publications
I see no reason to address the - in any case erroneous - comments of your anonymous expert. — Albert Einstein
other
2022
- The surface-topography challenge: Problem definitionTevis D B Jacobs, Nathaniel Miller, Martin H Müser, and Lars PastewkaarXiv:2206.13384 (2022)
We present to the community a surface-definition problem, whose solution we consider to be critical for the proper description of contacts between nominally flat surfaces. In 2015, Müser and Dapp issued the Contact Mechanics Challenge, which provided complete topography data for a fictional surface and asked theorists and modelers to compute the expected contact parameters for such a surface. This effort was a success, but exposed one glaring flaw in the community’s understanding of the nature of contact: these models require as input a complete description of surface topography, which is rarely or never available for real-world surfaces. The present challenge is to experimentalists: we will send you samples of two materials (one smoother and one rougher); you determine the surface topography of these materials. We call on you to measure such surfaces however you wish, using contact-based techniques, light scattering, microscopy, or other techniques. Examples of quantities of interest are: root-mean-square (RMS) parameters; the power spectral density (PSD); or the autocorrelation function (ACF). For the material, we have chosen chromium nitride, a wear- and corrosion-resistant coating used in industrial applications including automotive components, cutting tools, and die-casting. To participate, simply go to: https://contact.engineering/challenge to provide your shipping address and other information, then samples will be shipped out to you. The only requirement of participation is that your raw topography measurements are deposited on the free contact.engineering web app to facilitate data sharing. The purpose of this challenge is for our community to move towards: (a) better agreement on how to describe the multi-scale topography of experimental surfaces; and (b) better understanding of how to apply the well-developed models and theories to real-world surfaces.