Theoretical analysis and experimental study of the space-charge-screening effect in uni-traveling-carrier photodiode

A new optimized structure of an UTC (uni-traveling-carrier) photodiode is developed and epitaxied by metal-organic chemical vapor deposition. We fabricated a UTC photodiode of 30 mu m in diameter. Theoretical simulation based on drift-diffusion model was used to analyze the space-charge-screening effect in UTC photodiode primarily in two aspects: the carrier concentrations and the space electric field. The simulation results were generally in agreement with the experimental data.

Space growth studies of Ce-doped Bi12SiO20 single crystal

Ce-doped Bi12SiO20 (BSO) single crystal was grown on board of the Chinese Spacecraft-Shenzhou No. 3. A cylindrical crystal, 10 mm in diameter and 40 mm in length, was obtained. The morphology of crystals is significantly different for ground- and space-grown portions. The space- and ground-grown crystals have been characterized by Cc concentration distribution, X-ray rocking curve absorption spectrum and micro-Raman spectrum. The results show that the quality of Ce-doped BSO crystal grown in space is more homogeneous and more perfect than that of ground grown one. (C) 2004 Published by Elsevier B.V.

Growth of CeO2 : Bi12SiO20 crystals in multi-position furnace(II) - Space growth experiment

Ce-doped Bi12SiO20 single crystal with size of phi10mm x 40mm was successfully grown in space on board of the spacecraft Shenzhou No.3. The surface morphology of space-grown crystal is different from that of ground-grown crystal The space- and ground-grown crystals were measured by X-ray rocking curves, absorption spectra and micro-Raman spectra. The results show that the quality of Ce-deped crystal grown in space is better than that of the ground-grown one. The effect of doping on optical properties of BSO grown in space is evident in comparison with the ground-grown crystal.

Geometrical learning, descriptive geometry, and biomimetic pattern recognition

Studies on learning problems from geometry perspective have attracted an ever increasing attention in machine learning, leaded by achievements on information geometry. This paper proposes a different geometrical learning from the perspective of high-dimensional descriptive geometry. Geometrical properties of high-dimensional structures underlying a set of samples are learned via successive projections from the higher dimension to the lower dimension until two-dimensional Euclidean plane, under guidance of the established properties and theorems in high-dimensional descriptive geometry. Specifically, we introduce a hyper sausage like geometry shape for learning samples and provides a geometrical learning algorithm for specifying the hyper sausage shapes, which is then applied to biomimetic pattern recognition. Experimental results are presented to show that the proposed approach outperforms three types of support vector machines with either a three degree polynomial kernel or a radial basis function kernel, especially in the cases of high-dimensional samples of a finite size. (c) 2005 Elsevier B.V. All rights reserved.

Iris recognition algorithm based on point covering of high-dimensional space and neural network

In this paper, we constructed a Iris recognition algorithm based on point covering of high-dimensional space and Multi-weighted neuron of point covering of high-dimensional space, and proposed a new method for iris recognition based on point covering theory of high-dimensional space. In this method, irises are trained as "cognition" one class by one class, and it doesn't influence the original recognition knowledge for samples of the new added class. The results of experiments show the rejection rate is 98.9%, the correct cognition rate and the error rate are 95.71% and 3.5% respectively. The experimental results demonstrate that the rejection rate of test samples excluded in the training samples class is very high. It proves the proposed method for iris recognition is effective.

Space-charge-limited currents in GaN Schottky diodes

Unusual dark current voltage (I-V) characteristics were observed in GaN Schottky diodes. I-V characteristics of the GaN Schottky diodes were measured down to the magnitude of 10(-14) A. Although these Schottky diodes were clearly rectifying, their I-V characteristics were non-ideal which can be judged from the non-linearity in the semi-logarithmic plots. Careful analysis of the forward bias I-V characteristics on log-log scale indicates space-charge-limited current (SCLC) conduction dominates the current transport in these GaN Schottky diodes. The concentration of the deep trapping centers was estimated to be higher than 10(15) cm(-3). In the deep level transient spectra (DLTS) measurements for the GaN Schottky diodes, deep defect levels around 0.20 eV below the bottom of the conduction band were identified, which may act as the trapping centers. The concentration of the deep centers obtained from the DLTS data is about 5 x 10(15) cm(-3). SCLC measurements may be used to probe the properties of deep levels in wide bandgap GaN-AlGaN compound semiconductors, as is the case with insulators in the presence of trapping centers. (c) 2005 Elsevier Ltd. All rights reserved.