Based on psychophysical studies, we found that human subjects can succesfully distinguish between two silicon wafers that essentially differ in their surface energy alone. Subjects accurately determined whether a wafer was coated with a "hydrophobic", low-energy silane (FOTS), or a "hydrophilic", high-energy plasma treatment (SiOH). Despite the clear differences in friction coefficients, we do not always observe a difference in friction forces when the sliding was recreated using PDMS mock fingers (macroscopic scale). We find instead that particular conditions of velocity and mass are needed to recover a difference in friction force, and that patterned interfaces ("fingerprints") augment these differences across a wider set of conditions. We explain the frictional basis of this discriminability using an elastic, patterned, "rate-and-state" mathematical model. We present the results from our experiments in a novel, "discriminability matrix", which highlights conditions under which the two surfaces are distinguishable. The mathematical results corrobrate these findings, as well as recreating Schallamach waves and other slow frictional waves. These new findings could form the basis for a novel method to characterize surfaces for human perception.

Understanding fine textures in touch: The role of fingerprints in modulating sliding friction on surfaces and haptic devices

255th National Meeting (2018)

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