RESUMEN
BACKGROUND: In the previous three papers, the authors sought to conduct a thorough analysis of the feasibility for the use of zirconia in inlay supported, fixed partial dentures via finite element analysis (FEA). Correlating the response of the numerical model against the experimental model has never been satisfactorily performed for an anatomically accurate ceramic bridge; such validation is crucial if the results from the FEA are to be confidently relied upon. Part 4 of this series is a detailed fractographic analysis of the zirconia bridge that was the model for the experimental validation, performed in order to confirm the fracture origin/s and fracture trajectory as predicted from the FEA. METHODS: Established fractographic techniques involving optical examination followed by examination with scanning electron microscopy were conducted. The porous, granular surface of zirconia (both partially and fully sintered) does not lend itself to easy surface analysis but the classic fractographic signs (hackle lines, wake hackle lines and compression curl) are present. Use of linear fracture elastic mechanics allowed the calculation of theoretical critical flaw size and a comparison to two defects or inclusions found at the primary origin of fracture. RESULTS: Excellent agreement between the fracture sites and paths of travel as predicted in the numerical analysis exist with fractographic analysis. Furthermore, the calculated critical flaw size of 30 µm to 40 µm equates very well with defects seen at the general vicinity of the primary fracture origin and the general observed size of critical flaws in machined ceramics which range between 20 µm to 50 µm, thus providing further confirmation. CONCLUSIONS: The fractographic analysis detailed in this study provides validation of the 'zones of failure' as predicted in our FEA. Additionally, the excellent correlation between the calculated critical flaw size and the defects observed at the primary fracture site demonstrates that field of experimental mechanics is a powerful predictive tool.