Numerical Investigation of Thermal and Thermo-mechanical Effective Properties for Short Fibre Reinforced Composite

This study aims to investigate the thermal conductivity and the linear coefficient of thermal expansion for short fibre reinforced composites. The study combines numerical and statistical analyses in order to primarily examine the representative size and the effective properties of the volume element. Effects of various micromechanical parameters, such as fibre’s aspect ratio and fibre’s orientation, on the minimum representative size are discussed. The numerically acquired effective properties, obtained for the representative size, are presented and compared with analytical models.     

Robustness of nonlinear control systems with respect to unmodeleddynamics

In theory, it can be established that nonlinear control laws for linear or nonlinear plants can be used to meet strict performance requirements. The success of these control designs in practical situations will very much depend on whether they can still meet the expected performance characteristics in the presence of inevitable modeling errors. In this paper, we develop necessary and sufficient conditions for a general class of nonlinear control laws in the presence of high-frequency unmodeled dynamics, under which global signal boundedness or asymptotic stability is guaranteed. We show that a wide class of nonlinear control laws does not satisfy these conditions and therefore does not guarantee global stability in the presence of high-frequency unmodeled dynamics     

Hot-electron-induced degradation of front and back channels inpartially and fully depleted SIMOX MOSFETs

The characteristics of the front and back channels of 1-μm-long SIMOX MOSFETs were measured before and after various types of periods of hot-electron stress, and a comparison between the induced degradations was made. The back channel degrades much more severely than the front channel for both partially depleted and fully depleted devices. Fully depleted MOSFETs (140-nm-thick) are favorably contrasted with partially depleted ones (300-nm-thick) as to their vulnerability to hot-carrier-induced damage. Although defects are always located at and/or near the interface of the stressed channel, they may influence the properties of the opposite channel (via interface coupling) in fully depleted MOSFETs     

Interface characterization of fully depleted SOI MOSFETs by thedynamic transconductance technique

The dynamic transconductance technique of MOSFET interface characterization is adapted to fully depleted silicon-on-insulator (SOI) transistors and is used to measure the interface-state density energy profiles in several SIMOX (separation by implanted oxygen) transistors. By making measurements first with the current flowing through the channel under measurement and then through the opposite channel, much of the energy gap (from accumulation to well into weak inversion) can be probed. Remarkably high sensitivity is achieved by utilizing the imaginary part of the dynamic transconductance. Measured interface trap densities were in the region of ~10¹⁰-10¹¹ eV^-1-cm^-2     

Electron traps on high-temperature oxidized SIMOX buried oxides

Photo-injection was used to study the charge trapping properties of high-temperature oxidation (HITOX) SIMOX buried oxides (BOX), provided by two independent vendors. After electron injection, from a 5 eV mercury light source, the electron trapping per area for both HITOX material sources was found to be larger than their respective standard (control) separation by implantation of oxygen (SIMOX) structures. This increase has been attributed to the HITOX's process influence on the formation of the HITOX/BOX oxide     

Multi-platform data integration in microarray analysis

An increasing number of studies have profiled gene expressions in tumor specimens using distinct microarray platforms and analysis techniques. One challenging task is to develop robust statistical models in order to integrate multi-platform findings. We compare some methodologies on the field with respect to estrogen receptor (ER) status, and focus on a unified-among-platforms scale implemented by Shen et al. in 2004, which is based on a Bayesian mixture model. Under this scale, we study the ER intensity similarities between four breast cancer datasets derived from various platforms. We evaluate our results with an independent dataset in terms of ER sample classification, given the derived gene ER signatures of the integrated data. We found that integrated multi-platform gene signatures and fold-change variability similarities between different platform measurements can assist the statistical analysis of independent microarray datasets in terms of ER classification.