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Energy band engineering of graphitic carbon nitride for photocatalytic hydrogen peroxide production

Carbon Energy 2024年第11期6卷 346-370页

作者： Tengyang Gao Degui Zhao Saisai Yuan Ming Zheng Xianjuan Pu Liang Tang Zhendong Lei Key Laboratory of Organic Compound Pollution Control Engineering (MOE) School of Environmental and Chemical Engineering Shanghai UniversityShanghaiChina National & Local Joint Engineering Research Center for Mineral Salt Deep Utilization Huaiyin Institute of TechnologyHuaianChina School of Environmental and Chemical Engineering Jiangsu University of Science and TechnologyZhenjiangChina College of Environmental & Engineering Tongji UniversityShanghaiChina School of Materials Science and Engineering Nanyang Technological UniversitySin gaporeSingapore

Hydrogen peroxide(H_(2)O_(2))is one of the 100 most important chemicals in the world with high energy density and environmental *** with anthraquinone oxidation,direct synthesis of H_(2)O_(2) with hydrogen(H_(2))and oxygen(O_(2)),and electrochemical methods,photocatalysis has the characteristics of low energy consumption,easy operation and less pollution,and broad application prospects in H_(2)O_(2) *** photocatalysts,such as titanium dioxide(TiO_(2)),graphitic carbon nitride(g-C_(3)N_(4)),metal-organic materials,and nonmetallic materials,have been studied for H_(2)O_(2) *** them,g-C_(3)N_(4) materials,which are simple to synthesize and functionalize,have attracted wide *** electronic band structure of g-C_(3)N_(4) shows a bandgap of 2.77 eV,a valence band maximum of 1.44 V,and a conduction band minimum of−1.33 V,which theoretically meets the requirements for hydrogen peroxide *** comparison to semiconductor materials like TiO_(2)(3.2 eV),this material has a smaller bandgap,which results in a more efficient response to visible ***,the photocatalytic activity of g-C_(3)N_(4) and the yield of H_(2)O_(2) were severely inhibited by the electron-hole pair with high recombination rate,low utilization rate of visible light,and poor selectivity of *** previous reviews also presented various strategies to improve photocatalytic H_(2)O_(2) production,they did not systematically elaborate the inherent relationship between the control strategies and their energy band *** this point of view,this article focuses on energy band engineering and reviews the latest research progress of g-C_(3)N_(4) photocatalytic H_(2)O_(2) *** this basis,a strategy to improve the H_(2)O_(2) production by g-C_(3)N_(4) photocatalysis is proposed through morphology control,crystallinity and defect,and doping,combined with other materials and other ***,the challenges and prospect

关键词： energy band engineering graphitic carbon nitride hydrogen peroxide photocatalysis various strategies

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Unravelling the synergistic effects in GdCe composite oxides supported biochar catalysts for formaldehyde elimination: Elevated performance and SO_(2) toleration

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Journal of Environmental sciences 2025年第6期152卷 594-610页

作者： Yun Jiang Lei Gao Jianyong Dai Caiting Li Huiyu Xiong Yeling Li Zhichao Liu Wenjun Wang Junhao Hu School of Resources Environment and Safety Engineering University of South ChinaHengyang 421001China National&Local Joint Engineering Research Center for Airborne Pollutants Control and Radioactivity Protection in Buildings Hengyang 421001China College of Environmental Science and Engineering Hunan UniversityChangsha 410082China

A chain of GdCe oxides boosted biochars derived from maize straw and sewage sludge(GdyCe1-y/MPBs)were fabricated for formaldehyde(HCHO)catalytic *** ingenerate relationship between the abatement performance and corresponding structural feature was comprehensively evaluated by XPS,in situ DRIFTS,BET,XRD,SEM and H_(2)-***,10%Gd0.25Ce0.75/MPB exhibited excellent performance,favorable SO_(2) and moisture toleration over a broad temperature range from 160 to 320℃,where it achieved 96.8%removal efficiency with 90.5%selectivity at 200℃.The single or united effects of O_(2),SO_(2),H_(2)O on HCHO abatement over 10%Gd_(0.25)Ce_(0.75)/MPB were tested,and the findings demonstrated that the suppressive effects of SO_(2) and H_(2)O outweighed the promoting influence of O_(2) within a specific *** and Ce co-modified MPB revealed superior HCHO removal capability in contrast to that of Gd or Ce severally modified MPB,ascribing to the synergistic effect of GdO_(x) and CeO_(x) and benefitting from the augmentation of surface area and total pore volume,the aggrandizement of surface active oxygen species,the promotion of redox ability and the inhibition crystallization of CeO_(x).According to in situ DRIFTS,a series of intermediates including formate species and dioxymethylene(DOM)were produced,which would eventually decompose into H_(2)O and CO_(2).In addition,the mass transfer and diffusion of the reactants along with the accessibility of the catalytic sites were enlarged by the hierarchical porous structure of the support,which were also answerable for its distinguished catalytic ***,10%Gd0.25Ce0.75/MPB possessed remarkable potential for industrial applications.

关键词： Formaldehyde Catalytic oxidation Gd-Ce oxides Hierarchical porous biochar

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Multi-Objective Optimization Scheduling of Household Energy Based on Goose Algorithm

Multi-Objective Optimization Scheduling of Household Energy ...

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2024 CPSS and IEEE International Symposium on Energy Storage and Conversion, CPSS and ISESC 2024

作者： Hou, Zhenyu Gao, Feng Zhou, Kangjia Zhang, Yusen Nie, Kaizhe School of Control Science and Engineering Shandong University Jinan Shandong China School of Electrical Engineering Shandong University Jinan Shandong China

ISBN: (纸本)9798350380514

The incorporation of photovoltaic energy storage systems has introduced new avenues for enhancing household energy supply, thereby enabling a greater integration of re-newable energy sources within residential power consumption. This article proposes a multi-objective optimization scheduling model for household energy management that employs the goose algorithm. The primary objective of this model is to optimize and minimize both household electricity costs and carbon emissions while ensuring user satisfaction. The model comprises two crucial components. Firstly, an optimization scheme for the photovoltaic energy storage system that efficiently manages its charging and discharging operations to achieve a reduction in economic costs. Secondly, an optimization scheme for scheduling household appliance usage periods that strategically allocates appliance operation to meet multiple objectives. Through empirical analysis, the optimized scheduling of the photovoltaic energy storage system demonstrates a potential 6.17% reduction in economic expenditures, while the optimization of appliance usage periods showcases an 11.28% decrease in economic costs and a 0.85% reduction in carbon emissions costs. © 2024 IEEE.

关键词： Scheduling algorithms

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Early detection of rotating stallin axial flow compressors via deterministic learning:detectability analysis

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control Theory and Technology 2023年第2期21卷 161-172页

作者： Tianrui Chen Shuai Han Zejan Zhu Cong Wang School of Control Science and Engineering Shandong UniversityJinan 250061ShandongChina Center for Intelligent Medical Engineering Shandong UniversityJinan 250061ShandongChina School of Automation Science and Engineering South China University of TechnologyGuangzhou 510641GuangdongChina

Rotating stall and surge are two violent unstable phenomena of an aero-engine *** early detection of rotating stall is a critical and difficult issue in the operation of a ***,a deterministic learning based stall inception detection approach(SIDA)has been developed for modeling and detecting stall inception in aero-engine *** paper considers the derivation of analytical results on the detection capabilities for the SIDA based on deterministic ***,by utilizing the input/output stability of the residual system,a detectability condition of the SIDA is presented,and how to choose the parameters of the diagnostic system is also ***,based on the relationship between NN approximation capabilities and radial basis function(RBF)network structures,the influence of RBF network structures on the performance properties of the SIDA is ***,a simulation study is presented,in which the Mansoux-C2 compressor model is utilized to verify the effectiveness of the proposed SIDA.

关键词： Axial compressor Rotating stall Surge Fault detection Deterministic learning Detectability condition

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Dynamic and Heterogeneous Identity-Based Cooperative Co-Evolution for Distributed Lot-Streaming Flowshop Scheduling Problem

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Complex System Modeling and Simulation 2025年第1期5卷 86-106页

作者： Juan Wang Guanghui Zhang Xiaoling Li Yanxiang Feng School of Information Science and Technology Hebei Agricultural UniversityBaoding 071001China State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong UniversityXi’an 710049China School of Electronics and Control Engineering Chang’an UniversityXi’an 710064China School of Automation Science and Engineering Xi’an Jiaotong UniversityXi’an 710049China

In this research,a novel dynamic and heterogeneous identity based cooperative co-evolutionary algorithm(DHICCA)is proposed for addressing the distributed lot-streaming flowshop scheduling problem(DLSFSP)with the objective to minimize the makespan.A two-layer-vector representation is devised to bridge the solution space of DLSFSP and the search space of *** the evolution of DHICCA,population individuals are endowed with heterogeneous identities according to their quality,including superior individuals,ordinary individuals,and inferior individuals,which serve local exploitation,global exploration,and diversified restart,*** individuals with different identities require different evolutionary mechanisms to fully unleash their respective potentials,identity-specific evolutionary operators are devised to evolve them in a cooperative co-evolutionary *** is important to use limited population resources to solve complex optimization ***,exploitation is carried out on superior individuals by devising three exploitative operators with different intensities based on techniques of variable neighborhood,destruction-construction,and gene *** is executed on ordinary individuals by a newly constructed discrete Jaya algorithm and a probability crossover *** addition,restart is performed on inferior individuals to introduce new evolutionary individuals to the *** the cooperative co-evolution,all individuals with different identities are merged as a population again,and their identities are dynamically adjusted by new *** influence of parameters on the algorithm is investigated based on design-of-experiment and comprehensive computational experiments are used to evaluate the performance of all *** results validate the effectiveness of special designs and show that DHICCA performs more efficient than the existing state-of-the-art algorithms in solving the DLSFSP.

关键词： distributed flowshop scheduling lot-streaming scheduling identity division and merge heterogeneous evolution cooperative co-evolution

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Autonomous Stair-Climbing Locomotion of Quadruped Robot Using Visual Perception 14

Autonomous Stair-Climbing Locomotion of Quadruped Robot Usin...

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14th IEEE International Conference on Cyber Technology in Automation, control, and Intelligent Systems, CYBER 2024

作者： Li, Shuxin Zhang, Qin Luo, Chuang Chai, Hui School of Electrical Engineering University of Jinan Jinan250022 China School of Control Science and Engineering Shandong University Jinan250061 China

ISBN: (纸本)9798331506056

To expand the exploration range of the quadruped robot, this paper proposes a vision-based autonomous stair-climbing locomotion framework for the quadruped robot. Since the initial pose of the robot is unknown at early exploration phases, the complete point cloud data of the stair may not be collected, which often leads to inaccuracies in extracting step geometric parameters. Therefore, this paper integrates the yaw angle data from the robot's IMU for plane clustering and proposes a step sizes extraction method that establishes a local coordinate system between adjacent planes, which can calculate the accurate step width and height. The step sizes are utilized to plan the matching gait parameters, and the position servo controller is used to realize the stair-climbing of the quadruped robot. Simulation experiments conducted on a virtual prototype showed that the quadruped robot could climb six steps stably and quickly under the guidance of visual information, verifying the effectiveness of the above method. © 2024 IEEE.

关键词： Multipurpose robots

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Heterogeneous Federated Learning with controlled Gradient Variate of Client Momentum 20th

Heterogeneous Federated Learning with Controlled Gradient V...

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20th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2024

作者： Zhao, Rui Yang, Xiao Duan, Xiaowen Qiao, Lei Zhou, Rui Zhou, Qingguo The School of Information Science and Engineering Lanzhou University Lanzhou730000 China Beijing Institute of Control Engineering Beijing100190 China

ISBN: (纸本)9789819628636

Federated Learning (FL) is a novel distributed machine learning paradigm that addresses privacy concerns while training the robust model across distributed clients. The primary challenge of FL is the heterogeneity of data distribution, which slows down model convergence and degrades model performance. Especially, constrained by computational capacity and network bandwidth in edge computing applications, FL client optimization methods have become crucial for addressing the issue of the heterogeneity of data. Nevertheless, existing approaches overlook the impact of local training overfitting, which degrades the global model performance. Additionally, they fail to fully take advantage of the existing local model on clients. In this work, we propose a novel and lightweight client optimization method. Specifically, we utilize the gradient variate with the client historical offset computed by the local model and updated global model to guide the local objective function. Moreover, we provide a strategy that randomly adds gradient perturbations during training to prevent the local objective function from converging to local optima. Extensive experiments demonstrate that, under various heterogeneity scenarios, our proposal exhibits strong competitiveness compared to current state-of-the-art client optimization algorithms, with notable improvements in both performance and robustness. © IFIP International Federation for Information Processing 2025.

关键词： Federated learning

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Interbasin groundwater flows in the Yarlung Zangbo River Basin and its surrounding areas:A perspective

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science China(Technological sciences) 2025年第4期68卷 299-301页

作者： Jianxin CHEN Xingxing KUANG Linfeng FAN Chunmiao ZHENG Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control School of Environmental Science and EngineeringSouthern University of Science and TechnologyShenzhen518000China State Key Laboratory of Mountain Hazards and Engineering Resilience Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu610000China

Interbasin groundwater flows(IGFs)are movements of groundwater across topographic basin boundaries,which can either contribute to or deplete the water resources of a basin[1].Basins that net-export groundwater beyond their topographic boundaries are termed groundwater exporters,whereas those that receive groundwater from beyond their topographic confines are known as groundwater *** studies have highlighted that the Yarlung Zangbo River Basin(YZRB)is under the impact of IGFs[2,3].

关键词： interbasin groundwater flows interbasin groundwater flows igfs groundwater importers water resources movements groundwater groundwater exporters Yarlung Zangbo River Basin

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Spectral Calibration for In-situ Measurement of Glycerol Fermentation Component Concentrations via Infrared Spectroscopy

Spectral Calibration for In-situ Measurement of Glycerol Fer...

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2024 China Automation Congress, CAC 2024

作者： Li, Yahui Yang, Peilin Sun, Yaqin Zhang, Qin Liu, Tao Yan, Yu Dalian University of Technology School of Control Science and Engineering Dalian China Dalian University of Technology School of Biological Engineering Dalian China

ISBN: (纸本)9798350368604

For in-situ measurement of important component concentrations during a glycerol fermentation process via the near-infrared spectroscopy (NIR), this paper proposes a semi-supervised spectral calibration model building method based on the goose optimization algorithm (GO) for spectral data analysis to enhance in-situ measurement accuracy. To address the issue of very limited labeled samples as often encountered in practice, a semi-supervised approach based on combining the consistency regularization and pseudo-labelling strategy is presented, along with screening out reliable unlabeled spectra based on a wilcoxon signed-rank test for calibration model building. In addition, a comparative study on measuring the multiple component concentrations during a glycerol fermentation process is conducted in terms of using different modelling methods. Experimental results well demonstrate the measurement accuracy of the proposed spectral calibration method. © 2024 IEEE.

关键词： Near infrared spectroscopy

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Enhancing surrogate-assisted evolutionary optimization for medium-scale expensive problems: a two-stage approach with unsupervised feature learning and Q-learning

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Neural Computing and Applications 2024年第25期36卷 15545-15565页

作者： Gong, Yiyun Yu, Haibo Kang, Li Sun, Chaoli Zeng, Jianchao School of Electrical and Control Engineering North University of China Taiyuan030051 China School of Computer Science and Technology North University of China Taiyuan030051 China School of Environment and Safety Engineering North University of China Taiyuan030051 China School of Computer Science and Technology Taiyuan University of Science and Technology Taiyuan030024 China

This paper presents a novel two-stage progressive search approach with unsupervised feature learning and Q-learning (TSLL) to enhance surrogate-assisted evolutionary optimization for medium-scale expensive problems. The method attempts to address the challenges posed by multi-polar and multi-variable coupling properties in such problems. During the iteration, TSLL splits the optimization process into two distinct stages. First, two unsupervised feature learning techniques: principal component analysis (PCA) and Autoencoder, are utilized to improve the representation of potential optimal samples in the solution space. PCA is used for feature reduction, extracting the most important features. On the other hand, Autoencoder focuses on reconstructing features within the medium-scale solution space. To ensure comprehensive exploration of the entire solution space, TSLL employs two distinct surrogate modeling approaches along with Q-learning in the second stage to dynamically select the mutation strategy for the differential evolution operator. Numerous experiments demonstrate the superiority of TSLL over five state-of-the-art surrogate-assisted approaches and two sophisticated evolutionary algorithms including the winner of CEC 2017 on medium-scale benchmark problems and a wind farm layout problem. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Reinforcement learning

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