A study on optimal bonding angles of bi-material interfaces in dental crowns with porcelain fused to metal
Bibliographic record
Abstract
Interfaces between two different materials exist in the dental crowns used in dental restoration work. A common failure mode observed in dental crowns is debonding/fracture that is initiated at the corners of the interface between two materials, where a stress concentration or a stress singularity can be created. In this paper, finite element modelling and analytical methods are used to analyse the stress singularity at the free edge corners at the interfaces between porcelain and metal and also metal and cement in porcelain-fused-to-metal (PFM) crowns. Optimal ranges of bonding angles at the corners of the interface, that result in the elimination of the stress singularity, are obtained for PFM crowns made from a precious-metal-based or non-precious-metal-based alloy, respectively. The findings presented in this paper can serve as guidelines for the design and manufacture of PFM dental crowns.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".