Please use this identifier to cite or link to this item: doi:10.22028/D291-34088
Title: Tactile perception of randomly rough surfaces
Author(s): Sahli, Riad
Prot, Aubin
Wang, Anle
Müser, Martin H.
Piovarči, Michal
Didyk, Piotr
Bennewitz, Roland
Language: English
Title: Scientific Reports
Volume: 10
Issue: 1
Publisher/Platform: Springer Nature
Year of Publication: 2020
Free key words: Materials science
Mathematics and computing
Physics
Physiology
Psychology
DDC notations: 500 Science
Publikation type: Journal Article
Abstract: Most everyday surfaces are randomly rough and self-similar on sufficiently small scales. We investigated the tactile perception of randomly rough surfaces using 3D-printed samples, where the topographic structure and the statistical properties of scale-dependent roughness were varied independently. We found that the tactile perception of similarity between surfaces was dominated by the statistical micro-scale roughness rather than by their topographic resemblance. Participants were able to notice differences in the Hurst roughness exponent of 0.2, or a difference in surface curvature of 0.8 mm−1 for surfaces with curvatures between 1 and 3 mm−1. In contrast, visual perception of similarity between color-coded images of the surface height was dominated by their topographic resemblance. We conclude that vibration cues from roughness at the length scale of the finger ridge distance distract the participants from including the topography into the judgement of similarity. The interaction between surface asperities and fingertip skin led to higher friction for higher micro-scale roughness. Individual friction data allowed us to construct a psychometric curve which relates similarity decisions to differences in friction. Participants noticed differences in the friction coefficient as small as 0.035 for samples with friction coefficients between 0.34 and 0.45.
DOI of the first publication: 10.1038/s41598-020-72890-y
Link to this record: urn:nbn:de:bsz:291--ds-340886
hdl:20.500.11880/31349
http://dx.doi.org/10.22028/D291-34088
ISSN: 2045-2322
Date of registration: 21-May-2021
Faculty: NT - Naturwissenschaftlich- Technische Fakultät
Department: NT - Materialwissenschaft und Werkstofftechnik
NT - Physik
Professorship: NT - Prof. Dr. Martin Müser
NT - Keiner Professur zugeordnet
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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