Electron irradiation-induced defects in InP pre-annealed at high temperature

Electron irradiation-induced deep level defects have been studied in InP which has undergone high-temperature annealing in phosphorus and iron phosphide ambients, respectively. In contrast to a high concentration of irradiation-induced defects in as-grown and phosphorus ambient annealed InP, InP pre-annealed in iron phosphide ambient has a very low concentration of defects. The phenomenon has been explained in terms of a faster recombination of radiation-induced defects in the annealed InP. The radiation-induced defects in the annealed InP have been compared and studied. (c) 2006 Elsevier Ltd. All rights reserved.

Growth of high quality semi-insulating InP single crystal by suppression of compensation defects

Deep level defects in as-grown and annealed SI-InP samples were investigated by thermally stimulated current spectroscopy. Correlations between electrical property, compensation ratio, thermal stability and deep defect concentration in SI-InP were revealed. An optimized crystal growth condition for high quality SI-InP was demonstrated based on the experimental results.

Circuit design and simulation of a CMOS-based preamplifier for brain neural signals

A novel CMOS-based preamplifier for amplifying brain neural signal obtained by scalp electrodes in brain-computer interface (BCI) is presented in this paper. By means of constructing effective equivalent input circuit structure of the preamplifier, two capacitors of 5 pF are included to realize the DC suppression compared to conventional preamplifiers. Then this preamplifier is designed and simulated using the standard 0.6 mu m MOS process technology model parameters with a supply voltage of 5 volts. With differential input structures adopted, simulation results of the preamplifier show that the input impedance amounts to more than 2 Gohm with brain neural signal frequency of 0.5 Hz-100 Hz. The equivalent input noise voltage is 18 nV/Hz(1/2). The common mode rejection ratio (CMRR) of 112 dB and the open-loop differential gain of 90 dB are achieved.

Improvement of the electrical property of semi-insulating InP by suppression of compensation defects

Semi-insulating (SI) InP obtained by iron phosphide ambient annealing has very low concentration of deep level defects and better electrical property than SI-InP annealed in phosphorus ambient. The defect suppression phenomenon correlates with Fe diffusion and substitution in the annealing process. Analysis of the experimental result suggests that a high activation ratio of incorporated Fe in InP has an effect of defect suppression in Fe-doped and Fe-diffused SI-InP.

STUDY OF MICROSTRUCTURE AND DEFECTS IN HYDROGENATED MICROCRYSTALLINE SILICON FILMS

Microcrystalline silicon films were deposited by very high frequency (VHF) plasma-enhanced chemical vapor deposition (PECVD) with different hydrogen dilution. The microstructure of these films was investigated using Raman spectroscopy and infrared absorption (IR) spectra. The crystalline, amorphous, and grain boundary volume fractions X-c, X-a and X-gb were estimated from Raman measurements. An interface structure factor (R-if) is proposed to characterize the grain boundary volume fractions in IR spectroscopy. The density of states (DOS) of the microcrystalline crystalline silicon films were studied by phase-shift analysis of modulated photocurrent (MPC) and photoconductivity spectroscopy. It was observed that DOS increases with increasing grain boundary volume fractions, while the values of electron mobility-lifetime product mu T-e(e) disease.

on string languages generated by spiking neural p systems

We continue the study of spiking neural P systems by considering these computing devices as binary string generators: the set of spike trains of halting computations of a given system constitutes the language generated by that system. Although the "direct" generative capacity of spiking neural P systems is rather restricted (some very simple languages cannot be generated in this framework), regular languages are inverse-morphic images of languages of finite spiking neural P systems, and recursively enumerable languages are projections of inverse-morphic images of languages generated by spiking neural P systems.

Experimental investigation on TBAB clathrate hydrate slurry flows in a horizontal tube: Forced convective heat transfer behaviors

Tetra-n-butyl-ammonium bromide (TBAB) clathrate hydrate slurry (CHS) is one kind of secondary refrigerants, which is promising to be applied into air-conditioning or latent-heat transportation systems as a thermal storage or cold carrying medium for energy saving. It is a solid-liquid two phase mixture which is easy to produce and has high latent heat and good fluidity. In this paper, the heat transfer characteristics of TBAB slurry were investigated in a horizontal stainless steel tube under different solid mass fractions and flow velocities with constant heat flux. One velocity region of weakened heat transfer was found. Moreover, TBAB CHS was treated as a kind of Bingham fluids, and the influences of the solid particles, flow velocity and types of flow on the forced convective heat transfer coefficients of TBAB CHS were investigated. At last, criterial correlations of Nusselt number for laminar and turbulent flows in the form of power function were summarized, and the error with experimental results was within 20%.

Kinetic Model Study on Enzymatic Hydrolysis of Cellulose Using Artificial Neural Networks

Enzymatic hydrolysis of cellulose was highly complex because of the unclear enzymatic mechanism and many factors that affect the heterogeneous system. Therefore, it is difficult to build a theoretical model to study cellulose hydrolysis by cellulase. Artificial neural network (ANN) was used to simulate and predict this enzymatic reaction and compared with the response surface model (RSM). The independent variables were cellulase amount X-1, substrate concentration X-2, and reaction time X-3, and the response variables were reducing sugar concentration Y-1 and transformation rate of the raw material Y-2. The experimental results showed that ANN was much more suitable for studying the kinetics of the enzymatic hydrolysis than RSM. During the simulation process, relative errors produced by the ANN model were apparently smaller than that by RSM except one and the central experimental points. During the prediction process, values produced by the ANN model were much closer to the experimental values than that produced by RSM. These showed that ANN is a persuasive tool that can be used for studying the kinetics of cellulose hydrolysis catalyzed by cellulase.