Surface and Mechanical Characterization of Dental Yttria-Stabilized Tetragonal Zirconia Polycrystals (3Y-TZP) After Different Aging Processes
Bibliographic record
Abstract
Yttria-stabilized tetragonal zirconia polycrystals (3Y-TZP) is a ceramic material used in indirect dental restorations. However, phase transformation at body temperature may compromise the material's mechanical properties, affecting the clinical performance of the restoration. The effect of mastication on 3Y-TZP aging has not been investigated. 3Y-TZP specimens (IPS E-max ZirCAD and Z5) were aged in three different modes (n=13): no aging (control), hydrothermal aging (HA), or chewing simulation (CS). Mechanical properties and surface topography were analyzed. Analysis of variance showed that neither aging protocol (p=0.692) nor material (p=0.283) or the interaction between them (p=0.216) had a significant effect on flexural strength, values ranged from 928.8 MPa (IPSHA) to 1,080.6 MPa (Z5HA). Nanoindentation analysis showed that material, aging protocol, and the interaction between them had a significant effect (p<0.001) on surface hardness and reduced Young's modulus. The compositional analysis revealed similar yttrium content for all the experimental conditions (aging: p=0.997; material: p=0.248; interaction material×aging: p=0.720). Atomic force microscopy showed an effect of aging protocols on phase transformation, with samples submitted to CS exhibiting features compatible with maximized phase transformation, such as increased volume of the material microstructure at the surface leading to an increase in surface roughness.
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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 | 0.000 |
| 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".