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Updated: May 7, 2026

Quasistatic Mechanical Testing for Computer-Aided Design and Manufacturing Occlusal Veneers Cemented to Milled Dentin Analog Material
Published on: December 20, 2024
Fracture behavior of zirconia implant abutments is influenced by superstructure-geometry
Frank P Nothdurft1, Konrad Neumann, Andreas W Knauber
1Department of Prosthetic Dentistry and Dental Materials Sciences, Dental School and Clinics, Saarland University, Homburg, Saar, Germany, frank.nothdurft@uks.eu.
Objectives:
The purpose of this in vitro study was to evaluate the influence of the superstructure-geometry on the fracture behavior of zirconia abutments (Compartis, DeguDent GmbH, Hanau, G).
Materials And Methods:
Four different groups (n = 8) representing anterior single crown replacement were prepared. In groups 1 and 2, the implants were restored with customized all-ceramic abutments and anatomically shaped crowns (chromium cobalt alloy). Groups 3 and 4 received crowns with a geometry according to the international standard ISO 14801 (dynamic fatigue test for endosseous dental implants) with a spherical contact area. Groups 2 and 4 were subjected to mechanical aging in a chewing simulator (50 N × 1,200,000 cycles). Static loading until fracture was performed using a universal testing device at an angle of 30° to the implant axis. Fracture patterns were analyzed using SEM.
Results:
In group 2, only one specimen survived mechanical aging. In group 4, one specimen fractured during the chewing simulation. Groups 1 and 2 showed significantly lower load-bearing capacity than groups 3 and 4. Artificial aging did not influence the fracture resistance. The SEM analysis revealed fatigue-related fracture patterns in those specimens, which failed during artificial aging.
Conclusions:
Drawing conclusions from ISO testing concerning clinical performance appears to be critical as anatomic superstructure geometries induce different fracture behaviors.
Clinical Relevance:
ISO testing of zirconia abutments should be accompanied by load-bearing capacity testing under simulated clinical conditions to predict clinical performance.
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