Design and simulation of charge sensitive preamplifier with CMOS FET implemented as feedback capacitor C-fp

In this paper, to design a new preamplifier for optimum performances with charged-particle or heavy-ion detectors, the CMOS FET is implemented as a feedback capacitor C-fp, so that the entire system should be built only with MOSFET. This work is a revolution design because to realize an ASIC for a preamplifier circuit, the capacitor will also be included. We succeed after a simulation to maintain a rise time less than 3 ns, the output resistance less than 94 Omega and the linearity almost good.

用于粒子探测器的CMOS FET采样保持电路的设计与仿真(英文)；Design and Simulation of Track/Hold Circuit with CMOS FET for Particle Detector

介绍了一个峰保持电路。该电路适用于silicon strip,Si(Li),CdZn Te and CsI等探测器,实现采样-保持功能。已成功进行了基于CMOSFET的采样-保持电路的设计和仿真,通过使用Proteus的PSPICE仿真器和BSIMV3.3模型参数完成了电路性能的仿真。同时,实现了采样时间可在60ns到4.44s范围内进行选择,该电路具有较好的线性。

Quench Protection Design and Simulation of a 7 Tesla Superconducting Magnet

A 7 Tesla superconducting magnet with a clear warm bore of 156 mm in diameter has been developed for Lanzhou Penning Trap at the Institute of Modern Physics for high precision mass measurement. The magnet is comprised of 9 solenoid coils and operates in persistent mode with a total energy of 2.3 MJ. Due to the considerable amount of energy stored during persistent mode operation, the quench protection system is very important when designing and operating the magnet. A passive protection system based on a subdivided scheme is adopted to protect the superconducting magnet from damage caused by quenching. Cold diodes and resistors are put across the subdivision to reduce both the voltage and temperature hot spots. Computational simulations have been carried in Opera-quench. The designed quench protection circuit and the finite element method model for quench simulations are described; the time changing of temperature, voltage and current decay during the quench process is also analysed.

Retention modeling and simultaneous optimization of pH value and gradient steepness in RP-HPLC using feed-forward neural networks

A novel approach is proposed for the simultaneous optimization of mobile phase pH and gradient steepness in RP-HPLC using artificial neural networks. By presetting the initial and final concentration of the organic solvent, a limited number of experiments with different gradient time and pH value of mobile phase are arranged in the two-dimensional space of mobile phase parameters. The retention behavior of each solute is modeled using an individual artificial neural network. An "early stopping" strategy is adopted to ensure the predicting capability of neural networks. The trained neural networks can be used to predict the retention time of solutes under arbitrary mobile phase conditions in the optimization region. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for amino acids derivatised by a new fluorescent reagent.

Modeling and optimization for separation of ionic solutes in pressurized flow capillary electrochromatography

By manipulation of applied pressure or voltage, pressurized flow capillary electrochromatography (P-CEC) permits unique control of selectivity for ionic solutes. A simple mathematical model has been developed to describe the quantitative relationship between the electrochromatographic retention factor (k(*)) of charged solutes and the applied voltage and pressure. The validity of the model was verified experimentally with hydrophilic interaction mode CEC (HI-CEC). On the basis of the model developed, it was found that the value of k(*) could be predicted accurately using only a limited number of data points from the initial experiments at different voltages or pressures. Correlation between the experimentally measured and calculated k(*) was excellent, with a correlation coefficient greater than 0.999. Optimization for the separation of peptides by P-CEC was also performed successfully on the basis of the proposed model.

Retention modeling and optimization of pH value and solvent composition in HPLC using back-propagation neural networks and uniform design

A novel method for the optimization of pH value and composition of mobile phase in HPLC using artificial neural networks and uniform design is proposed. As the first step. seven initial experiments were arranged and run according to uniform design. Then the retention behavior of the solutes is modeled using back-propagation neural networks. A trial method is used to ensure the predicting capability of neural networks. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for both basic and acidic samples.

Analysis of spatio-temporal dynamic pattern and driving forces of urban land in China in 1990s using TM images and GIS

China has witnessed fast urban growth in the recent decade. This study analyzes spatio-temporal characteristics of urban expansion in China using satellite images and regionalization methods. Landsat TM images at three time periods, 1990/1991, 1995/1996, and 1999/2000, are interpreted to get 1:100000 vector land use datasets. The study calculates the urban land percentage and urban land expansion index of every 1 km(2) cell throughout China. The study divides China into 27 urban regions to conceive dynamic patterns of urban land changes. Urban development was achieving momentum in the western region, expanding more noticeably than in the previous five years, and seeing an increased growth percentage. Land use dynamic changes reflect the strong impacts of economic growth environments and macro-urban development policies. The paper helps to distinguish the influences of newly market-oriented forces from traditional administrative controls on China's urban expansion. (c) 2005 Elsevier Ltd. All rights reserved.

Preparation and simulation of an additional catalyst layer for direct methanol fuel cell

An additional anode catalyst layer with PtRu/C was hot pressed between two Nafion (R) 112 membranes and a conventional direct methanol fuel cell (DMFC) cathode/membrane/anode assembly with the above membranes as separator was fabricated. The additional catalyst layer formed an assistant cell with the cathode to prevent methanol crossover. A simple one-dimensional mathematical model was presented to describe the performance of this new type of membrane electrode assembly system. As seen from both experimental result and model analysis, the additional catalyst layer can not only effectively prevent the methanol crossover, but also generate electrical power with the crossover methanol. The percentage of output power of the assistant cell to the total power analyzed by the model is about 40% under usual condition, which is much higher than that from experimental result, indicating the potential of the development in the DMFC designing. It was also discovered that the electrical power generated from the assistant cell with crossover methanol could take higher percentage in total electrical power when the main DMFC current density became lower.

Dynamic mechanical and thermal properties of plasticized poly(lactic acid)

The blends of low molecular weight triacetin (TAC) and oligomeric poly(1,3-butylene glycol adipate) (PBGA) were used as multiple plasticizers to lubricate poly(lactic acid) (PLA) in this study. The thermal and mechanical properties of plasticized polymers were investigated by means of dynamic mechanical analysis and differential scanning calorimetry. Atomic force microscopy (AFM) was used to analyze the morphologies of the blends. Multiple plasticizers were effective in lowering the glass transition temperature (T-g) and the melting temperature (T-m) of PLA. Moreover, crystallinity of PLA increased with increasing the con-tent of multiple plasticizers. Tensile strength of the blends decreased following the increasing of the plasticizers, but increased in elongation at break. AFM topographic images showed that the multiple plasticizers dispersed between interfibrillar regions. Moreover, the fibrillar crystallite formed the quasicrosslinkings, which is another cause for the increase in elongation at break.

DYNAMIC SCALING AND FRACTAL BEHAVIOR OF SPINODAL PHASE-SEPARATION IN POLYMER MIXTURES OF POLY(METHYL METHACRYLATE) WITH POLY(STYRENE-CO-ACRYLONITRILE)

Dynamic scaling and fractal behaviour of spinodal phase separation is studied in a binary polymer mixture of poly(methyl methacrylate) (PMMA) and poly(styrene-co-acrylonitrile) (SAN). In the later stages of spinodal phase separation, a simple dynamic scaling law was found for the scattering function S(q,t):S(q,t) approximately q(m)-3S approximately (q/q(m)). The possibility of using fractal theory to describe the complex morphology of spinodal phase separation is discussed. In phase separation, morphology exhibits strong self-similarity. The two-dimensional image obtained by optical microscopy can be analysed within the framework of fractal concepts. The results give a fractal dimension of 1.64. This implies that the fractal structure may be the reason for the dynamic scaling behaviour of the structure function.