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Recent advances in ionic liquids-based hybrid processes for CO_(2) capture and utilization

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Journal of Environmental Sciences 2021年第1期33卷 281-295页

作者： Shaohan Lian Chunfeng Song Qingling Liu Erhong Duan Hongwei Ren Yutaka Kitamura Tianjin Key Laboratory of Indoor Air Enuironmental Quality Control School of Enuironmental Science and EngineeringTianjin UniversityTianjin 300072China Pollution Prevention Biotechnology Laboratory of Hebei Province School of Environmental Science and EngineeringHebei University of Science and TechnologyshijizhuangHebei 050018China Graduate School of L.ife and Environmental Sciences University of Tsukuba1-1-1TennodaiTsukubalbaraki 305-8572Japan

CO_(2) capture and utilization(CCU)is an effective strategy to mitigate global ***,adsorption and membranes are methods used for CO_(2) separation and capture,and various catalytic pathways have also been developed for CO_(2) *** widely researched and used in industry,these processes are energy-intensive and this challenge needs to be *** realize further optimization,novel materials and processes are continuously being *** generation materials such as ionic liquids(ILs)have shown promising potential for cost-effective CO_(2) capture and *** study reviews the current status of ILs-based solvents,adsorbents,membranes,catalysts and their hybrid processes for CO_(2) capture and *** special properties of ILs are integrated into new materials through hybridization,which significantly improves the performance in the process of CCU.

关键词： CO_(2) hybrid Ionic liquids Absorption Adsorption Membrane Catalysis

AC fault ride through control strategy on inverter side of hybrid HVDC transmission systems

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Journal of Modern Power Systems and Clean Energy 2019年第5期7卷 1129-1141页

作者： Zexin ZHOU Zhengguang CHEN Xingguo WANG Dingxiang DU Guosheng YANG Yizhen WANG Liangliang HAO China Electric Science Research Institute Co. Ltd.BeijingChina State Key Laboratory for Power Grid Safety and Energy Conservation BeijingChina School of Electrical Engineering and Automation Tianjin UniversityTianjinChina College of Electrical Engineering Beijing Jiaotong UniversityBeijingChina

hybrid high-voltage direct current(HVDC)transmission systems employ a new type of HVDC transmission topology that combines the advantages of the linecommutated converter system and the voltage-source converter *** can improve the efficiency and reliability of long-distance power ***,realizing alternating-current(AC)grid-fault ride through on the inverter side of a hybrid HVDC transmission system is a challenge considering that a voltage-source converter based HVDC(VSC-HVDC)is used on the inverter *** this study,a control strategy for an overvoltage fixed trigger angle based on the power-balance method is developed by fully utilizing the operation characteristics of a hybrid HVDC transmission *** strategy reduces the inverter-side overvoltage of the HVDC system under a fault in the inverter-side AC *** based on Gezhou Dam are conducted to validate the effectiveness of the proposed strategy.

关键词： hybrid HVDC transmission Fault crossing Control strategy Inverter side

Modeling of thermal conductivity and density of alumina/silica in water hybrid nanocolloid by the application of Artificial Neural Networks

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Chinese Journal of Chemical Engineering 2019年第3期27卷 726-736页

作者： Sathishkumar Kannaiyan Chitra Boobalan Fedal Castro Nagarajan Srinivas Sivaraman Department of Chemical Engineering Sri Sivasubramaniya Nadar College of Engineering Department of Mechanical Engineering Aarupadai Veedu Institute of Technology

In this research work, the thermal conductivity and density of alumina/silica(Al_2O_3/SiO_2) in water hybrid nanofluids at different temperatures and volume concentrations have been modeled using the artificial neural networks(ANN). The nanocolloid involved in the study was synthesized by the two-step method and characterized by XRD, TEM, SEM–EDX and zeta potential analysis. The properties of the synthesized nanofluid were measured at various volume concentrations(0.05%, 0.1% and 0.2%) and temperatures(20 to 60 °C). Established on the observational data and ANN, the optimum neural structure was suggested for predicting the thermal conductivity and density of the hybrid nanofluid as a function of temperature and solid volume concentrations. The results indicate that a neural network with 2 hidden layers and 10 neurons have the lowest error and a highest fitting coefficient o thermal conductivity, whereas in the case of density, the structure with 1 hidden layer consisting of 4 neurons proved to be the optimal structure.

关键词： Thermal conductivity Modeling hybrid nanocolloids ANN thermal energy

State of art on energy management strategy for hybrid-powered unmanned aerial vehicle

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Chinese Journal of Aeronautics 2019年第6期32卷 1488-1503页

作者： Tao LEI Zhou YANG Zicun LIN Xiaobin ZHANG School of Automation Northwestern Polytechnic UniversityXi’an 710129China Key Laboratory of Aircraft Electric Propulsion Technology Ministry of Industry and Information Technology of ChinaXi’an 710129China

New energy sources such as solar energy and hydrogen energy have been applied to the Unmanned Aerial Vehicle(UAV), which could be formed as the hybrid power sources due to the requirement of miniaturization, lightweight, and environmental protection issue for UAV. hybrid electrical propulsion technology has been used in UAV and it further enforces this trend for the evolution to the hybrid-Powered System(HPS). In order to realize long endurance flight mission and improve the energy efficiency of UAV, many researching works are focused on the Energy Management Strategy(EMS) of the HPS with digital simulation, ground demonstration platforms and a few flight tests for the UAV in recent years. energy management strategy, in which off-line or on-line control algorithms acted as the core part, could optimize dynamic electrical power distribution further and directly affect the efficiency and fuel economy of hybrid-powered system *** order to give the guideline for this emerging technology for UAV, this paper presents a review of the topic highlighting energy optimal management strategies of UAV. The characteristics of typical new energy sources applied in UAV are summarized firstly, and then the classification and analysis of the architecture for hybrid power systems in UAV are presented. In the context of new energy sources and configuration of energy system, a comprehensive comparison and analysis for the state of art of EMS are presented, and the various levels of complexity and accuracy of EMS are considered in terms of real time, computational burden and optimization performance based on the optimal control and operational modes of UAV. Finally, the tendency and challenges of energy management strategy applied to the UAV have been forecasted.

关键词： Energy management strategy(EMS) hybrid power system(HPS) New energy sources Optimization algorithms UAV

Chinese micro-blog sentiment classification through a novel hybrid learning model

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Journal of Central South University 2017年第10期24卷 2322-2330页

作者： LI Fang-fang WANG Huan-ting ZHAO Rong-chang LIU Xi-yao WANG Yan-zhen ZOU Bei-ji School of Information Science and Engineering Central South UniversityChangsha 410083China “Mobile Health”Ministry of Education–China Mobile Joint Laboratory Changsha 410083China College of Computer National University of Defense TechnologyChangsha 410073China

With the rising and spreading of micro-blog, the sentiment classification of short texts has become a research hotspot. Some methods have been developed in the past decade. However, since the Chinese and English are different in language syntax, semantics and pragmatics, sentiment classification methods that are effective for English twitter may fail on Chinese micro-blog. In addition, the colloquialism and conciseness of short Chinese texts introduces additional challenges to sentiment classification. In this work, a novel hybrid learning model was proposed for sentiment classification of Chinese micro-blogs, which included two stages. In the first stage, emotional scores were calculated over the whole dataset by utilizing an improved Chinese-oriented sentiment dictionary classification method. Data with extremely high or low scores were directly labeled. In the second stage, the remaining data were labeled by using an integrated classification method based on sentiment dictionary, support vector machine(SVM) and k-nearest neighbor(KNN). An improved feature selection method was adopted to enhance the discriminative power of the selected features. The two-stage hybrid framework made the proposed method effective for sentiment classification of Chinese micro-blogs. Experiments on the COAE2014(Chinese Opinion Analysis Evaluation 2014) dataset show that the proposed method outperforms other schemes.

关键词： Chinese micro-blog short text hybrid learning sentiment classification

Manipulation of multi-transparency windows and fast-slow light transitions in a hybrid cavity optomechanical system

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Science China(Physics,Mechanics & Astronomy) 2019年第5期62卷 75-83页

作者： Ming-Hua Zheng Tie Wang Dong-Yang Wang Cheng-Hua Bai Shou Zhang Cheng-Shou An Hong-Fu Wang Department of Physics College of Science Yanbian University Department of Physics Harbin Institute of Technology

We study the generation of quadruple-transparency windows and the implementation of a conversion between slow and fast light in a hybrid optomechanical system. By demonstrating the generation of these transparency windows one by one, we analyze the physical mechanism through which each transparency window forms in detail. Additionally, we discuss how the system parameters affect the formation of transparency windows and conclude that the location, width, and absorption of each transparency window can be arbitrarily manipulated by varying the appropriate parameters. Moreover, when the pump field is changed from red to blue detuning, conversions between slow and fast light occur in the output field. These interesting properties of the output field can be applied to achieve the coherent control and manipulation of light pulses using cavity optomechanical system.

关键词： hybrid cavity optomechanical system optomechanical induced transparency fast-slow light

Ultrafast Carrier Dynamics and Terahertz Photoconductivity of Mixed-Cation and Lead Mixed-Halide hybrid Perovskites

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Chinese Physics Letters 2019年第2期36卷 83-91页

作者： Wan-Ying Zhao Zhi-Liang Ku Li-Ping Lv Xian Lin Yong Peng Zuan-Ming Jin Guo-Hong Ma Jian-Quan Yao Department of Physics Shanghai University State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of Technology Department of Chemical Engineering School of Environmental and Chemical EngineeringShanghai University STU & SIOM Joint Laboratory for Superintense Lasers and Applications College of Precision Instrument and Opto-electronics Engineering Institute of Laser and Opto-electronicsTianjin University

Using time-dependent terahertz spectroscopy, we investigate the role of mixed-cation and mixed-halide on the ultrafast photoconductivity dynamics of two different methylammonium(MA) lead-iodide perovskite thin films. It is found that the dynamics of conductivity after photoexcitation reveals significant correlation on the microscopy crystalline features of the samples. Our results show that mixed-cation and lead mixed-halide affect the charge carrier dynamics of the lead-iodide perovskites. In the(5-AVA)_(0.05)(MA)_(0.95) PbI_(2.95) Cl_(0.05)/spiro thin film, we observe a much weaker saturation trend of the initial photoconductivity with high excitation fluence, which is attributed to the combined effect of sequential charge carrier generation, transfer, cooling and polaron formation.

关键词： Ultrafast Carrier Dynamics Terahertz Photoconductivity Mixed-Cation Lead Mixed-Halide hybrid Perovskites

Gas Sensors Based on Chemi?Resistive hybrid Functional Nanomaterials

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Nano-Micro Letters 2020年第6期12卷 27-69页

作者： Yingying Jian Wenwen Hu Zhenhuan Zhao Pengfei Cheng Hossam Haick Mingshui Yao Weiwei Wu School of Advanced Materials and Nanotechnology Interdisciplinary Research Center of Smart SensorsXidian UniversityXi’an 710071People’s Republic of China School of Aerospace Science and Technology Xidian UniversityXi’an 710071People’s Republic of China Department of Chemical Engineering Russell Berrie Nanotechnology InstituteTechnion-Israel Institute of Technology3200003 HaifaIsrael Institute for Integrated Cell-Material Sciences(WPI-iCeMS) Kyoto University Institute for Advanced StudyKyoto UniversityYoshida Ushinomiya-choSakyo-kuKyoto 606-8501Japan

Chemi-resistive sensors based on hybrid functional materials are promising candidates for gas sensing with high responsivity,good selectivity,fast response/recovery,great stability/repeatability,room-working temperature,low cost,and easy-to-fabricate,for versatile *** progress report reviews the advantages and advances of these sensing structures compared with the single constituent,according to five main sensing forms:manipulating/constructing heterojunctions,catalytic reaction,charge transfer,charge carrier transport,molecular binding/sieving,and their *** and challenges of the advances of each form are presented and *** thinking and ideas regarding the orientation of the development of hybrid material-based gas sensor in the future are discussed.

关键词： Gas sensor hybrid Chemi-resistor Functional nanomaterials

An intelligent SVM modeling process for crude oil properties prediction based on a hybrid GA-PSO method

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Chinese Journal of Chemical Engineering 2019年第8期27卷 1888-1894页

作者： Kexin Bi Tong Qiu Department of Chemical Engineering Tsinghua UniversityBeijing 100084China Beijing Key Laboratory of Industrial Big Data System and Application Beijing 100084China

Properties prediction of crude oil remains an essential issue for refineries. In this communication, an exhaustive and extendable support vector machine(SVM) intelligent prediction process has been proposed to solve this problem. A novel hybrid genetic algorithm-particle swarm optimization(GA-PSO)method was applied to optimize the SVM model. The optimization process and result demonstrated that the newly proposed GA-PSO-SVM method was more accurate and time-saving than the classical GA or PSO method. Compared with the classical Grid-search SVM, the combined GA-PSO-SVM model appeared to be more applicable for the properties prediction task. The TBP distillation curve fitting was exampled to evaluate the performance of the developed model. The regression result demonstrated the high accuracy and efficiency of the proposed process. The model can be applied in the Industrial Internet as a plugin, and the adaptability and flexibility is demonstrated by the implement of crude oil molecular reconstruction employing the intelligent prediction process.

关键词： Intelligent properties prediction Support vector machine hybrid GA-PSO TBP distillation curve fitting