Raman Spectroscopy Evaluation of Subsurface Hydrothermal Degradation of Zirconia
Bibliographic record
Abstract
The aims of this study were to calibrate the collection depth for RMS and, using the calibration, to evaluate the in‐depth phase transformation induced in a dental 3 Y ‐ TZP ceramic by hydrothermal aging, simulating LTD . Objectives 10x and 80x affording spatial resolutions of ~3 and ~1 μm, respectively, were used. Probe size was controlled by the confocal pinhole aperture. The collection depth of each probe (objective – pinhole combination) was calibrated on a wedge‐shaped pure tetragonal zirconia specimen. Pure tetragonal samples of a dental 3 Y ‐ TZP were aged in vitro in an autoclave, in Ringer solution, at 130°C, under 0.6 MPa, for 10, 15, 20, 25, and 90 h. Two specimens were used for each time interval and two unexposed specimens served as controls. Monoclinic volume fraction ( V fm ) was determined by X‐ray diffraction and by in‐depth probing with RCMS . Probes based on 10x objective penetrated up to 68 μm, whereas those based on the 80x were limited to 5 μm. Aging induced significant increase in V fm , ranging from 30% after 10 h to 80% after 90 h. After 90 h aging, the 80% V fm extended to at least 20 μm from the surface. A maximum V fm was identified at 2.5 μm subsurface depth in 10, 15, and 20 h aged specimens.
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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".