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2004
Conference Paper
Titel
Acoustic microscopy, brillouin scattering and laser-SAW technique for defect characterization in DLC films
Abstract
DLC films are beginning to find their way into industrial applications to prolong the life of machine components. Preliminary wear tests on nano-structured DLC coated samples demonstrated an appreciable improvement in pitting resistance and usable life. One of the key parameters that have great impact on the wear resistance of a material is its microstructure. The acoustic microscope was developed as a tool for studying internal microstructure of non-transparent solids and now it is widely used for detection of cracks and subsurface defects. Despite the expedient use of this NDE technique, quantitative characterization of the imaged defects is rarely completed because the theory describing image formation caused by subsurface defects is complicated1 and it requires knowledge of the material's elastic properties. In this article, we used scanning acoustic microscopy (Leitz ELSAM) to detect and analyze defects in thin chromium-alloyed DLC (Cr-DLC) films. Our main goal was to investigate the distribution of subsurface defects in Cr-DLC coatings deposited on a steel substrate where the thickness of the films varied from 2 to 3 mm. Two frequencies (200 MHz and 1 GHz) were used to detect and image the defects and for size determination. To locate the depth of the defects, acoustic images were taken at different defocus positions. Velocity of the Rayleigh wave was measured by surface Brillouin scattering and the elastic moduli of the coatings were evaluated by fitting the surface acoustic wave dispersion curve measured by a SAW-laser technique. Elastic moduli were then used in a model developed by Lobkis et al.1 to simulate the imaged subsurface defects obtained by acoustic microscopy. In this report we discuss the possibility of using this approach for characterization of subsurface defects that are located no deeper than one wavelength of the Rayleigh wave. Our study illustrates that a combination of low (200 MHz) and high (1 GHz) frequency images of the subsurface voids provide sufficient information to uniquely determine their distribution and location. Images at 200 MHz revealed a higher sensitivity to the subsurface voids although they did not provide accurate information about the size and location of the defects. Detection and identification of the defects at high frequency (1 GHz), as a rule, were more difficult; however, the high frequency images were useful for determining the size and position of the defects.