Novel Glass Formation in the Ca–Si–Al–O–N–F System
Bibliographic record
Abstract
Ca–Si–Al–O–N–F glass formation regions have been mapped on 6Ca 2+ –3Si 4+ –4Al 3+ ternary diagrams at fixed O:N:F of 79:20:1 and 75:20:5 (in eq%). For both fluorine contents, glass formation regions extend toward more Ca‐rich compositions at 1650°C compared with the Ca–Si–Al–O–N system at 1700°C. Ca–Si–Al–O–N–F melting temperatures are 150°–800°C lower than equivalent Ca–Si–Al–O compositions due to fluorine incorporation into the melt. Si‐rich compositions, with both 1 and 5 eq% F, form porous glasses due to loss of SiF 4 . Reaction mechanisms were studied by firing two compositions (0 or 5 eq% F) with identical cation ratios in the range of 900°–1650°C at 100°C intervals and following phase development using X‐ray diffraction. For Ca–Si–Al–O–N compositions, initial liquid formation occurs at >1200°C with complete dissolution of Si 3 N 4 at 1300°C. For Ca–Si–Al–O–N–F compositions, reactions occur at lower temperatures with Si 3 N 4 dissolution at 1200°C. At 20 eq% N, glasses with maximum fluorine content of ∼7 eq% were obtained. At 5 eq% F, the solubility limit for N is ∼25 eq%. At 1 eq% F, the maximum nitrogen content can be substantially increased to 40 eq% N. Incorporation of both nitrogen and fluorine in Ca–Si–Al–O glasses extends glass formation regions through combinations of lower melting temperatures (fluorine) and higher viscosities (nitrogen).
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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".