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Characterization of Carbon-Based Materials Assisted by Time Series Modeling

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Silicon Carbide (SiC) samples were characterized by the means of THz radiation spectroscopy. The subsequent results were processed by computational methods based on prediction (time series analysis). The library-based determination of parameters allowed allocating specific defects (such as point defects, dislocations, nonuniformities, etc.) and screening the noise (or any unwanted signals). In addition, the location of different layers in a semiconductor crystal may be determined. As a result, signal processing time was reduced by approximately 50%. Also, the improved characterization technique allowed presentation of the results in the form more understandable to an analyst without extensive experience in THz materials characterization. This feature, along with the mathematical presentation of the results makes it possible to bring the considered materials characterization closer to industrial applications, ultimately rendering the characterization process fully automatic. Graphs are given showing the attenuation of parasitic interference, background noise and unnecessary information. The typical attenuation of the unwanted signal was ∼7 dB. The described method may be applied to any semiconductor material.
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Document Type: Short Communication

Publication date: June 1, 2010

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  • Nanoscience and Nanotechnology Letters (NNL) is a multidisciplinary peer-reviewed journal consolidating nanoscale research activities in all disciplines of science, engineering and medicine into a single and unique reference source. NNL provides the means for scientists, engineers, medical experts and technocrats to publish original short research articles as communications/letters of important new scientific and technological findings, encompassing the fundamental and applied research in all disciplines of the physical sciences, engineering and medicine.
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