As an important semiconductor photocatalytic material, bismuth oxide (Bi2O3) is considered as a promising visible photocatalyst due to its special electronic structure and excellent visible light response performance. It displays a good application prospect in photocatalytic treatment of wastewater. However, the application of Bi2O3 is limited by its low photocatalytic performance, therefore, Bi2O3 pholocatalyst with superior performance is expected to be obtained by modifying methods by the researchers. In this review, a series of modification methods, such as surface morphology regulation, surface modification, metal ion modification and semiconductor combination, are summarized. Then, the future development of modified Bi2O3 photocatalytic materials is prospected.
With the rapid economic development, the demand for energy continues to increase, and the emission of CO2 gas keep growing. The electrochemical reduction of carbon dioxide (ERC) to fuel and chemicals is an effective way to realize the conversion and utilization of CO2 as well as the storage of renewable energy. Cu?based catalysts are one of the materials which can directly reduce CO2 to high value?added chemicals(such as hydrocarbons) with high efficiency. Thus, the Cu?based catalysts have been one of the research focus of ERC technology research. The main research progress of Cu?based catalysts for ERC technology in recent years is reviewed. Firstly, reaction principle of ERC and the technology challenge are summarized, and then the cooperative control strategy for the structure and composition of copper?based catalysts is discussed for monometallic copper?based catalysts, polymetallic copper?based catalysts, copper oxide and oxide?derived copper catalysts, and copper?organic composite catalysts. In addition, research progress and unsolved problems of Cu?based catalysts are also summarized. Finally, the future trend these catalysts is also prospected.
In different production stages of shale gas fields, various operating conditions and parameters vary widely, and the operating conditions of the triethylene glycol dehydration unit may deviate from the optimal range, which may easily lead to insignificant dehydration effects, which will affect normal production. The HYSYS software was used to simulate the process of a 300.0×104 Nm3/d shale gas triethylene glycol dehydration unit.The influence of the process parameters on the dehydration effect of the triethylene glycol such as the triethylene glycol circulation volume, the mass fraction of the triethylene glycol lean liquid, the flow rate of the feed gas into the tower, and the temperature of the feed gas into the tower,the operating pressure of the absorption tower, the temperature of the lean triethylene glycol liquid entering the tower, the total efficiency of the trays and the number of trays in the absorption tower were quantitatively analyzed.And the reasonable operating range of each process parameter was determined to achieve the best dehydration effect and meet the requirements of dry gas export. The results show that increasing the triethylene glycol circulation, lean liquid mass fraction, absorption tower operating pressure, total tray efficiency and number of absorption trays, as well as reducing the flow and temperature of feed gas into the tower, and the temperature of triethylene glycol lean liquid entering the tower are all helpful to improve the dehydration effect of triethylene glycol; increasing the temperature of the reboiler and the flow of stripping gas are beneficial to increase the mass fraction of the lean triethylene glycol. In addition, the HYSYS simulation calculation results are compared with the on?site production data. The results show that the two are basically consistent, which verifies the accuracy of the simulation calculation results, which can be used to guide actual production. The above research has certain guiding significance for improving dehydration efficiency and reducing investment cost.
The Li2ZnTi3O8@polyaniline (LZTO@PANI) composite materials were prepared by sol?gel and chemical oxidation polymerization methods using tetrabutyl titanate, zinc acetate, lithium acetate and aniline as raw materials. The materials were characterized and analyzed by X?ray diffraction (XRD), infrared spectroscopy (IR), scanning electron microscope (SEM) transmission electron microscope (TEM) and electrochemical testing. The results show that the polyaniline in the composite material has an amorphous structure and no impurities are introduced. When the coating amount of polyaniline is 5.3%, the discharge specific capacity is 330.0 (mA·h)/g at 0.1 A/g. In addition, after 100 cycles, the specific discharge capacity is 281.3 (mA·h)/g.
Study on the Interface of Monitoring Configuration Software Based on SVG
The graphical interface is one of the basic components of the monitoring configuration software, which has a great impact on the software. However, a variety of configuration software currently used different graphic styles to form the monitor screen, so that different systems interact difficultly. To overcome this shortcoming and improve the reusing rate of code writing monitor screen and enhance applications efficiency of dealing with a lot of graphics information, this paper sets up a monitoring graphics elements library of configuration software, which uses SVG recommended by the international image formats of monitoring interface, and elaborates the way to define equipment element property. Integrating Batik project of ASF (Apache software foundation) and adopting Object Orient Design Thought, the paper analyses and designs the monitoring graphics elements library module of configuration software. Configuring graph's properties as the corresponding with relational SQL datebase which facilitate the programmer inputs data, can improve the total level of the configuration software.
As the greenhouse effect becomes gradually significant, CO2 capture and storage (CCS) has turned into a potential emission reduction measure, and the adsorption method of CO2 capture is one of the most promising technologies. Porous solid adsorbents have attracted widespread attention due to their excellent CO2 adsorption performance. This review focused on the research of CO2 removal by adsorption. Five different adsorption materials were introduced, and the main factors affecting CO2 adsorption were summarized, as well as the adsorption performance of modified materials. The results show that the changes of temperature, pressure, and pore structure can affect the physical adsorption properties of the materials; reduction, oxidation, and metal ion loading modification can improve the CO2 adsorption performance by Changing the type or number of functional groups on the surface of the material.
In recent years, the natural gas hydrate as a new type of high efficiency, energy saving, environmental protection energy was praised by the world's energy industry, and its potential value could not be ignored. The study of gas hydrate was integrated in different countries of the world history, the present research situation and prospect analysis. In view of the natural gas hydrate in China started to be late and a series of actual situation, a set of research strategies suitable for the current development of our country was put forward, and some problems in the process of the actual mining were introduced.
The common research methods for the adsorption and diffusion of zeolite molecular sieves at home and abroad, the characteristics and applicable scope of each method, and the research status of adsorption and diffusion phenomena at home and abroad are introduced. The research results of domestic and foreign scientific research workers are systematically introduced. On this basis, the scientific problems that existed in this field are put forward. Aiming at these problems, a research program by using gas chromatography for the study of adsorption and diffusion phenomena is proposed. The principle of gas chromatography and the method of adsorption and diffusion are described in detail. The corresponding formulas are deduced, and the application of gas chromatography in the study of adsorption and diffusion is also prospected.
Long-term natural gas load forecasting can solve the problem of the imbalance between supply and demand of city gas and provide assistance for the city gas company's management and running. In order to improve the accuracy of predicting the longterm natural gas load,a forecasting model of natural gas longterm load was built based on SVM-GA(Support Vector MachinesGenetic Algorithm). The relevant factors influencing natural gas consumption was analyzed and determined. In order to improve prediction accuracy, the penalty factor c and the kernel parameter g of support vector machines were optimized using genetic algorithm and cross validation methods. Optimized parameters were inputted support vector machines model and long-term natural gas load forecasting was made. In a case study from a certain city,a comparative analysis was made of the forecasting results among SVM-GA,SVM and crossvalidation method combined prediction model and BP(Back Propagation) neural networks. The forecasting model based on SVM-GA was validated with a high prediction accuracy and the resulted relative mean square error,normalization mean square error,normalization absolute square error,normalization rootmean square error, maximum absolute error resulted from the SVM-GA were lower than those from SVM and crossvalidation method combined prediction model or BP neural networks by 0.58%,3.98%,2.99%,4.58%,8.64% and 6.13%,26.28%,19.71%,21.09%,31.48%. Therefore,the support vector machine and genetic algorithm combined model can accurately predict the long-term natural gas load.
Power grid is diagnosed after a failure to prevent the fault occurred by inferring the information that the fault generated.The method of model prediction (MP) and abductive reasoning network(ARN) is proposed to forecast the power system fault. MP predicted the troublefree operation data of the power grid by using historical data, and compared with the actual grid runtime data, the difference was calculated and used as the input of fault diagnosis system. ARN was used to bulid the fault diagnosis system and solve the complicated relationships between data processing and the corresponding candidate fault section. The fault location can be found before protection device and circuit breaker by combining the method of MP and ARN. The test results showed that the model prediction method can quickly and accurately diagnose the fault compared with BP neural network method.
The dust removal characteristics and working mechanism of the current four major types of dust collectors were reviewed. It mainly focused on electrostatic precipitator technology, introduced its research status at home and abroad in recent years, analyzed the influence of many different factors (equipment structure parameters, gas characteristics, dust properties) on the efficiency of electrostatic precipitator equipment, and summarized electrostatic precipitator. The current technical shortcomings of the collector: The selection of the discharge electrode, the optimization of the best parameters, the anti?corrosion and cleaning of the dust collecting plate. In the future, the following issues should be focued on: development of discharge electrode materials suitable for new forms of electrostatic precipitators, discharge characteristics and dust removal efficiency in complex atmospheres, reduced insulation performance at the dust collector, and corrosion protection.
For a long time, fabric defect detection has been completed by quality inspectors. Meanwhile, the process of defect discrimination is greatly affected by subjective factors and has the problems of low detection efficiency and high cost. With the close combination of computer vision technology and various fields, fabric defect detection system based on vision has gradually become an important solution to replace manual quality inspection. For the fabric defect detection based on vision, this paper reviews the aspects including industry development, general detection standards, overall structure of the system and key technologies in detection algorithms, introduces the existing fabric defect detection products based on vision in the market, analyzes the common defect detection standards and the basic structure of the detection system, and summarizes and compares the research status of image processing and deep learning technology in the field of fabric defect detection in recent years. Finally, the paper summarizes the key problems to be solved, and discusses the possible development direction in the future.