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Surface functionalization of phosphorene via P–H bond for ambient protection and robust photocatalytic H_(2) evolution

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Science China Materials 2022年第5期65卷 1245-1251页

作者： Rui Shi Lei Kang Xiaojuan Bai Yong Chen Key Laboratory of Photochemical Conversion and Optoelectronic Materials&CAS-HKU Joint Laboratory on New Materials Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing 100190China Key Laboratory of Functional Crystals and Laser Technology Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing 100190China Key Laboratory of Urban Stormwater system and Water Environment Beijing Engineering Research Center of Sustainable Urban Sewage System Construction and Risk ControlBeijing University of Civil Engineering and ArchitectureBeijing 100044China University of Chinese Academy of Sciences Beijing 100190China

The facile oxidation of few-layer black phosphorus(i.e., phosphorene) in the atmospheric environment is a major hurdle for its applications in photocatalytic solarenergy conversion. The introduction of protective layers, such as a surface capping layer, surface coordination, and P–C covalent functionalization, can protect phosphorene from oxidative degradation but inevitably decreases its photocatalytic performance due to the blockage of catalytic active sites. Herein, we develop a hydrogenation approach via the introduction of P–H covalent bonds on the surface of phosphorene(i.e., phosphorene-H) to inhibit the oxidation of phosphorene-H without sacrificing the original photocatalytic H_(2) evolution performance. Experiments and density functional theory calculations demonstrate that about 5 mol% of phosphorus atoms in phosphorene-H are involved in forming P–H covalent bonds, hindering the reaction between O_(2) and phosphorene-H in terms of thermodynamics and *** hydrogenation strategy is envisaged to augment the prospect of phosphorene in the field of photocatalysis.

关键词： phosphorene antioxidation hydrogenation photocatalytic H_(2)evolution

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Kernel-Based Regularized Continuous-Time system Identification from Sampled Data

arXiv

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arXiv 2024年

作者： Fang, Xiaozhu Mu, Biqiang Chen, Tianshi School of Data Science Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen518172 China The Key Laboratory of Systems and Control of CAS Institute of Systems Science Academy of Mathematics and System Science Chinese Academy of Sciences Beijing100190 China

The identification of continuous-time (CT) systems from discrete-time (DT) input and output signals, i.e., the sampled data, has received considerable attention for half a century. The state-of-the-art methods are parametric methods and thus subject to the typical issues of parametric methods. In the last decade, a major advance in system identification is the so-called kernel-based regularization method (KRM), which is free of the issues of parametric methods. It is interesting to test the potential of KRM on CT system identification. However, very few results have been reported, mainly because the estimators of KRM have no closed forms for general CT input signals, except for some very special cases. In this paper, we show for KRM that the estimators have closed forms when the DT input signal has the typical intersample behavior, i.e., zero-order hold or band-limited, and this paves the way for the application of KRM for CT system identification. Numerical simulations show that the proposed method is more robust than the state-of-the-art methods and more accurate when the sample size is small. © 2024, CC BY.

关键词： Continuous time systems

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ESNet: evolution and succession network for high-resolution salient object detection 24

ESNet: evolution and succession network for high-resolution ...

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Proceedings of the 41st International Conference on Machine Learning

作者： Hongyu Liu Runmin Cong Hua Li Qianqian Xu Qingming Huang Wei Zhang Institute of Information Science Beijing Jiaotong University & Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing China School of Control Science and Engineering Shandong University & Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China School of Computer Science and Technology Hainan University Hainan China Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China

Preserving details and avoiding high computational costs are the two main challenges for the High-Resolution Salient Object Detection (HRSOD) task. In this paper, we propose a two-stage HRSOD model from the perspective of evolution and succession, including an evolution stage with Low-resolution Location Model (LrLM) and a succession stage with High-resolution Refinement Model (HrRM). The evolution stage achieves detail-preserving salient objects localization on the low-resolution image through the evolution mechanisms on supervision and feature; the succession stage utilizes the shallow high-resolution features to complement and enhance the features inherited from the first stage in a lightweight manner and generate the final high-resolution saliency prediction. Besides, a new metric named Boundary-Detail-aware Mean Absolute Error (MAEBD) is designed to evaluate the ability to detect details in high-resolution scenes. Extensive experiments on five datasets demonstrate that our network achieves superior performance at real-time speed (49 FPS) compared to state-of-the-art methods. Our code is publicly available at: https://***/rmcong/ESNet_ICML24.

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A Fast Conversion Method of Tube Coordinates

A Fast Conversion Method of Tube Coordinates

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作者： Hao Zhao Renbo Xia Yueling Chen Liming Tao Daixian Zhao Tianyu Zhang Key Laboratory of Networked Control System Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institute of Robotics and Intelligent Manufacturing Innovation Chinese Academy of Sciences University of Chinese Academy of Sciences

Inspired by the idea of the coordinate transformation of the robot arm, the tube structure is analogized to the robot arm structure, and the conversion method of the tube bend processing parameters LRA to the three-dimensional coordinate points is obtained. The method first regards the tube as a "mechanical arm";then, using the similarity of the LRA processing parameters and DH parameters, all the LRA parameters are converted into D-H parameters;finally, the D-H parameter method is applied to calculate the distance between each axis of the " mechanical arm ". If the first space coordinate point is defined as the origin of the base coordinate system (0, 0, 0), then the position of the origin of other coordinate systems in the base coordinate system can be obtained;It has been proved by experiments that this method fast and feasible.

关键词： Tube Coordinates Fast Conversion Method Mechanical Arm D-H Parameter Method

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Research on NLOS environmental ranging method based on gradient boosting tree

Research on NLOS environmental ranging method based on gradi...

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2024 8th International Conference on Electrical, Mechanical and Computer Engineering (ICEMCE)

作者： Wenyu Li Shun Cao Xianda Liu Minghao Wang Shuan Sheng School of Information Engineering Shenyang University of Chemical Technology Shenyang Liaoning China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang Liaoning China Key Laboratory of Networked Control System Chinese Academy of Sciences Shenyang Liaoning China Shenyang National Research Institute of Intelligent Robots Co. Ltd. Liaoning China

ISBN: (数字)9798331506230

ISBN: (纸本)9798331506247

Indoor distance measurement plays a critical role in positioning services. The complexity of indoor environments, coupled with a limited and small sample size, results in suboptimal distance accuracy. This paper proposes a method for non-line-of-sight distance measurement based on a gradient boosting tree model, effectively addressing the issue of sample size dependency. The random hyperparameter settings of the gradient boosting tree model lead to prolonged fitting times. Additionally, the model utilizes a fixed learning rate, which limits the analysis of features in small samples. To tackle these concerns, we develop a grid optimization algorithm that identifies the best hyperparameter combinations through a hyperparameter grid search. We also implement a weighted value approach and a cosine annealing algorithm to precisely update the learning rate according to training conditions, thus maximizing the learning of small sample features. Our proposed model significantly enhances distance accuracy in non-line-of-sight environments under constraints of training sample size and variety. Comparative experiments demonstrate that our model improves distance accuracy by 63% relative to other machine learning models, with a mean square error of only 0.168m.

关键词： Training Analytical models Accuracy Stability criteria Fitting Power system stability Boosting Distance measurement Data models Optimization

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A Family of Hyper-parameter Estimators for Regularized Linear system Identification

A Family of Hyper-parameter Estimators for Regularized Linea...

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IEEE Conference on Decision and control

作者： Meng Zhang Tianshi Chen Biqiang Mu Key Laboratory of Systems and Control of CAS Institute of Systems Science Academy of Mathematics and System Science Chinese Academy of Sciences Beijing China School of Data Science and Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen China

Hyper-parameter estimation is one of the fundamental issues for kernel-based regularized system identification methods. Empirical Bayes (EB) estimator and Stein's unbiased risk estimator (SURE) are two popular hyper-parameter estimators, but they both have advantages and disadvantages. Specifically, EB is not asymptotically optimal in the mean squared error (MSE) sense but SURE is, while SURE is more sensitive to ill-conditioned regression matrix but EB is more robust. In this paper, to find a better estimator by combining their strength and mitigating their weakness, we propose a family of hyper-parameter estimators by linking EB and SURE estimators together through an index. The finite sample and asymptotic properties of this family of estimators have been established. The Monte Carlo simulation results show that there does exist a ‘middle’ hyper-parameter estimator in this family that is superior to the EB and SURE.

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A Novel Hybrid Method for Fault Diagnosis of Industrial Equipment Based on Vibration Signals

A Novel Hybrid Method for Fault Diagnosis of Industrial Equi...

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Prognostics and system Health Management Conference (PHM-Qingdao)

作者： Sen Tao Kai Wang Peng Zeng Tianda Yu Hao Wu Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Shenyang China Nuclear Power Institute of China Chengdu China State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing China

Industrial equipment reliability is a critical issue that smart manufacturing systems must address. Implementation of online fault diagnosis for industrial equipment is a promising technology that can improve equipment reliability. Vibration analysis is a popular technique for equipment condition monitoring. For the non-linear and non-stationary features of industrial vibration signals, a hybrid model based on wavelet transform (WT), support vector machine (SVM), and grey wolf optimization algorithm (GWO) is proposed. The time-frequency domain features of fault signals are extracted by wavelet transform to solve the non-linearity of signals, and the obtained feature vectors are input into SVM for classification. Aiming at the problem of setting penalty coefficient and kernel function parameters, GWO is introduced to seek hyperparameters by using the hunting principle of wolves. In the experimental part, firstly, the comparison of the GWO-WT-SVM, GWO-SVM and SVM models was carried out. Secondly, Comparison with classical classification algorithms is made. Apparently, the GWO-WT-SVM model achieves higher accuracy than other models in bearing fault diagnosis.

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Optimizing Photocatalytic Performance in an Electrostatic-Photocatalytic Air Purification system Through Integration of Triboelectric Nanogenerator and Tesla Valve

SSRN

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SSRN 2024年

作者： Li, Xiaoliang Cao, Leo N.Y. Zhang, Ting Fang, Rongkun Ren, Yuqing Chen, Xiangyu Bian, Zhenfeng Li, Hexing MOE Key Laboratory of Resource Chemistry Shanghai Key Laboratory of Rare Earth Functional Materials Shanghai Normal University Shanghai China CAS Center for Excellence in Nanoscience Beijing Key Laboratory of Micro-nano Energy and Sensor Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences Beijing100083 China School of Nanoscience and Technology University of Chinese Academy of Sciences Beijing100049 China Sino-Dutch R&D Centre for Future Wastewater Treatment Technologies Key Laboratory of Urban Stormwater System and Water Environment Beijing University of Civil Engineering and Architecture Beijing100044 China State Key Laboratory of Pollution Control and Resource Reuse College of Environmental Science and Engineering Tongji University Shanghai200092 China Shanghai University of Electric Power Shanghai China

Increasing the collision frequency between gas molecules and photocatalysts can enhance the removal efficiency of volatile organic compounds (VOCs) and particulate matter (PM) in air. In this study, we propose an Electrostatic-Photocatalytic air purification system, containing Tesla valve, triboelectric nanogenerator (TENG), and photocatalysis parts. The incorporation of Ag@ZnO nanorod array (Ag@ZnO-NR) photocatalysts into the internal baffles of the Tesla valve pipeline effectively enhances the collision probability between air pollutant molecules and photocatalysts, and thus facilitating the removal efficiency of pollutants. Additionally, the high-voltage electricity (~9.0 kV) generated by the TENG facilitates the separation of electron-hole pairs in the photocatalyst, leading to increased production of superoxide radicals (O·-2), hydroxyl radicals (·OH), and holes (h+), thereby enhancing the photocatalytic efficiency. In a 1.8 L space system, we achieved an approximately 97% removal efficiency for toluene within 130 minutes and a similar efficiency for formaldehyde (~200 ppm) within 175 minutes. Additionally, the PM2.5 concentration rapidly decreased from 999 μg·m-3 to 42 μg·m-3 within 6 minutes, alongside with a significantly faster pollutant removal rate compared to conventional methods. By integrating Tesla valves, TENG, and photocatalysis, this combined system presents an efficient and promising approach for addressing indoor air pollution, with potential applications across various settings. © 2024, The Authors. All rights reserved.

关键词： Photocatalysis

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An Improved Chimp Optimization Algorithm for Short-term Hydrothermal Scheduling

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2022年第3期49卷 666页

作者： Chen, Gonggui Wang, Shumin He, Yongsheng Shang, Wanfeng Long, Hongyu Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Chongqing University of Posts and Telecommunications Chongqing400065 China State Grid Chongqing Electric Power Company Chongqing400015 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen Shenzhen518055 China Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China

The short-term hydrothermal scheduling (STHS) is a complex non-linear, non-convex and high-dimensional mathematical optimization problem. Due to the fact that the original chimp optimization algorithm (ChOA) is likely to fall into local optimum and has the disadvantage of low population diversity, an improved chimp optimization algorithm (IChOA) is proposed to solve the STHS problem. Firstly, Logistic-Tent chaotic mapping is employed to initialize the population and increase the population diversity. Then a new nonlinear convergence factor is introduced to make the optimization search process more applicable to STHS problems. Next, particle swarm algorithm (PSO) and gravitational search algorithm (GSA) are combined to enhance the shortcoming and balance the global search ability and local exploration ability of ChOA. Moreover, Cauchy mutation and opposition-based learning strategy are supplemented as perturbation interference when the optimal position is not updated to improve the ability to leap out of the local optimum. Finally, a graded optimization strategy is adopted for the constraint handing of dynamic reservoir balance and thermal power balance. Three standard hydrothermal power systems are utilized to verify the practicability and validity of the proposed method. Results of simulations reveal that IChOA has significant competitive advantages in addressing the STHS problem. © 2022, IAENG International Journal of Computer Science. All Rights Reserved.

关键词： Particle swarm optimization (PSO)

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A method of laser focusing control in microlaser-induced breakdown spectroscopy

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Plasma Science and Technology 2019年第3期21卷 31-39页

作者： Wei WANG Lanxiang SUN Peng ZHANG Liming ZHENG Lifeng QI Wei DONG Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences University of Chinese Academy of Sciences Key Laboratory of Networked Control System Chinese Academy of Sciences

This paper presents a method for the automatic adjustment of the laser defocusing amount in micro-laser-induced breakdown spectroscopy. A microscopic optical imaging system consisting of a CCD camera and a 20× objective lens was adopted to realize the method. The real-time auto-focusing of the system was achieved by detecting the effective pixels of the light spot generated by the laser pointer. The focusing accuracy of the method could achieve 3 μm. The element concentrations of Mn and Ni in low-alloy steels were analyzed at a crater diameter of about 35 μm using the presented method. After using the presented method, the determination coefficients of Mn and Ni both exceeded 0.997, with the root-mean-square errors being 0.0133 and 0.0395, respectively. Scanning analysis was performed on the inclined plane and the curved surface by means of focusing control and non-focusing control. Ten characteristic spectral lines of Fe were selected as the analysis lines. With the focusing control, the average relative standard deviations obtained on the inclined plane and curved surface were both less than 5%, and much less than the values without focusing control, 14.6% and 40.39%.

关键词： LIBS microanalysis ablation crater focusing control

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