Fracture Strength of Zirconia Implants after Artificial Aging
Bibliographic record
Abstract
BACKGROUND: Zirconia (ZrO(2)) might be an alternative material to titanium (Ti) for dental implant fabrication. However, no data are available on the fracture strength of one-piece ZrO(2) oral implants. PURPOSE: The objective of this study was to evaluate the fracture strength of ZrO(2) implants after exposure to the artificial mouth. MATERIALS AND METHODS: One hundred twenty ZrO(2) and Ti implants were used. The Ti implants were divided into two control groups (A and B). ZrO(2) implants manufactured from yttria-stabilized tetragonal ZrO(2) polycrystal (Y-TZP) in group C, from Y-TZP dotted with alumina (Y-TZP-A) in group D, and from Y-TZP-A with a modified surface in groups E and F were used. In group F, the implant heads were prepared, and in group G, the implants were restored with ZrO(2) crowns. Each group included 16 samples with the exception of group D, which included 24 samples. A subgroup of each implant type (eight implants) was subjected to thermomechanical cycling in a chewing simulator prior to fracture testing. Test specimens were then loaded until a fracture occurred. RESULTS: Seven of the 120 samples failed in the chewing simulator. ZrO(2) implant fracture occurred at 725 to 850 N when the implants were not prepared, and at 539 to 607 N when prepared. The samples in group A fractured at the level of the abutment screw. All ZrO(2) implants fractured at the level of the Technovit resin (Heraeus Kulzer GmbH & Co., Wehrheim, Germany). No fracture of the ZrO(2) crowns in group G was observed. CONCLUSION: Mean fracture strength values obtained were all within the limits of clinical acceptance. However, implant preparation had a statistically significant negative influence on the implant fracture strength. Long-term clinical data are necessary before one-piece ZrO(2) implants can be recommended for daily practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".