Low-dimensional Friction Modelling with Considering Random Asperity Distributions

This paper presents a new model to study the friction between rough surfaces with random distribution of the asperities, taking into account the contact mechanics. The results obtained show that as the surface separation decreases, the normal and friction forces increase and the coefficient of friction decreases. This model predicts higher friction forces and coefficient of friction than the model based on the Hertzian contact model. The sensitivity of the coefficient of friction to material properties is investigated using two sets of material properties. Assuming that the standard deviation and the radius of the asperities are constant, the first set investigates the variation of the adhesion energy, length of Burgers vectors, and elastic modulus parameters for the base material silicon. In the second set, real materials such as silicon, Fe, Cu, Au, and Ag are studied in contact with a silicon substrate. The results show that the friction coefficient decreases with the increase of the adhesion energy and increases with the increase of the length of Burgers vectors and elastic modulus.