Quantitative characterization of surface topography using spectral analysis Article Swipe
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1088/2051-672x/aa51f8
· OA: W2470121600
Roughness determines many functional properties of surfaces, such as\nadhesion, friction, and (thermal and electrical) contact conductance. Recent\nanalytical models and simulations enable quantitative prediction of these\nproperties from knowledge of the power spectral density (PSD) of the surface\ntopography. The utility of the PSD is that it contains statistical information\nthat is unbiased by the particular scan size and pixel resolution chosen by the\nresearcher. In this article, we first review the mathematical definition of the\nPSD, including the one- and two-dimensional cases, and common variations of\neach. We then discuss strategies for reconstructing an accurate PSD of a\nsurface using topography measurements at different size scales. Finally, we\ndiscuss detecting and mitigating artifacts at the smallest scales, and\ncomputing upper/lower bounds on functional properties obtained from models. We\naccompany our discussion with virtual measurements on computer-generated\nsurfaces. This discussion summarizes how to analyze topography measurements to\nreconstruct a reliable PSD. Analytical models demonstrate the potential for\ntuning functional properties by rationally tailoring surface topography -\nhowever, this potential can only be achieved through the accurate, quantitative\nreconstruction of the power spectral density of real-world surfaces.\n
