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Rapid, Selective Surface Oxygenation of Activated Carbon Via Microwave Air Oxidation Toward Advanced Organic Pollutant Adsorption and Energy Storage

SSRN

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SSRN 2022年

作者： Zhou, Haiqin Liang, Chenghu Lai, Penghui Kong, Lingzhao Yang, Bo Zhu, Wenkun Dai, Lichun Key Laboratory of Development and Application of Rural Renewable Energy Ministry of Agriculture and Rural Affairs Biogas Institute of Ministry of Agriculture and Rural Affairs Chengdu610041 China State Key Laboratory of Environment-friendly Energy Materials National Co-innovation Center for Nuclear Waste Disposal and Environmental Safety Nuclear Waste and Environmental Safety Key Laboratory of Defense School of National Defense Science & Technology Southwest University of Science and Technology Mianyang621010 China CAS Key Laboratory of Low-Carbon Conversion Science and Engineering Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai 201210 China Zhai Mingguo Academician Work Station Sanya University Sanya572022 China

Oxidation is a common-used strategy to enhance the surface functionality of activated carbon. Disappointingly, previous oxidation routes always enrich high-polarity poor-capacitance O-C=O groups (i.e., carboxyl/lactone) on the carbon material surface, which is a double-edged sword for its application in organic pollutant adsorption and electrochemical energy storage. Herein, microwave air oxidation (MWAO) was proposed as a facile, rapid strategy to selectively oxygenate the surface of activated carbon (AC). Characterization results suggested that the surface of the pristine AC was substantially oxygenated in a rapid microwave radiation process (e.g., 800 W for 15 S), and the pore structure was also preserved after MWAO. More importantly, unlike other oxidation routes, MWAO was not favorable for the formation high-polarity poor-pseudocapacitance O-C=O groups, resulting in higher bulk pH, zeta potential and thermal stability after MWAO of AC. Batch adsorption results indicated that MWAO remarkably increased the adsorption of various organic pollutants (dyes and antibiotics) by AC. Electrochemical analysis suggested that the specific capacitance for the AC was increased by 250% (from 60 to 208 F/g at 1A/g after MWAO at 800 W for 15 s), attributed to the reduced electrical resistance and the enhanced ion transport after MWAO. The results of this study might pave a new way for the engineering of surface functionality of AC for advanced application in organic pollutant adsorption and electrochemical energy storage. © 2022, The Authors. All rights reserved.

关键词： Adsorption

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Radioisotope Identification with Scintillation Detector Based on Artificial Neural Networks using Simulated Training Data

Radioisotope Identification with Scintillation Detector Base...

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2020 IEEE Nuclear science Symposium and Medical Imaging Conference, NSS/MIC 2020

作者： Fan, Peng Feng, Siliang Zhu, Chenglin Zhao, Chunqing Ding, Yigang Shen, Zicai Liu, Yaqiang Ma, Tianyu Xia, Yan National key Laboratory of Science and Technology on Reliability and Environmental Engineering Beijing100094 China Beijing Institute of Spacecraft Environment Engineering Beijing100094 China Department of Engineering Physics Tsinghua University Beijing100084 China

ISBN: (纸本)9781728176932

Artificial neural networks (ANN) based on learning the features of the entire measured gamma energy spectrum has been used for radioisotope identification and proved promising especially for gamma-ray spectroscopy with low energy resolution. The implementation of ANN method, however, requires tedious experimental measurement process in generation of training data for various radioisotopes. In this work, we propose an ANN-based radioisotope identification method with simulated training data. Gamma energy spectra of 27 different radioisotopes were generated with Monte Carlo simulation. A detector energy response model was proposed to match the energy spectra generated from simulation and measured from experiment, thus "pseudo" measured energy spectra of various radioisotopes transformed from simulation can be used for ANN training, which eliminates the tedious experimental measurement process for training data generation. To reduce the complexity of the training process, the principal component analysis (PCA) method was used for dimension reduction of the input energy spectra in ANN and the channel number of the energy spectra was reduced from 2000 to 50. The trained ANN was further used to identify experimentally measured gamma energy spectra of various radioisotopes including 60Co, 137Cs, 18F, 131I, 226Ra and 232Th at 103, 104 and 105 count levels. In single isotope identification test, with increased count level, higher correct identification rate is achieved and at 105 count level, all the isotopes are correctly identified for all the samples. In mixed isotope identification test, at 105 count level, all the radioisotope combinations can be identified with a correct identification rate larger than 98%, which demonstrates the feasibility and accuracy of the ANN method. To conclude, the proposed ANN method with simulated training data features good radioisotope identification capability with greatly simplified training data generation process and is feasible for gam

关键词： Neural networks

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Pyrolyzed Iron–Nitrogen–Carbon Hybrids Enable Efficient Periodate Activation Toward Contaminant Decomposition: Active Site, Degradation Mechanism, and Influential Factors

SSRN

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SSRN 2022年

作者： Long, Yangke Huang, Shixin Zhao, Shiyin Xiao, Guicong Sun, Jianlin Peng, Dan Department of Transportation and Environment Shenzhen Institute of Information Technology Shenzhen518172 China Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control School of Environmental Science and Engineering Southern University of Science and Technology Shenzhen518055 China College of Science National University of Defense Technology Changsha410073 China Guangzhou University China

To incorporate periodate-based advanced oxidation technologies (PI-AOTs) into practical wastewater treatment, there is a need for efficient and affordable activators. Pyrolyzed Fe–N/C materials are candidates for this purpose, but their actual active sites and associated activation mechanisms remain unclear. Herein, a series of Fe–N/C samples (denoted as Fe@NC-X) with differing structures and iron components was delicately synthesized. Experimental studies of the structure–activity relationship and density functional theory (DFT) computations revealed that Fe–Nx species dominated as the active site responsible for periodate activation, while the inactive iron-based particles (i.e., Fe0 and Fe3C) optimized the binding affinity of their surrounding carbon layers toward periodate to confer enhanced activity. In-depth exploration of the oxidative mechanism revealed that Fe@NC-X activated periodate through an electron transfer regime. We also showed that the optimal Fe@NC-0.2/periodate system exhibited superior activity for 4-CP oxidation with a high apparent rate constant of 0.38 min−1, which exceeded that of many reported activators. Moreover, Fe@NC-0.2/periodate is effective for eliminating miscellaneous organic pollutants and is strongly resistant to environmental interference. These findings provide an indispensable foundation for the rational development of advanced Fe–N/C activators and offer vital insights into the underlying mechanism underlying pollutant destruction through PI-AOTs. © 2022, The Authors. All rights reserved.

关键词： Wastewater treatment

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XiHe: A Data-Driven Model for Global Ocean Eddy-Resolving Forecasting

arXiv

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arXiv 2024年

作者： Wang, Xiang Wang, Renzhi Hu, Ningzi Wang, Pinqiang Huo, Peng Wang, Guihua Wang, Huizan Wang, Senzhang Zhu, Junxing Xu, Jianbo Yin, Jun Bao, Senliang Luo, Ciqiang Zu, Ziqing Han, Yi Zhang, Weimin Ren, Kaijun Deng, Kefeng Song, Junqiang College of Meteorology and Oceanography National University of Defense Technology Changsha410073 China Department of Atmospheric and Oceanic Sciences Fudan University Shanghai200438 China School of Computer Science and Engineering Central South University Changsha410083 China Qingdao266580 China College of Artificial Intelligence Tianjin University of Science and Technology Tianjin300457 China Key Laboratory of Marine Hazards Forecasting National Marine Environmental Forecasting Center Ministry of Natural Resources Beijing100081 China

Global ocean forecasting is fundamentally important to support marine activities. The leading operational Global Ocean Forecasting Systems (GOFSs) use physics-driven numerical forecasting models that solve the partial differential equations with expensive computation. Recently, specifically in atmosphere weather forecasting, data-driven models have demonstrated significant potential for speeding up environmental forecasting by orders of magnitude, but there is still no data-driven GOFS that matches the forecasting accuracy of the numerical GOFSs. In this paper, we propose the first data-driven 1/12◦ resolution global ocean eddy-resolving forecasting model named XiHe, which is established from the 25-year France Mercator Ocean International’s daily GLORYS12 reanalysis data. XiHe is a hierarchical transformer-based framework coupled with two special setups. One is the land-ocean mask mechanism for focusing exclusively on the global ocean circulation. The other is the ocean-specific block for effectively capturing both local ocean information and global teleconnection. Extensive experiments are conducted under satellite observations, in situ observations, and the IV-TT Class 4 evaluation framework of the world’s leading operational GOFSs from January 2019 to December 2020. The results demonstrate that XiHe achieves stronger forecast performance in all testing variables than existing leading operational numerical GOFSs including Mercator Ocean Physical SYstem (PSY4), Global Ice Ocean Prediction System (GIOPS), BLUElink OceanMAPS, and Forecast Ocean Assimilation Model (FOAM). Particularly, the accuracy of ocean current forecasting of XiHe out to 60 days is even better than that of PSY4 in just 10 days. Additionally, XiHe is able to forecast the large-scale circulation and the mesoscale eddies. Furthermore, it can make a 10-day forecast in only 0.35 seconds, which accelerates the forecast speed by thousands of times compared to the traditional numerical GOFSs. Copyright ©

关键词： Ocean currents

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Tuning the bandgap of double perovskites

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Journal of Semiconductors 2021年第12期42卷 6-8页

作者： Yu Zou Wenjin Yu Lixiu Zhang Cuncun Wu Lixin Xiao Liming Ding State Key Laboratory for Mesoscopic Physics Department of PhysicsPeking UniversityBeijing 100871China School of Materials Science and Engineering State Key Laboratory of Reliability and Intelligence of Electrical EquipmentHebei University of TechnologyTianjin 300130China Center for Excellence in Nanoscience(CAS) Key Laboratory of Nanosystem and Hierarchical Fabrication(CAS)National Center for Nanoscience and TechnologyBeijing 100190China

With great achievements in efficiency,stability,and large-scale preparation of perovskite solar cells(PSCs),the com-mercialization of PSC is ongoing,but there is still an issue on lead *** lead content in the device is low,the water solubility of lead salts leads to potential environmental *** present,the non-lead perovskites studied in-clude:divalent metal perovskite(e.g.,Sn^(2+),Ge^(2+),Cu^(2+)),trivalent metal perovskite(e.g.,Bi^(3+),Sb^(3+),In^(3+)),tetravalent met-al double perovskite(e.g.,Sn^(4+),Pd^(4+),Ti^(4+),Pt^(4+))and mono-trivalent mixed double perovskite(e.g.,Ag+and Bi^(3+),Ag+and In^(3+),Ag^(+)and Sb^(3+)).Their properties are summarized in Table *** the first report on non-lead double perovskite Cs2AgBiBr6 in 2016^([1]).

关键词： perovskite double valent

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A novel type of neural networks for feature engineering of geological data:Case studies of coal and gas hydrate-bearing sediments

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Geoscience Frontiers 2020年第5期11卷 1511-1531页

作者： Lishuai Jiang Yang Zhao Naser Golsanami Lianjun Chen Weichao Yan State Key Laboratory of Mining Disaster Prevention and Control Shandong University of Science and TechnologyQingdao 266590China College of Energy and Mining Engineering Shandong University of Science and TechnologyQingdao 266590China College of Safety and Environmental Engineering Shandong University of Science and TechnologyQingdao 266590China Department of Well Logging School of GeosciencesChina University of Petroleum(East China)Qingdao 266580China

The nature of the measured data varies among different disciplines of *** rock engineering,features of data play a leading role in determining the feasible methods of its proper *** present study focuses on resolving one of the major deficiencies of conventional neural networks(NNs)in dealing with rock engineering ***,since the samples are obtained from hundreds of meters below the surface with the utmost difficulty,the number of samples is always ***,the experimental analysis of these samples may result in many repetitive values and 0 ***,conventional neural networks are incapable of making robust models in the presence of such *** the other hand,these networks strongly depend on the initial weights and bias values for making reliable *** this in mind,the current research introduces a novel kind of neural network processing framework for the geological that does not suffer from the limitations of the conventional *** introduced single-data-based feature engineering network extracts all the information wrapped in every single data point without being affected by the other *** method,being completely different from the conventional NNs,re-arranges all the basic elements of the neuron model into a new ***,its mathematical calculations were performed from the very ***,the corresponding programming codes were developed in MATLAB and Python since they could not be found in any common programming software at the time *** new kind of network was first evaluated through computer-based simulations of rock cracks in the 3 DEC *** the model’s reliability was confirmed,it was adopted in two case studies for estimating respectively tensile strength and shear strength of real rock *** samples were coal core samples from the Southern Qinshui Basin of China,and gas hydrate-bearing sediment(GHBS)samples from the Nankai Trough of *** coa

关键词： Tensile strength Shear strength Gas Hydrate Feature engineering Rock engineering data Neuron model

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Wave soldering structure optimization simulation of multilayer ceramic capacitors

Wave soldering structure optimization simulation of multilay...

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2020 International Conference on Applied Physics and Computing, ICAPC 2020

作者： Su, Wei Luo, Wenhao Li, Junkui Liu, Renhuai MOE Key lab of Disaster Forecast and Control in Engineering Guangzhou510632 China Science and Technology on Reliability Physics and Application Technology of Electronic Component Laboratory China Electronic Product Reliability and Environmental Testing Research Institute Guangzhou510610 China School of Mechanics and Construction Engineering Jinan University Guangzhou510632 China

In this paper, the thermal analysis and structural analysis of MLCC are carried out by using the commercial finite element software ANSYS. By comparing the thermal-mechanical analysis results of the structural optimization models of different schemes, the optimal optimization scheme is found. The model calculated the time required for MLCC to reach temperature stability considering thermal convection and heat conduction, and obtained the thermal deformation and thermal stress distribution of MLCC element. Based on the analysis results of MLCC original model, the thermal analysis under different wave soldering temperatures was carried out. Based on the simulated transient results, the structure and materials of MLCC key components were optimized. The results provide a basis for the optimal design of MLCC. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： Thermoanalysis

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Research on the maturity assessment method of intelligent PHM for groundwater circulation well

Research on the maturity assessment method of intelligent PH...

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13th International Conference on Quality, reliability, Risk, Maintenance, and Safety engineering (QR2MSE 2023)

作者： B. Yang L. Zhang R. Yang Z. Miao P. Wang S. Pu H. Xu State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Chengdu University of Technology Chengdu People's Republic of China College of Management Science Chengdu University of Technology Chengdu People's Republic of China BCEG Environmental Remediation Co. Ltd. National Engineering Laboratory for Site Remediation Technologies Beijing People's Republic of China Beijing GeoEnviron Engineering & Technology Inc. Beijing People's Republic of China

ISBN: (数字)9781839539275

GCW system is one of the hot research objects of in-situ remediation of contaminated groundwater. However, the system will be difficult to maintain if there is a failure during underground operation. The uncertainty of the source of the failure will make it more difficult to perform maintenance on the system, which will delay the remediation process. Therefore, a method that can diagnose or predict system failures in a timely manner is needed. Based on RPL, this study designs an intelligent PHM system to predict potential failures of GCW systems based on the relationship between performance degradation and failure time of GCW systems. And the maturity of the intelligent PHM system is evaluated into 5 levels, and 15 maturity evaluation factors in 4 dimensions are proposed. The maturity model and its application process are obtained. This modeling method provides ideas for decision-makers and managers to carry out early maintenance, and estimate its development level in related fields.

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Ultimate strength analysis of local thinning tee pipe considering plastic strengthening effect

Ultimate strength analysis of local thinning tee pipe consid...

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2020 International Conference on Applied Physics and Computing, ICAPC 2020

作者： Su, Wei Luo, Wenhao Dong, Xianshan Liu, Renhuai MOE Key lab of Disaster Forecast and Control in Engineering Guangzhou 510632 China Science and Technology on Reliability Physics and Application Technology of Electronic Component Laboratory China Electronic Product Reliability Environmental Testing Research Institute Guangzhou510610 China School of Mechanics and Construction Engineering Jinan University Guangzhou510632 China

In this paper, the locally thinned three-way structure under internal pressure is analyzed based on the theory of plastic strengthening effect and limit analysis. A finite element model is presented through ANSYS commercial software to simulate the mechanical properties of orthogonal and oblique three-way structures. This paper systematically analyses how the shape and size of the thinning effect the plastic limit load of the pipe and what is the typical failure mode of plastic failure. Some valuable conclusions are drawn, which provide a useful reference for the design and production of the tee pipe. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： Finite element method

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Ultimate strength analysis of three-way pipe considering plastic reinforcement effect

Ultimate strength analysis of three-way pipe considering pla...

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2020 International Conference on Applied Physics and Computing, ICAPC 2020

Considering the plastic reinforcement effect in materials, the plastic limit load of the three-way structure is analyzed. ANSYS commercial finite element software is used for numerical simulation. According to the results, the paper discusses the influence of the plastic reinforcement effect on the pipe's plastic ultimate load and failure mode. And the structure is further analyzed to verify the theory and design ideas in actual engineering. For improving the design and safety assessment of the three-way structure, the results provide a theoretical basis and a numerical reference, and the finite element method is economical than the experimental method. At last, it satisfies the accuracy requirements of engineering. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： Finite element method

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