Abstract
Although 3D-printed porous dental implants may possess improved osseointegration potential, they must exhibit appropriate fatigue strength. Finite element analysis (FEA) has the potential to predict the fatigue life of implants and accelerate their development. This work aimed at developing and validating an FEA-based tool to predict the fatigue behavior of porous dental implants.
Test samples mimicking dental implants were designed as 4.5 mm-diameter cylinders with a fully porous section around bone level. Three porosity levels (50%, 60% and 70%) and two unit cell types (Schwarz Primitive (SP) and Schwarz W (SW)) were combined to generate six designs that were split between calibration (60SP, 70SP, 60SW, 70SW) and validation (50SP, 50SW) sets.
Twenty-eight samples per design were additively manufactured from titanium powder (Ti6Al4V). The samples were tested under bending compression loading (ISO 14801) monotonically (N=4/design) to determine ultimate load (Fult) (Instron 5866) and cyclically at six load levels between 50% and 10% of Fult (N=4/design/load level) (DYNA5dent). Failure force results were fitted to F/Fult = a(Nf)b (Eq1) with Nf being the number of cycles to failure, to identify parameters a and b. The endurance limit (Fe) was evaluated at Nf = 5M cycles. Finite element models were built to predict the yield load (Fyield) of each design. Combining a linear correlation between FEA-based Fyield and experimental Fult with equation Eq1 enabled FEA-based prediction of Fe.
For all designs, Fe was comprised between 10% (all four samples surviving) and 15% (at least one failure) of Fult. The FEA-based tool predicted Fe values of 11.7% and 12.0% of Fult for the validation sets of 50SP and 50SW, respectively. Thus, the developed FEA-based workflow could accurately predict endurance limit for different implant designs and therefore could be used in future to aid the development of novel porous implants.
Acknowledgements: This study was funded by EU's Horizon 2020 grant No. 953128 (I-SMarD). We gratefully acknowledge the expert advice of Prof. Philippe Zysset.
