Micro and nano scale statistical properties of randomly rough engineering surfaces and their tribological properties
Surface roughness is a key factor in determining successful component performance in modern nanotechnology, precision engineering and tribological applications.
This project is advertised as part of the EPSRC Doctoral Training Partnership. It is currently not available to self-funded applicants. Find out more information about the DTP including how to apply.
However, currently there is no clear understanding how roughness affects dry friction, adhesion, and contact between rough surfaces. The current statistical approaches to description of surface roughness are rather primitive and there is a need in critical re-examination of the current statistical approaches . The objective of the proposed cross-disciplinary research is threefold: (i) to develop the stochastic versions of the multiscale and multilevel models of rough surfaces at nano/microscales; (ii) to perform multiscale experimental studies of engineering surfaces at the scales using state-of-the-art experimental methods including scanning force microscopy and stylus profilometery; and (iii) to test the developed models in application to models of dry friction and adhesion between the surfaces. The study will involve a combination of novel statistical approaches to the experimental data obtained and applications of modern methods of nanomechanics and numerical simulations of the developed models. The proposed research will enable understanding of the parameters that are of importance for adhesion, contact interactions and friction between rough engineering surfaces including surfaces of bulk engineering materials and coatings in various practical applications.
 Borodich FM, Pepelyshev A, Savencu O, Statistical approaches to description of rough engineering surfaces at nano and microscalese, Tribology International , (2016), 103, 197-207.
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