Characterizing the residual glass in a MgO/Al2O3/SiO2/ZrO2/Y2O3 glass-ceramic
Bibliographic record
Abstract
Abstract The non-isochemical crystallization of glasses leads to glass-ceramics in which the chemical composition of the amorphous matrix differs from that of the parent glass. It is challenging to solely analyse the properties of these residual glassy phases because they frequently contain finely dispersed crystals. In this study, the composition of the residual glass matrix after the crystallization of a glass with the mol% composition 50.6 SiO 2 · 20.7 MgO · 20.7 Al 2 O 3 · 5.6 ZrO 2 · 2.4 Y 2 O 3 is analysed by scanning transmission electron microscopy (STEM) including energy dispersive X-ray analysis (EDXS). A batch of the residual glass with the determined composition is subsequently melted and selected properties are analysed. Furthermore, the crystallization behaviour of this residual glass is studied by X-ray diffraction, scanning electron microscopy including electron backscatter diffraction and STEM-EDXS analyses. The residual glass shows sole surface crystallization of indialite and multiple yttrium silicates while bulk nucleation does not occur. This is in contrast to the crystallization behaviour of the parent glass, in which a predominant bulk nucleation of spinel and ZrO 2 is observed. The crystallization of the residual glass probably leads to different crystalline phases when it is in contact to air, rather than when it is enclosed within the microstructure of the parent glass-ceramics.
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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".