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Sensing characterization of Sn/In/Ti nanocomplex oxides for CO, CH_4 and NO_2

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Science china(Technological Sciences) 2007年第1期50卷 18-26页

作者： BAI ShouLi1, TONG zhangFa2, LI DianQing1, HUANG XiaoWei3, LUO RuiXian1 & CHEN AiFan1 1 State Key Laboratory of chemical Resource engineering, beijing university of chemical technology, beijing 100029, china 2 School of Chemistry and chemical engineering, Guangxi university, Nanning 530004, china 3 College of Biochemical engineering, beijing Union university, beijing 100023, china 1. State Key Laboratory of chemical Resource engineering Beijing University of Chemical Technology Beijing 100029 China 2. School of Chemistry and chemical engineering Guangxi University Nanning 530004 China 3. College of Biochemical engineering Beijing Union University Beijing 100023 China

The nanocomplex oxides of Sn-In and Sn-In-Ti were prepared by controlled co-precipitation method as sensing materials of semiconductor gas sensors for detection of CO, CH4 and NO2. Through manipulating the Sn/In cation ratio, metal salt total concentration, precipitation pH value and aging time, the nanocrystalline powders were successfully derived with chemical homogeneity and superior thermal stability, compared with the single component oxides. The particle size and morphology, surface area, and thermal and phase stabilities were characterized using TEM, TG-DTA, BET and XRD. The sensing tests showed that the Sn-In com-posites exhibit high sensitivity and selectivity for CO and NO2. The introduction of TiO2 enhanced CH4 sensitivity and selectivity, particularly, additives of Pd and Al2O3 as a dopant and surface modification greatly enhanced the sensing properties. The sensitivity depended on the composition of composites, calcination temperature and operating temperature. The optimal values were (25%In2O3- 75%SnO2)-20%TiO2 for ternary composite, 600 and 300℃, respectively. Temperature-programmed de-sorption (TPD) studies were employed to explain the gas adsorption behavior dis-played by the surface of nanocomposites and X-ray photoelectron spectroscopic (XPS) analysis was used to confirm the electronic interactions existing between oxide components. The sensing mechanism of the nanocomposites was attributed to chemical and electronic synergistic effects.

关键词： SnO2-In2O3-TiO2 nanocomposites CO NO2 CH4 gas sensing

Theoretical analysis of alloy multiplying factor by the empirical electron theory of solids and molecules

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Science china(Technological Sciences) 2007年第6期50卷 807-814页

作者： SONG YuePeng1,2, LIU GuoQuan2, LI ZhiLin3, FENG ChengMing1 1 Mechanical and Electronic engineering College, Shandong Agricultural university, Tai’an 271018, china 2 College of Materials Science and engineering, university of Science and technology, beijing 100083, china 3 College of Material Science and engineering, beijing university of chemical technology, beijing 100029, china Mechanical Electronic engineering College Shandong Agricultural University Tai’an 271018 China College of Materials Science engineering University of Science technology Beijing 100083 China College of Material Science engineering Beijing University of Chemical Technology Beijing 100029 China

By introducing the distribution probability of structural units in austenite contain- ing alloying elements and considering its effects on phase transformation, this paper establishes a calculation model of distribution probability of structural units. A new valence electron structure (VES) parameter-transformation effect coefficient of alloying elements (HL), is defined and then studied both theoretically and ex- perimentally. The relationship between the parameter HL and the multiplying factor (the quenching capability factor) of alloying elements is studied. The results indi- cate that the two parameters (HL and the quenching capability factor) have the same variation characteristic and substance feature. Therefore, the multiplying factor virtually expresses the relative quantity of structural units in the alloying elements-containing austenite.

关键词： multiplying factor (the quenching capability factor), empirical electron theory of solids and molecules, transformation effect coefficient of alloying elements, structural units in austenite containing alloying elements

Investigation of ZSM-5/MCM-41 Composite Molecular Sieve for Reducing Olefin Content of FCC Gasoline

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china Petroleum Processing & Petrochemical technology 2009年第4期11卷 10-17页

作者： Ji Dekun~(1,2) Li Shuyuan~1 Ding Fuchen~2 Chi Yaoling~2 (1.chemical engineering School,china university of Petroleum(beijing),beijing 102249 2.Department of chemical engineering,beijing Institute of Petrochemical technology) chemical engineering School China University of Petroleum (Beijing) Beijing 102249 China Department of chemical engineering Beijing Institute of Petrochemical Technology China

ZSM-5/MCM-41 composite molecular sieve was prepared by the nano-assembling *** ZSM-5 molecular sieve,the MCM-41 molecular sieve,the ZSM-5/MCM-41 mechanical mixture and the ZSM-5/MCM-41 composite molecular sieve were characterized by X-ray powder diffractometry,N_2 adsorption isotherms,temperature programmed desorption of ammonia and scanning electron microscopy and their properties were *** FCC gasoline as the feed,activities of different molecular sieves for reducing olefin content were investigated in a continuous high-pressure micro-reactor unit under the following conditions:a reaction temperature of 400℃,a reaction time of 2 h,a weight hourly space velocity of 3h^(-1),and a reaction pressure of 2.0 *** results showed that the HMCM-41 molecular sieve had low reaction performance,and the HZSM-5 molecular sieve demonstrated high aromatization activity,while the ZSM-5/MCM- 41 composite molecular sieve exhibited a best olefin-reducing performance because of its high isomerization activity and moderate aromatization *** a largest olefin-reducmg capability and a reasonable distribution of products,the composite molecular sieve was more suitable for FCC gasoline upgrading compared to other three catalysts.

关键词： ZSM-5 MCM-41 composite molecular sieve FCC gasoline olefin reduction

Inducing effect of Pb(Zr_(0.4)Ti_(0.6))O_3 thin film derived by different processes in BiFeO_3/Pb(Zr_(0.4)Ti_(0.6))O_3 multilayer capacitor at room temperature

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Science china(Technological Sciences) 2009年第1期52卷 10-14页

作者： XIE Dan1, ZANG YongYuan1, LUO YaFeng1, REN TianLing1, LIU LiTian1 & DANG ZhiMin2 1 Institute of Microelectronics, Tsinghua university, beijing 100084, china 2 College of Material Science and engineering, beijing university of chemical technology, beijing 100029, china Institute of Microelectronics Tsinghua University Beijing 100084 China College of Material Science and engineering Beijing University of Chemical Technology Beijing 100029 China

BiFeO3/PZT multilayer capacitor was prepared on Pt(100)/Ti/SiO2/Si(100) substrate. PZT buffer layer was derived by MOCVD method (label: PZT1) and sputtering method (label: PZT2) respectively. XRD analysis indicated that high (110) orientation of BFO in the BFO/PZT1 structure was achieved. SEM analysis indicated a better microstructure in the BFO/PZT1 structure compared with BFO/PZT2. The remnant polarization of the BFO/PZT1 was 82.5 μC/cm2 at an applied voltage of 8 V, compared with that of 25.2 μC/cm2 in the BFO/PZT2 structure. The BFO/PZT1 multilayer exhibited little polarization fatigue (1.5%) upon 1×1010 switching cycles, at an applied voltage of 4 V. The leakage current density was about 2×10?7 A/cm2 at an applied voltage 4 V, in the BFO/PZT1 capacitor. All the results indicated that PZT can act as an inducing layer to the BFO and the MOCVD derived PZT has more inducing effect to the BFO thin film at room temperature.

关键词： BFO PZT MOCVD properties FeRAM

Process optimization of reaction of acid leaching residue of asbestos tailing and sodium hydroxide aqueous solution

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Science china(Technological Sciences) 2009年第1期52卷 204-209页

作者： DU GaoXiang1,3, ZHENG ShuiLin2 & DING Hao1 1 School of Materials Science and technology, china university of Geosciences (beijing), beijing, 100083, china 2 School of chemical and Environment engineering, china university of Mining and technology (beijing), beijing 100083, china 3 hebei Qinghe Refractory Group Co. Ltd., Xingtai 054804, china 1. School of Materials Science and technology China University of Geosciences (Beijing) Beijing 100083 China 3. hebei Qinghe Refractory Group Co. Ltd. Xingtai 054804 China 2. School of chemical and Environment engineering China University of Mining and Technology (Beijing) Beijing 100083 China

Silica is the major component of the acid leaching residue of asbestos tailing. The waterglass solution can be prepared by the reaction of the residue with sodium hydroxide aqueous solution. Compared to the high temperature reaction method, this process is environmental friendly and low cost. In this paper, the reaction process of the residue and the sodium hydroxide aqueous solution is optimized. The optimum reaction process parameters are as follows: the usage of sodium hydroxide is 26.4 g/100 g acid leaching residue, the reaction temperature is 90℃, the reaction time is 1 h, and the ratio of the liquid/solid is 2.0. The significance sequence of the process parameters to the alkali leaching reaction effect is the usage of sodium hydroxide > the ratio of the liquid/solid > the reaction time > the reaction temperature. The significance sequence to the leaching ratio of SiO2 is the ratio of the liquid/solid > the usage of sodium hydroxide > the reaction time > the reaction temperature. The significance sequence to the modulus of the sodium silicate is the ratio of the liquid/solid > the usage of sodium hydroxide > the reaction time > the reaction temperature. Under the optimum conditions, the leaching ratio of the SiO2 is 77.5%, and the modulus of the sodium silicate is 3.15. The XRD analysis result indicates that the major components of the alkali leaching residue are serpentine, talc, quartz and some albite.

关键词： asbestos tailing acid leaching residue sodium hydroxide process optimization

Speed Sensorless Control System of Induction Machine Using Adaptive Rotor Resistance Observer

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Speed Sensorless Control System of Induction Machine Using A...

2009中国控制与决策会议

作者： kang shanlin~1,kang yuzhe~2,zhang huanzhen~1 1.hebei university of engineering,handan 05603.,china 2.beijing university of chemical technology,beijing 100029,china

Due to quick torque response and robustness against parameter variation,the direct torque control system has been widely utilized in the industrial *** improve its dynamic performance,a novel approach using wavelet network for identifying stator resistance on-line is *** wavelet transform can accurately detect and localize signal characteristic in time-frequency domains,where the real-time stator resistance variation can be *** wavelet network provides a sufficient structure that guarantees the approximation *** with neural network,the wavelet network has four merits: self-construction network,partial retrieval of approximated function,fast convergence and escaping local minima,improving dynamic performance of direct torque control in low *** input nodes of wavelet network have two variables:one is stator current error,and the other is variance ratio of stator current error. The output node of wavelet network is stator resistance *** improved least squares algorithm is used to complete the network parameter initialization,which would have good convergence *** simulation results prove that the proposed method can efficiently reduce the torque ripple and current ripple,optimizing the inverter control strategy.

关键词： Induction motor dynamic performance wavelet network stator current stator identification parameter initialization low speed

Application of Signal Processing and Neural Network for Transient Waveform Recognition in Power System

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Application of Signal Processing and Neural Network for Tran...

2010 Chinese Control and Decision Conference

作者： shanlin kang~1,huanzhen zhang~1,yuzhe kang~2 1.hebei university of engineering,handan 05603.,china 2.beijing university of chemical technology,beijing 100029,china

＜正＞The electric utilities and end users of power system network have become more concerned about power quality issues due to technical and financial consequences that have resulted from electric power quality *** power quality monitoring technology has an effective on analyzing power quality related *** paper presents a novel study combining wavelet transform with pattern recognition technique to investigate voltage stability using for power quality *** wavelet transformation possesses capabilities of time and frequency domain localizations,achieving a great impetus in signal singularity *** statistics-based denoising method is designed to filter the random noise and impulse noise in power quality disturbance signals,incorporating the advantages of wavelet transform to extract signal feature meanwhile restraining various *** wavelet decomposition coefficients as feature vector of neural network are presented for extracting disturbance *** neural network provides a means of determining a degree of belief for each identified disturbance *** performance of the proposed approach is studied and a proper combination of wavelet transformation and neural network is identified.

关键词： Power system power quality monitoring wavelet transform signal denoising voltage stability feature vector

Simulation Analysis of Time-frequency based on Waveform Detection Technique for Power Quality Application

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Simulation Analysis of Time-frequency based on Waveform Dete...

2010 Chinese Control and Decision Conference

作者： shanlin kang~1,huanzhen zhang~1,yuzhe kang~2 1.hebei university of engineering,handan 05603.,china 2.beijing university of chemical technology,beijing 100029,china

＜正＞The automatic detection and classification of power quality disturbances has become a sigmficant issue in modern power industry,because of electric load sensitive to power transient *** paper presents a novel approach for detection and location of power quality disturbances based on wavelet transform and artificial neural *** wavelet transform is the projection of a discrete signal into two spaces:the approximation space and a series of detail *** implementation of the projection operation is done by discrete-time subband decomposition of input signals using filtering followed by *** wavelet transform is utilized to produce representative feature vectors that can accurately capture the characteristics of power quality disturbance,exploring feature extraction of disturbance signal to obtain dynamic parameters. The feature vector obtained from wavelet decomposition coefficients are utilized as input variables of neural network for pattern classification of power quality *** training algorithm shows great potential for automatic power quality monitoring technique with on-line detection and classification *** combination performance of wavelet transform with neural network is evaluated by simulation results, approving that the proposed method is effective for analysis of power quality signal.

关键词： Automatic detection and classification power quality disturbance feature vector artificial neural network dynamic parameter

Application of Wavelet Transform for Fault Pattern Recognition and Analysis of Power System Generator

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Application of Wavelet Transform for Fault Pattern Recogniti...

2009中国控制与决策会议

作者： kang shanlin~1,kang yuzhe~2,zhang huanzhen~1 1.hebei university of engineering,handan 05603.,china 2.beijing university of chemical technology,beijing 100029,china

＜正＞The high-capacity turbine-generator set has been widely used in power system as an important power supply and its operating condition is under mal-condition,so keeping it running in safety status is essential.A novel approach using wavelet neural network is proposed for transient vibration signal processing and fault pattern *** signal acquiring,the occurrence of transient signal makes the waveform nonstationary,especially during the start-up of *** means of wavelet transform,the transient signal can be decomposed into series of wavelet subspaces,each of which covers a specific octave frequency band in *** effective eigenvectors are acquired by orthonormal wavelet transform based on multi-resolution analysis,which is called feature *** feature vectors are applied to the neural network for training and *** neural network has three advantageous:data driven learning,local interconnections and good convergence *** improved training algorithm based on recursive orthogonal least squares is utilized to accomplish network parameter *** means of proper samples selection and network parameter adjustment,the fault pattern can be determined from the network output *** simulation results and applications show that the proposed method is effective and the diagnosis result is correct.

关键词： Turbo-generator set wavelet transform neural network feature extraction fault diagnosis pattern recognition