Biomechanical Behavior of Narrow Dental Implants Made with Aluminum- and Vanadium-Free Alloys: A Finite Element Analysis
Bibliographic record
Abstract
Titanium (Ti) alloys used for narrow dental implants usually contain aluminum (Al) and vanadium (V) for improved resistance. However, those elements are linked to possible cytotoxic effects. Thus, this study evaluated the biomechanical behavior of narrow dental implants made with Al- and V-free Ti alloys by the finite element method. A virtual model of a partially edentulous maxilla received single implants (diameter: 2.7 and 2.9 mm; length: 10 mm) at the upper lateral incisor area, with respective abutments and porcelain-fused-to-metal crowns. Simulations were performed for each implant diameter and the following eight alloys (and elastic moduli): (1) Ti-6Al-4V (control; 110 GPa), (2) Ti-35Nb-5Sn-6Mo-3Zr (85 GPa), (3) Ti-13Nb-13Zr (77 GPa), (4) Ti-15Zr (113 GPa), (5) Ti-8Fe-5Ta (120 GPa), (6) Ti-26.88Fe-4Ta (175 GPa), (7) TNTZ-2Fe-0.4O (107 GPa), and (8) TNTZ-2Fe-0.7O (109 GPa). The implants received a labially directed total static load of 100 N at a 45° angle relative to their long axis. Parameters for analysis included the maximum and minimum principal stresses for bone, and von Mises equivalent stress for implants and abutments. Ti-26.88Fe-4Ta reaches the lowest maximum (57 MPa) and minimum (125 MPa) principal stress values, whereas Ti-35Nb-5Sn-6Mo-3Zr (183 MPa) and Ti-13Nb-13Zr (191 MPa) models result in the highest principal stresses (the 2.7 mm model surpasses the threshold for bone overload). Implant diameters affect von Mises stresses more than the constituent alloys. It can be concluded that the narrow implants made of the Ti-26.88Fe-4Ta alloy have the most favorable biomechanical behavior, mostly by mitigating stress on peri-implant bone.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 source (direct Gemma or distilled Codex), 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".