Finite element modeling of multiple water droplets impact onto a rough surface: Re-assessing Sa and surface wavelength.

Waterjet peening is a promising green technology for roughening the metallic surface of orthopedic and dental implants in order to promote osseointegration. The current conventional surface characterization is essentially based on the arithmetic mean height (Sa), without additional considerations, in particular the effective surface area. Yet, this parameter together with the surface energy, is determinant for the cell-implant interaction. The influence of waterjet peening on the surface topography is investigated numerically by generating 9 rough surfaces with different initial Sa and wavelength lambda. Among the selected topography descriptors, the maximum pit depth Sv might be more viable for characterizing the evolution of the rough surface compared to the other 3 roughness parameters, Sa, maximum peak height Sp and maximum height Sz. The Power Spectrum Density of peened surfaces increases overall, compared to the untreated surfaces irrespective of initial Sa(0) and lambda(0). An analytical formula was derived by simplifying a representative single valley as a half ellipsoid, emphasizing the more influential role of the wavelength lambda compared to Sa in determining the effective surface area for cell adhesion.