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A Novel Oscillating Chemical Reaction Using Ninhydrin as Single Organic Substrate

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Chinese Chemical Letters 2006年第1期17卷 77-80页

作者： fu Wei yang Jin zhang GAO Wu yang Kan Jun SUN Institute of Chemistry Northwest Normal University Lanzhou 730070

A novel oscillating chemical reaction using ninhydrin as a single organic substrate was represented in this paper. It distinguished from the classically catalyzed BZ oscillating chemical reaction due to there was no active methene （CH2=） and/or enol structure in the ninhydrin molecule, which served as single organic substrate. This suggested that the substrates used in catalyzed BZ reaction were not always the organic compounds containing active methene （CH2=） and/or enol structure and bromination process in this kind of catalyzed chemical oscillating reaction was not also necessary.

关键词： Single organic substrate active methene enol structure oscillating chemical reaction.

Solar evaporation for simultaneous oil-water separation and electricity generation with Janus wood-based absorbers

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Frontiers of Environmental Science & Engineering 2024年第2期18卷 13-23页

作者： Yue yang Ze fu Qi zhang Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse School of Environmental and Biological EngineeringNanjing University of Science&TechnologyNanjing 210094China Key Laboratory of Industrial Ecology and Environmental Engineering(Ministry of Education) School of Environmental Science and TechnologyDalian University of TechnologyDalian 116024China National Laboratory of Solid State Microstructures Collaborative Innovation Center of Advanced MicrostructuresCollege of Engineering and Applied SciencesKey Laboratory of Intelligent Optical Sensing and Manipulation(Ministry of Education)Jiangsu Key Laboratory of Artificial Functional MaterialsNanjing UniversityNanjing 210093China

Oily wastewater from ocean oil spills endangers marine ecosystems and human health. Therefore, developing an effective and sustainable solution for separating oil-water mixtures is urgent. Interfacial solar photothermal evaporation is a promising approach for the complete separation of two-phase mixtures using only solar energy. Herein, we report a carbonized wood-based absorber with Janus structure of comprising a hydrophobic top-layer and an oleophobic bottom-layer for simultaneous solar-driven oil-water separation and electricity generation. Under sunlight irradiation, the rapid evaporation of seawater will induce a separation of oil-water mixtures, and cause a high salt concentration region underlying the interface, while the bottom “bulk water” maintains in a low salt concentration, thus forming a salinity gradient. Electricity can be generated by salinity gradient power. Therefore, oil-water separation efficiency of > 99% and derived extra electricity power of ~0.1 W/m2 is achieved under solar radiation, demonstrating the feasibility of oil-water separation and electricity production synchronously directly using solar energy. This work provides a green and cost-effective path for the separation of oil-water mixtures.

关键词： Oily wastewater Carbonized wood Salinity gradient Electricity generation Solar irradiation

Degradation behaviors of Nabumetone and its metabolite during UV/monochloramine process:Experimental and theoretical study

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Journal of Environmental Sciences 2024年第8期142卷 103-114页

作者： Xiang Tu Yunsong Bai Qing fu Sheng Chang Kunfeng zhang yang Pan Ruiyang Xiao Yifu fu Qi zhang State Key Laboratory of Environmental Criteria and Risk Assessment State Environmental Protection Key Laboratory of Drinking Water Source ProtectionResearch Centre of Lake EnvironmentNational Engineering Laboratory for Lake Pollution Control and Ecological RestorationChinese Research Academy of Environmental SciencesBeijing 100012China School of Environmental Science and Engineering Suzhou University of Science and TechnologySuzhou 215009China Institute of Environmental Engineering School of Metallurgy and EnvironmentCentral South UniversityChangsha 410083China School of Forestry Northeast Forestry UniversityHarbin 150040China

This study investigated degradation behaviors of a nonsteroidal anti-inflammatory drug Nabumetone(NMT)and its major metabolite 6-methoxy-2-naphthylacetic acid(MNA)in the coupling process of ultraviolet and monochloramine(UV/NH2Cl).The second-order rate constants of the contaminants reacting with reactive radicals(HO·,Cl·,Cl_(2)·-,and CO_(3)·^(-))were determined by laser flash photolysis ***·and Cl·contributed predominantly with 52.3%and 21.7%for NMT degradation and 60.8%and 22.3%for MNA *** presence of chlorides retarded the degradation of NMT,while promoted the destruction of MNA,which was ascribed to the photosensitization effects of MNA under UV *** functional theory(DFT)calculations revealed that radical adduct formation(RAF)was dominant pathway for both HO·and Cl·reacting with the contaminants,and hydrogen atom transfer(HAT)preferred to occur on side chains of NMT and *** reacted with NO_(2)·through single electron transfer(SET)with the second-order rate constant calculated to be 5.35×10^(7)(mol/L)^(-1)sec^(-1),and the contribution of NO_(2)·was predicted to be 13.0%of the total rate constant of NMT in pure water,which indicated that NO_(2)·played a nonnegligible role in the degradation of *** acute toxicity and developmental toxicity of NMT were enhanced after UV/NH_(2)Cl treatment,while those of MNA were *** transformation products of both NMT and MNA exhibited higher mutagenicity than their parent *** study provides a deep understanding of the mechanism of radical degradation of NMT and MNA in the treatment of UV/NH2Cl.

关键词： UV/NH_(2)Cl Reactive species Degradation kinetics Reaction mechanism Degradation products

Deep learning CNN-APSO-LSSVM hybrid fusion model for feature optimization and gas-bearing prediction

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Petroleum Science 2024年第4期21卷 2329-2344页

作者： Jiu-Qiang yang Nian-Tian Lin Kai zhang Yan Cui Chao fu Dong zhang College of Earth Sciences and Engineering Shandong University of Science and Technology Laboratory for Marine Mineral Resources Qingdao National Laboratory for Marine Science and Technology Transportation Institute of Inner Mongolia University Key Laboratory of Gas Hydrate Qingdao Institute of Marine Geology Ministry of Natural Resources

Conventional machine learning(CML) methods have been successfully applied for gas reservoir prediction. Their prediction accuracy largely depends on the quality of the sample data; therefore, feature optimization of the input samples is particularly important. Commonly used feature optimization methods increase the interpretability of gas reservoirs; however, their steps are cumbersome, and the selected features cannot sufficiently guide CML models to mine the intrinsic features of sample data efficiently. In contrast to CML methods, deep learning(DL) methods can directly extract the important features of targets from raw data. Therefore, this study proposes a feature optimization and gas-bearing prediction method based on a hybrid fusion model that combines a convolutional neural network(CNN)and an adaptive particle swarm optimization-least squares support vector machine(APSO-LSSVM). This model adopts an end-to-end algorithm structure to directly extract features from sensitive multicomponent seismic attributes, considerably simplifying the feature optimization. A CNN was used for feature optimization to highlight sensitive gas reservoir information. APSO-LSSVM was used to fully learn the relationship between the features extracted by the CNN to obtain the prediction results. The constructed hybrid fusion model improves gas-bearing prediction accuracy through two processes of feature optimization and intelligent prediction, giving full play to the advantages of DL and CML methods. The prediction results obtained are better than those of a single CNN model or APSO-LSSVM model. In the feature optimization process of multicomponent seismic attribute data, CNN has demonstrated better gas reservoir feature extraction capabilities than commonly used attribute optimization methods. In the prediction process, the APSO-LSSVM model can learn the gas reservoir characteristics better than the LSSVM model and has a higher prediction accuracy. The constructed CNN-APSO-LSSVM mode

关键词： Multicomponent seismic data Deep learning Adaptive particle swarm optimization Convolutional neural network Least squares support vector machine Feature optimization Gas-bearing distribution prediction

Dynamics of Land Use/Land Cover Considering Ecosystem Services for a Dense-Population Watershed Based on a Hybrid Dual-Subject Agent and Cellular Automaton Modeling Approach

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Engineering 2024年第6期37卷 182-195页

作者： Yutong Li Yanpeng Cai Qiang fu Xiaodong zhang Hang Wan Zhifeng yang Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds Institute of Environmental and Ecological EngineeringGuangdong University of TechnologyGuangzhou 510006China School of Water Conservancy and Civil Engineering Northeast Agricultural UniversityHarbin 150030China School of Environmental Science and Engineering Shandong UniversityQingdao 266000China

Land use/land cover represents the interactive and comprehensive influences between human activities and natural conditions,leading to potential conflicts among natural and human-related issues as well as among *** study introduced economic standards for farmers.A hybrid approach(CA-ABM)of cellular automaton(CA)and an agent-based model(ABM)was developed to effectively deal with social and land-use synergic issues to examine human–environment interactions and projections of land-use conversions for a humid basin in south *** attributes and socioeconomic data were used to analyze land use/land cover and its drivers of *** major modules of the CA-ABM are initialization,migration,assets,land suitability,and land-use change *** estimates of the factors influencing the urban land-use conversion probability were captured using parameters based on a spatial logistic regression(SLR)***,multicriteria evaluation(MCE)and Markov models were introduced to obtain empirical estimates of the factors affecting the probability of ecological land *** agent-based CA-SLR-MCE-Markov(ABCSMM)land-use conversion model was proposed to explore the impacts of policies on land-use *** model can reproduce observed land-use patterns and provide links for forest transition and urban expansion to land-use decisions and ecosystem *** results demonstrated land-use simulations under multi-policy scenarios,revealing the usefulness of the model for normative research on land-use management.

关键词： Land use/land cover Human-environment interactions Agent-based model Cellular automaton

Energy Management of Price-maker Community Energy Storage by Stochastic Dynamic Programming

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 492-503页

作者： Lirong Deng Xuan zhang Tianshu yang Hongbin Sun yang fu Qinglai Guo Shmuel S.Oren Department of Electrical Engineering Shanghai University of Electric PowerShanghai 200000China Tsinghua-Berkeley Shenzhen Institute Tsinghua UniversityShenzhen 518055China Department of Industrial Engineering and Operations Research University of California BerkeleyBerkeleyCAUSA Risk Analytics and Optimization Chair EPFLSwitzerlandand also with Power Systems LaboratoryETH Zurich8092 ZurichSwitzerland State Key Laboratory of Power Systems Department of Electrical EngineeringTsinghua UniversityBeijing 100084China

In this paper,we propose an analytical stochastic dynamic programming(SDP)algorithm to address the optimal management problem of price-maker community energy *** a price-maker,energy storage smooths price differences,thus decreasing energy arbitrage ***,this price-smoothing effect can result in significant external welfare changes by reduc-ing consumer costs and producer revenues,which is not negligible for the community with energy storage *** such,we formulate community storage management as an SDP that aims to maximize both energy arbitrage and community *** incorporate market interaction into the SDP format,we propose a framework that derives partial but sufficient market information to approximate impact of storage operations on market *** we present an analytical SDP algorithm that does not require state *** from computational efficiency,another advantage of the analytical algorithm is to guide energy storage to charge/discharge by directly comparing its current marginal value with expected future marginal *** studies indicate community-owned energy storage that maximizes both arbitrage and welfare value gains more benefits than storage that maximizes only *** proposed algorithm ensures optimality and largely reduces the computational complexity of the standard *** Terms-Analytical stochastic dynamic programming,energy management,energy storage,price-maker,social welfare.

关键词： Analytical stochastic dynamic programming energy management energy storage price-maker social welfare

Sulfur and carbon co-doped g-C_(3)N_(4)microtubes with enhanced photocatalytic H2 production activity

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Frontiers in Energy 2024年第1期18卷 110-121页

作者： yang GE Quanhao SHEN Qi zhang Naixu LI Danchen LU Zhaoming zhang Zhiwei fu Jiancheng ZHOU School of Chemistry and Chemical Engineering Southeast UniversityNanjing 211189China Shangdong Yellow Triangle Biotechnology Industry Research Institute Co. Ltd.Dongying 257091China Xuzhou B&C Chemical Co. Ltd.Xuzhou 221300China

Metal-free graphitic carbon nitride(g-C_(3)N_(4))has captured significant attention as a low-cost and efficient hydrogen production photocatalyst *** regulating the microstructure and accelerating the separation of photogenerated carriers remain crucial strategies for promoting the photocatalytic performance of this ***,a novel sulfur–carbon co-doped g-C_(3)N_(4)(SCCN)hierarchical microtubules filled with abundant nanosheets inside by thermal polymerization is *** nanosheets create abundant pores and cavities inside the SCCN microtubes,thereby increasing the specific surface area of g-C_(3)N_(4)and providing sufficient reactant attachment ***,the hierarchical structure of SCCN microtubules strengthens the reflection and scattering of light,and the utilization of visible light is favorably *** importantly,co-doping S and C has greatly improved the photocatalytic performance of graphitic carbon nitride,optimized the band gap structure and enhanced the photogenerated carrier ***,the SCCN exhibits a remarkable photocatalytic H_(2)evolution rate of 4868μmol/(g·h).This work demonstrates the potential of multi-nonmetal doped g-C_(3)N_(4)as the ideal photocatalyst for H2 evolution.

关键词： carbon nitride photocatalysis hydrogen production

Deep Guided Attention Network for Joint Denoising and Demosaicing in Real Image

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Chinese Journal of Electronics 2024年第1期33卷 303-312页

作者： Tao zhang Ying fu Jun zhang School of Computer Science and Technology Beijing Institute of Technology Advanced Reasearch Institute of Multidisciplinary Science Beijing Institute of Technology

Denoising(DN) and demosaicing(DM) are the first crucial stages in the image signal processing pipeline. Recently, researches pay more attention to solve DN and DM in a joint manner, which is an extremely undetermined inverse problem. Existing deep learning methods learn the desired prior on synthetic dataset, which limits the generalization of learned network to the real world data. Moreover, existing methods mainly focus on the raw data property of high green information sampling rate for DM, but occasionally exploit the high intensity and signalto-noise(SNR) of green channel. In this work, a deep guided attention network(DGAN) is presented for real image joint DN and DM(JDD), which considers both high SNR and high sampling rate of green information for DN and DM, respectively. To ease the training and fully exploit the data property of green channel, we first train DN and DM sub-networks sequentially and then learn them jointly, which can alleviate the error accumulation. Besides, in order to support the real image JDD, we collect paired raw clean RGB and noisy mosaic images to conduct a realistic dataset. The experimental results on real JDD dataset show the presented approach performs better than the state-of-the-art methods, in terms of both quantitative metrics and qualitative visualization.

关键词： Training Visualization Inverse problems Green products Noise reduction Pipelines Signal processing

A dual measurement method of strain and temperature

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Journal of Marine Science and Application 2007年第1期6卷 63-68页

作者： JIANG Hai-li SUN Wei-min zhang Cong LIU Zhi-hai JIANG fu-qiang zhang yang College of Science Harbin Engineering University Harbin 150001 China

With the rapid development of China's foreign trade, the coastal and inland waterway transport has been increased rapidly. The potential market for marine engines is more and more obvious. The measurement of the engine temperature and strain becomes very important. The fluorescence fiber sensors are broadly used to measure temperature, concentration, and pH value, etc. The fluorescence sensing systems are based on different principles, namely fluorescence intensity, fluorescence intensity ratio, and fluorescence lifetime. The fluorescence lifetime is an effective parameter for sensing purpose, because it is independent of the intensity of the pumping source and does not need expensive narrow-band filters. An experiment system has been established, in which some samples were produced to measure the fluorescence lifetime and temperature characteristics and the relationship of the strain and temperature versus the fluorescence lifetime was achieved at the same time. The experiment result was fitted and analyzed. The test results show that the fluorescence lifetime decreases with the increasing of temperature. The change of fluorescence lifetime with the strain is inconspicuous comparing to that with the temperature.

关键词： fluorescence lifetime fluorescence fiber simultaneous measurement temperature strain