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Remaining Life Prediction Method for Photovoltaic Modules Based on Two-Stage Wiener Process

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Energy Engineering 2025年第1期122卷 331-347页

作者： Jie Lin Hongchi Shen Tingting Pei Yan Wu school of Electrical Engineering and information Engineering Lanzhou University of TechnologyLanzhou730050China

Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation *** service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental *** cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.

关键词： Photovoltaic modules degradation stochastic processes lifetime prediction

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

Synergistically enhanced ORR and HER performance on Co-N-C coupled in-situ generated PtCo intermetallic

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Journal of Energy Chemistry 2025年第1期100卷 721-729页

作者： Guanyu Luo Min Song Lulu An Xiao Huang Qian Zhang Chenhao Zhang Tao Shen Shuang Wang Deli Wang Key Laboratory of Material Chemistry for Energy Conversion and Storage (Huazhong University of Science and technology) Ministry of education School of Chemistry and Chemical Engineering Huazhong University of Science and Technology

Integrating multi-scale sites in a composite catalyst is vital to realize efficient ***,a synergistic composite catalyst consisting of Co atomic sites and in-situ generated PtCo intermetallic compounds （IMCs）(o-PtCo@CoNC) is proposed through Co pre-anchoring and subsequent impregnation-reduction *** loading of Co atoms provides a chance for in-situ generating PtCo ordered intermetallic *** remaining Co single atoms and PtCo IMCs construct synergistic electrocatalytic *** from the ordered structure,synergistic effect of Pt Co IMCs and Co single atoms,o-PtCo@CoNC exhibits excellent electrocatalytic performance for oxygen reduction reaction （ORR） and hydrogen evolution reaction （HER） with mass activity of 1.21 A mgPt-1（at 0.9 V） and5.70 A mgPt-1（at an overpotential of 100 mV）,***,o-PtCo@CoNC delivers negligible loss of half-wave potential and overpotential during long-term stability test in acid solutions,with 13 mV decay after 50,000 potential cycles for ORR and a 2.7 mV decay after 20,000 potential cycles for *** integration strategy of single-atomic sites coupled IMCs paves the way for enhancing the activity and durability of Pt-based electrocatalysts.

关键词： Synergistic effect Intermetallics Single atomic sites Oxygen reduction reaction Hydrogen evolution reaction

AI-Enhanced Secure Data Aggregation for Smart Grids with Privacy Preservation

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Computers, Materials & Continua 2025年第1期82卷 799-816页

作者： Congcong Wang Chen Wang Wenying Zheng Wei Gu school of Software Nanjing University of Information Science and TechnologyNanjing210044China school of information Science and Engineering Zhejiang Sci-Tech UniversityHangzhou310018China State Key Laboratory of Public Big Data Guizhou UniversityGuiyang550025China school of Computer Science and technology(school of Artificial Intelligence) Zhejiang Sci-Tech UniversityHangzhou310018China school of Computer Science(school of Cyber Science and Engineering) Nanjing University of Information Science and TechnologyNanjing210044China

As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy *** research emphasizes data security and user privacy concerns within smart ***,existing methods struggle with efficiency and security when processing large-scale *** efficient data processing with stringent privacy protection during data aggregation in smart grids remains an urgent *** paper proposes an AI-based multi-type data aggregation method designed to enhance aggregation efficiency and security by standardizing and normalizing various data *** approach optimizes data preprocessing,integrates Long Short-Term Memory(LSTM)networks for handling time-series data,and employs homomorphic encryption to safeguard user *** also explores the application of Boneh Lynn Shacham(BLS)signatures for user *** proposed scheme’s efficiency,security,and privacy protection capabilities are validated through rigorous security proofs and experimental analysis.

关键词： Smart grid data security privacy protection artificial intelligence data aggregation

A Generative Model-Based Network Framework for Ecological Data Reconstruction

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Computers, Materials & Continua 2025年第1期82卷 929-948页

作者： Shuqiao Liu Zhao Zhang Hongyan Zhou Xuebo Chen school of Electronic and information Engineering University of Science and Technology LiaoningAnshan114051China school of Computer Science and Software Engineering University of Science and Technology LiaoningAnshan114051China

This study examines the effectiveness of artificial intelligence techniques in generating high-quality environmental data for species introductory site selection *** Strengths,Weaknesses,Opportunities,Threats(SWOT)analysis data with Variation Autoencoder(VAE)and Generative AdversarialNetwork(GAN)the network framework model(SAE-GAN),is proposed for environmental data *** model combines two popular generative models,GAN and VAE,to generate features conditional on categorical data embedding after SWOT *** model is capable of generating features that resemble real feature distributions and adding sample factors to more accurately track individual sample *** data is used to retain more semantic information to generate *** model was applied to species in Southern California,USA,citing SWOT analysis data to train the *** show that the model is capable of integrating data from more comprehensive analyses than traditional methods and generating high-quality reconstructed data from them,effectively solving the problem of insufficient data collection in development *** model is further validated by the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)classification assessment commonly used in the environmental data *** study provides a reliable and rich source of training data for species introduction site selection systems and makes a significant contribution to ecological and sustainable development.

关键词： Convolutional Neural Network(CNN) VAE GAN TOPSIS data reconstruction

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)

Unraveling post-growth mechanisms of monolayer CsPbBr3 nanocubes:Laser-enhanced transformations and cathodoluminescence-electron microscopy correlations

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Journal of Energy Chemistry 2025年第1期100卷 146-156页

作者： Mingxing Li Xiaoge Wang Xiaofan Cao Zhiqun He Chunjun Liang Mingxing Chen Jing Ju Fangtian You Key Laboratory of Luminescence and Optical information Ministry of Education Institute of Optoelectronic Technology Beijing Jiaotong University Beijing National Laboratory for Molecular Sciences (BNLMS) College of Chemistry and Molecular Engineering Peking University

Lead-halide perovskite nanoparticles（LHP NPs） are highly promising materials for next-generation displays and solid-state lighting due to their exceptional optical properties. However, their inherent instability presents a significant challenge. Recent advances have demonstrated that optoelectronic devices based on monolayer nanoparticle films exhibit both high luminescence efficiency and long-term *** research demonstrates that mobility limitations and anisotropic alignments in CsPbBr3nanocube monolayer films are key to their stabilization, hindering spontaneous growth through face-to-face fusion and resulting in the formation of connecting necks in a diagonal direction. Introducing laser irradiation confirmed this by significantly accelerating nanocubes growth, increasing mobility, and enhancing local structural ordering, leading to larger and more regularly shaped nanosheets. Fourier transform infrared spectroscopy and energy dispersive spectroscopy line-scan analyses indicated that laser irradiation did not disrupt the ligand structure. Transmission electron microscopy and correlative cathodoluminescence electron microscopy revealed the effects of post-growth and heterogeneous structures, including enhanced luminescence and inhomogeneous intensity in the nanosheets. These findings deepen the understanding of the post-growth mechanism of monolayer nanoparticles and the structure-emission correlation and highlight the unique role of laser irradiation in directing the formation of well-defined and regular nanostructures.

关键词： Energy dispersive spectroscopy

Practical approach for detecting k-nonseparability of multipartite quantum states

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 32-48页

作者： Jie Guo Jinchuan Hou Xiaofei Qi Kan He College of Mathematics Taiyuan University of Technology school of Mathematics and Statistics Shanxi University Key Laboratory of Complex Systems and Data Science of Ministry of education Shanxi University

The instantaneous detection of entanglement in quantum states poses a significant challenge in the fields of quantum computation and quantum information, and there are no practical methods or tools to complete this task satisfactorily so far. We propose a sufficient and necessary criterion of k-nonseparability for any n-partite finite or infinite dimensional systems, 2 ≤ k ≤ n. This criterion serves as the foundation for a practical scheme designed to detect entanglement and k-nonseparability across multipartite finite-dimensional systems. To exemplify the application of our scheme, we have developed a software tool that facilitates swift and precise identification of entanglement, k-nonseparability, and genuine entanglement within n-qubit systems, specifically tailored for systems with 2 ≤ n ≤ 4.

关键词： multipartite systems entanglement states entanglement witnesses ${\bm~k}$-nonseparability

Grid-Connected/Islanded Switching Control Strategy for Photovoltaic Storage Hybrid Inverters Based on Modified Chimpanzee Optimization Algorithm

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Energy Engineering 2025年第1期122卷 265-284页

作者： Chao Zhou NarisuWang Fuyin Ni Wenchao Zhang school of Electrical and information Engineering Jiangsu University of TechnologyChangzhou213001China Jiangsu Key Laboratory of Power Transmission&Distribution Equipment technology Jiangsu University of TechnologyChangzhou213001China

Uneven power distribution,transient voltage,and frequency deviations are observed in the photovoltaic storage hybrid inverter during the switching between grid-connected and island *** response to these issues,this paper proposes a grid-connected/island switching control strategy for photovoltaic storage hybrid inverters based on the modified chimpanzee optimization *** proposed strategy incorporates coupling compensation and power differentiation elements based on the traditional droop ***,it combines the angular frequency and voltage amplitude adjustments provided by the phase-locked loop-free pre-synchronization control *** pre-synchronization is achieved by regulating the virtual current to zero and aligning the photovoltaic storage hybrid inverter with the grid ***,two novel operators,learning and emotional behaviors are introduced to enhance the optimization precision of the chimpanzee *** operators ensure high-precision and high-reliability optimization of the droop control parameters for photovoltaic storage hybrid inverters.A Simulink model was constructed for simulation analysis,which validated the optimized control strategy’s ability to evenly distribute power under load *** strategy effectively mitigated transient voltage and current surges during mode ***,seamless and efficient switching between gridconnected and island modes was achieved for the photovoltaic storage hybrid *** enhanced energy utilization efficiency,in turn,offers robust technical support for grid stability.

关键词： Photovoltaic storage hybrid inverters modified chimpanzee optimization algorithm droop control seamless switching