Contact analysis of gap formation at dental implant‐abutment interface under oblique loading: A numerical‐experimental study
Bibliographic record
Abstract
PURPOSE: To develop numerical and experimental methods for investigating the formation of micro-gaps and the change in contact area at the implant-abutment interface of two different connector designs under oblique cyclic loading. MATERIALS AND METHODS: Samples (n = 10 per group) of two-piece implant systems with the conical connection (group A) and the external hexagonal connection (group B) were subjected to cyclic loading with increasing load amplitudes up to 220 N. After loading, the samples were scanned using micro-CT, with silver nitrate as a high-contrast penetrant, and the level of leakage was assessed using a discrete scoring system. Three-dimensional finite element (FE) analyses of the two implant systems were also conducted to reveal the micro-gap formation process, especially bridging of the internal abutment screw space. The experimental and numerical results for the bridging load were then compared. RESULTS: 90% of the samples in group A showed leakage into the internal implant space at a load of around 100 N; while over 80% of those in group B did so at a load of around 40 N. This agreed with the FE analysis, which showed bridging of the internal implant space at loads similar to those measured for the two implant systems. Residual gaps of less than 1.49 μm were predicted for group A only after unloading. CONCLUSIONS: The FE-predicted loads for bridging agreed well with those found experimentally for leakage to occur. The conical connection showed more resistance against formation of micro-gaps at the implant-abutment interface than the external hexagonal connection. Although the minimum load required to bridge the internal implant space was within the range of human biting force, the relation between bacterial invasion and micro-gaps needs further research.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".