Yin Chenxuan Wang Xuelin Zhang Sichen Li Peijun Zhang Yuqi Zhou Kai Tao Mengyang Li Bing Wei Hongjing Wu Mengyang Li Bing Wei Hongjing Wu school of Physics Xidian UniversityXi’an 710071People’s Republic of China school of Advanced Materials and Nanotechnology State Key Discipline Laboratory of Wide Band Gap Semiconductor TechnologyXidian UniversityXi’an 710071People’s Republic of China school of Microelectronics Xidian UniversityXi’an 710071People’s Republic of China school of Telecommunication Engineering Xidian UniversityXi’an 710071People’s Republic of China MOE Key Laboratory of Material Physics and Chemistry Under Extraordinary School of Physical Science and TechnologyNorthwestern Polytechnical UniversityXi’an 710072People’s Republic of China The Ministry of Education Key Laboratory of Micro and Nano Systems forAerospace School of Mechanical EngineeringNorthwestern PolytechnicalUniversityXi’an 710072People’s Republic of China

Defects-rich heterointerfaces integrated with adjustable crystalline phases and atom vacancies,as well as veiled dielectric-responsive character,are instrumental in electromagnetic *** methods,however,constrain their delicate ***,an innovative alternative is proposed:carrageenan-assistant cations-regulated(CACR)strategy,which induces a series of sulfides nanoparticles rooted in situ on the surface of carbon *** unique configuration originates from strategic vacancy formation energy of sulfides and strong sulfides-carbon support interaction,benefiting the delicate construction of defects-rich heterostructures in M_(x)S_(y)/carbon composites(M-CAs).Impressively,these generated sulfur vacancies are firstly found to strengthen electron accumulation/consumption ability at heterointerfaces and,simultaneously,induct local asymmetry of electronic structure to evoke large dipole moment,ultimately leading to polarization coupling,i.e.,defect-type interfacial ***“Janus effect”(Janus effect means versatility,as in the Greek two-headed Janus)of interfacial sulfur vacancies is intuitively confirmed by both theoretical and experimental investigations for the first ***,the sulfur vacancies-rich heterostructured Co/Ni-CAs displays broad absorption bandwidth of 6.76 GHz at only 1.8 mm,compared to sulfur vacancies-free CAs without any dielectric *** defects-rich heterostructures,this one-pot CACR strategy may steer the design and development of advanced nanomaterials,boosting functionality across diverse application domains beyond electromagnetic response.

关键词： Defects-rich heterointerfaces Sulfides Polarization coupling Electromagnetic wave absorption

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Overview and Prospect of Distributed Energy P2P Trading

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Energy Engineering 2025年第1期122卷 379-404页

作者： Jiajia Liu Mingxing Tian Xusheng Mao school of Automation and Electrical Engineering Lanzhou Jiaotong UniversityLanzhou730070China

After a century of relative stability in the electricity sector,the widespread adoption of distributed energy resources,along with recent advancements in computing and communication technologies,has fundamentally altered how energy is consumed,traded,and *** change signifies a crucial shift as the power system evolves from its traditional hierarchical organization to a more decentralized *** the heart of this transformation are innovative energy distribution models,like peer-to-peer(P2P)sharing,which enable communities to collaboratively manage their energy *** effectiveness of P2P sharing not only improves the economic prospects for prosumers,who generate and consume energy,but also enhances energy resilience and *** allows communities to better leverage local resources while fostering a sense of collective responsibility and collaboration in energy ***,there is still no extensive implementation of such sharing models in today’s *** on distributed energy P2P trading is still in the exploratory stage,and it is particularly important to comprehensively understand and analyze the existing distributed energy P2P trading *** paper contributes with an overview of the P2P markets that starts with the network framework,market structure,technical approach for trading mechanism,and blockchain technology,moving to the outlook in this field.

关键词： Distributed energy P2P market mechanisms classification and comparison

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Optimizing battery deployment: Aging trajectory prediction enabling homogenous performance grouping

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Journal of Energy Chemistry 2025年第1期100卷 565-577页

作者： Shuquan Wang Feng Gao Zhan Ma Hao Tian Yusen Zhang school of Control Science and Engineering Shandong University Key Lab of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University

As battery deployments in electric vehicles and energy storage systems grow, ensuring homogeneous performance across units is crucial. We propose a multi-derivative imaging fusion(MDIF) model, employing advanced imaging and machine learning to predict battery aging trajectories from minimal initial data, thus facilitating effective performance grouping before deployment. Utilizing a derivative strategy and Gramian Angular Difference Field for dimensional enhancement, the MDIF model uncovers subtle predictive features from discharge curve data after only ten cycles. The architecture includes a parallel convolutional neural network with lateral connections to enhance feature integration and *** on a self-developed dataset, the model achieves an average root-mean-square error of 0.047 Ah and an average mean absolute percentage error of 1.60%, demonstrating high precision and *** robustness is further validated through transfer learning on two publicly available datasets, adapting with minimal retraining. This approach significantly reduces the testing cycles required, lowering both time and costs associated with battery testing. By enabling precise battery behavior predictions with limited data, the MDIF model optimizes battery utilization and deployment strategies, enhancing system efficiency and sustainability.

关键词： Lithium-ion battery Battery prognostics Fusion model Convolutional neural network Transfer learning

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New types of singular solutions of conformal Q-curvature equations

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Acta Mathematica Sinica,English Series 2025年

作者： Zongming Guo Zhongyuan Liu Fangshu Wan Department of Mathematics Henan Normal University school of Mathematics and Statistics Henan University school of Mathematical Sciences Anhui University

We construct radial and non-radial singular solutions u ∈ C4（B{0}） with a non-removable singular point x = 0 for the conformal Q-curvature equation:■where B = {x ∈ R4: |x| D0≥ 0, and satisfying ■Moreover, detailed asymptotic expansions near x = 0 of these radial and non-radial singular solutions can be established. As an application, we can also obtain the existence of two types of solutions u ∈ C4（R4■） to the problem ■ satisfying |x|-2u（x） →-D D0, and satisfying u（x） = o（|x|2） uniformly as |x| → ∞.

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LoRa Sense:Sensing and Optimization of LoRa Link Behavior Using Path-Loss Models in Open-Cast Mines

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 425-466页

作者： Bhanu Pratap Reddy Bhavanam Prashanth Ragam school of Computer Science and Engineering VIT-AP UniversityAmaravati52237India

The Internet of Things(IoT)has orchestrated various domains in numerous applications,contributing significantly to the growth of the smart world,even in regions with low literacy rates,boosting socio-economic *** study provides valuable insights into optimizing wireless communication,paving the way for a more connected and productive future in the mining *** IoT revolution is advancing across industries,but harsh geometric environments,including open-pit mines,pose unique challenges for reliable *** advent of IoT in the mining industry has significantly improved communication for critical operations through the use of Radio Frequency(RF)protocols such as Bluetooth,Wi-Fi,GSM/GPRS,Narrow Band(NB)-IoT,SigFox,ZigBee,and Long Range Wireless Area Network(LoRaWAN).This study addresses the optimization of network implementations by comparing two leading free-spreading IoT-based RF protocols such as ZigBee and *** field tests are conducted in various opencast mines to investigate coverage potential and signal *** is tested in the Tadicherla open-cast coal mine in ***,LoRaWAN field tests are conducted at one of the associated cement companies(ACC)in the limestone mine in Bargarh,India,covering both Indoor-toOutdoor(I2O)and Outdoor-to-Outdoor(O2O)environments.A robust framework of path-loss models,referred to as Free space,Egli,Okumura-Hata,Cost231-Hata and Ericsson models,combined with key performance metrics,is employed to evaluate the patterns of signal *** field testing and careful data analysis revealed that the Egli model is the most consistent path-loss model for the ZigBee protocol in an I2O environment,with a coefficient of determination(R^(2))of 0.907,balanced error metrics such as Normalized Root Mean Square Error(NRMSE)of 0.030,Mean Square Error(MSE)of 4.950,Mean Absolute Percentage Error(MAPE)of 0.249 and Scatter Index(SI)of *** the O2O scenario,the Ericsson model

关键词： Internet of things long range wireless area network ZigBee mining environments path-loss models coefficient of determination mean square error

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An efficient quantum proactive incremental learning algorithm

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 49-57页

作者： Lingxiao Li Jing Li Yanqi Song Sujuan Qin Qiaoyan Wen Fei Gao State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications school of Cyberspace Security Beijing University of Posts and Telecommunications

In scenarios where a large amount of data needs to be learned, incremental learning can make full use of old knowledge, significantly reduce the computational cost of the overall learning process, and maintain high performance. In this paper, taking the MaxCut problem as our example, we introduce the idea of incremental learning into quantum computing, and propose a Quantum Proactive Incremental Learning algorithm(QPIL). Instead of a one-off training of quantum circuit, QPIL contains a multi-phase training on gradually-increased subgraphs of all vertices, proactively reducing large-scale problems to smaller ones to solve in steps, providing an efficient solution for MaxCut. Specifically, some vertices and corresponding edges are randomly selected for training to obtain optimized parameters of the quantum circuit at first. Then, in each incremental phase, the remaining vertices and corresponding edges are gradually added and the parameters obtained from the previous phase are reused in the parameter initialization of the current phase. We perform experiments on 120 different small-scale graphs, and it shows that QPIL performs superior to prevalent quantum and classical baselines in terms of approximation ratio(AR), time cost, anti-forgetting, and solving stability. In particular, QPIL's AR surpasses 20% of mainstream quantum baselines, and the time cost is less than 1/5 of them. The idea of QPIL is expected to inspire efficient and high-quality solutions in large-scale Max Cut and other combinatorial optimization problems.

关键词： variational quantum algorithm incremental learning multi-phase training MaxCut quantum computing

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Method for Estimating the State of Health of Lithium-ion Batteries Based on Differential Thermal Voltammetry and Sparrow Search Algorithm-Elman Neural Network

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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

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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

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Modeling and Capacity Configuration Optimization of CRH5 EMU On-Board Energy Storage System

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Energy Engineering 2025年第1期122卷 307-329页

作者： Mingxing Tian Weiyuan Zhang Zhaoxu Su school of Automation and Electrical Engineering Lanzhou Jiaotong UniversityLanzhou730070China

In the context of the“dual carbon”goals,to address issues such as high energy consumption,high costs,and low power quality in the rapid development of electrified railways,this study focused on the China Railways High-Speed 5 Electric Multiple Unit and proposed a mathematical model and capacity optimization method for an onboard energy storage system using lithium batteries and supercapacitors as storage ***,considering the electrical characteristics,weight,and volume of the storage media,a mathematical model of the energy storage system was ***,to tackle problems related to energy consumption and power quality,an energy management strategy was proposed that comprehensively considers peak shaving and valley filling and power quality by controlling the charge/discharge thresholds of the storage *** optimization adopted a bilevel programming model,with the series/parallel number of storage modules as variables,considering constraints imposed by the Direct Current to Direct Current converter,train load,and *** improved Particle Swarm Optimization algorithm and linear programming solver were used to solve specific *** results show that the proposed onboard energy storage system can effectively achieve energy savings,reduce consumption,and improve power qualitywhile meeting the load and space limitations of the train.

关键词： Electrified railway regenerative braking bi-level programming on-board energy storage power quality capacity configuration

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Performance analysis of two-way relay mixed RF/FSO system with co-channel interference

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Optoelectronics Letters 2025年第2期21卷 85-89页

作者： WANG Zhuo school of Optoelectronic Engineering Changchun University of Science and Technology

In this paper,the performance of a two-way relay (TWR) mixed radio frequency/free space optical (RF/FSO) system with co-channel interference (CCI) is *** from interference-limited one-way relay (OWR) system,CCIs should be considered at both relay and users in TWR ***,opportunistic user schedule is applied to select the user with the largest signal to interference plus noise ratio (SINR).Exact and asymptotic outage probability (OP) is *** bit error rate (BER) is further presented to evaluate the overall *** results show that the performance of a TWR system is dominated by the uplink or downlink whose performance is severer.

关键词： Bit error rate

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