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Dataset associated with "Friction between soft contacts at nanoscale on uncoated and protein-coated surfaces"

Citation

Liamas, Evangelos and Connell, Simon D. and Zembyla, Morfo and Ettelaie, Rammile and Sarkar, Anwesha (2020) Dataset associated with "Friction between soft contacts at nanoscale on uncoated and protein-coated surfaces". University of Leeds. [Dataset] https://doi.org/10.5518/943

Dataset description

The understanding of friction on soft sliding biological surfaces at the nanoscale is poorly understood as hard interfaces are frequently used as model systems. Herein, we studied the influence of elastic modulus on the frictional properties of model surfaces at the nanoscale for the first time. We prepared model silicone-based elastomer surfaces with tuneable modulus ranging from hundreds of kPa to a few MPa, similar to those found in real biological surfaces, and employed atomic force microscopy to characterize their modulus, adhesion, and surface morphology. Consequently, we used friction force microscopy to investigate nanoscale friction in hard-soft and soft-soft contacts using spherical colloidal probes covered by adsorbed protein films. Unprecedented results from this study reveal that modulus of a surface can have a significant impact on the frictional properties of protein-coated surfaces with higher deformability leading to lower contact pressure and, consequently, decreased friction. These important results pave the way forward for designing new functional surfaces for serving as models of appropriate deformability to replicate the mechanical properties of the biological structures and processes for accurate friction measurements at nanoscale.

Divisions: Faculty of Engineering and Physical Sciences > School of Food Science and Nutrition
Related resources:
LocationType
http://eprints.whiterose.ac.uk/168933/Publication
https://doi.org/10.1039/D0NR06527GPublication
License: Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited: 16 Dec 2020 16:33
URI: https://archive.researchdata.leeds.ac.uk/id/eprint/792

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