TY - JOUR
T1 - Finite element modeling of multiple water droplets impact onto a rough surface
T2 - Re-assessing Sa and surface wavelength
AU - Xie, J.
AU - Chen, P.
AU - Rittel, D.
N1 - Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/10
Y1 - 2020/10
N2 - 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 λ. 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 Sa0 and λ0. An analytical formula was derived by simplifying a representative single valley as a half ellipsoid, emphasizing the more influential role of the wavelength λ compared to Sa in determining the effective surface area for cell adhesion.
AB - 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 λ. 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 Sa0 and λ0. An analytical formula was derived by simplifying a representative single valley as a half ellipsoid, emphasizing the more influential role of the wavelength λ compared to Sa in determining the effective surface area for cell adhesion.
KW - Effective surface area
KW - Implants
KW - Rough surface parameters
KW - Waterjet peening
UR - http://www.scopus.com/inward/record.url?scp=85085614660&partnerID=8YFLogxK
U2 - 10.1016/j.jmbbm.2020.103816
DO - 10.1016/j.jmbbm.2020.103816
M3 - Article
C2 - 32501219
AN - SCOPUS:85085614660
SN - 1751-6161
VL - 110
JO - Journal of the Mechanical Behavior of Biomedical Materials
JF - Journal of the Mechanical Behavior of Biomedical Materials
M1 - 103816
ER -