3-D Simulator of Laser Crystallization for Polycrystalline-Silicon Thin-Film Transistors
A 3-D simulator of laser crystallization for polycrystalline-silicon thin-film transistors has been developed. Random nucleation, crystal growth velocity, latent heat emission, and partial crystallization are modeled, and a 2-D algorithm is extended to a 3-D algorithm. The <formula formulatype="inline"><tex Notation="TeX">$\mu$</tex></formula>-Czochralski technique is analyzed using the 3-D simulator, and it is found that the grain size becomes large when the initial temperature is high after the laser irradiation.
Explosive crystallization processes in silicon
This paper deals with selfsustaining crystallization processes, the so-called explosive crystallization, in silicon produced by short temperature pulses. By this, crystalline Si layers can be generated on amorphous substrates, e.g. on SiO2, at which liquid and solid-state crystallization processes can take place.Emphasis will be given to the liquid-phase explosive crystallization processes. Here, the transformation of amorphous into crystalline silicon occurs through two coupled laterally moving interfaces, amorphous-liquid and liquid-crystalline.Using an experimental equipment existing of 3 synchronized lasers supplying the temperature pulse for the ignition, the spreading out and stopping of the laterally moving interfaces, in connection with time-resolved measurements of the reflectivity by a laser test beam, information about the characteristic parameters as the velocity of the process, the crystallized area and the course of the crystallization front will be obtained. The crystalline structure was investigated by optical and transmission-electron micrography.The main results are: the crystallization fronts move radially from the ignition point with a velocity of about 15 m/s, crystalline laminae grow preferentially in 〈110〉 direction over a distance of more than 100 μm, areas of some millimeters in diameter can be crystallized and the quality of the crystallized layers essentially depends on the “amorphousness” of the virgin layer and the preparation method.The experimental results are in good agreement with theoretical predictions.
Surface roughness monitoring by singular spectrum analysis of vibration signals
Abstract This study assessed two methods for enhanced surface roughness (Ra) monitoring based on the application of singular spectrum analysis (SSA) to vibrations signals generated in workpiece-cutting tool interaction in CNC finish turning operations i.e., the individual analysis of principal components (I-SSA), and the grouping analysis of correlated principal components (G-SSA). Singular spectrum analysis is a non-parametric technique of time series analysis that decomposes a signal into a set of independent additive time series referred to as principal components. A number of experiments with different cutting conditions were performed to assess surface roughness monitoring using both of these methods. The results show that singular spectrum analysis of vibration signal processing discriminated the frequency ranges effective for predicting surface roughness. Grouping analysis of correlated principal components (G-SSA) proved to be the most efficient method for monitoring surface roughness, with optimum prediction and reliability results at a lower analytical-computational cost. Finally, the results show that singular spectrum analysis is an ideal method for analyzing vibration signals applied to the on-line monitoring of surface roughness.