Structural Relaxation in Polyanionic Sodium Fluorophosphate Glasses
Bibliographic record
Abstract
Structural heterogeneity is a common feature of all glasses, however, little is known about the underlying contributions of chemical fluctuations and modulations in free volume in concrete glass forming systems. In this investigation, we relate the dynamics of structural relaxation of (100-x)NaPO3–xAlF3 glasses to their heterogeneous structure as determined from multinuclear magnetic resonance spectroscopic analysis. For this, we evaluate differential scanning calorimetry (DSC) data using the integral isoconversional method to determine the variation in activation energy, Ea, of the glass transition as a function of temperature and conversion progress. Specific heat measurements from DSC allow for the determination of the effective size of the cooperatively rearranging region (CRR). From 31P, 19F and 27Al NMR, we observe that the introduction of AlF3 into the NaPO3 network increases the average connectivity (i.e., the number of heteronuclear Al—O—P bonds), rationalizing the higher Ea determined from the DSC measurements. We find highly constrained regions of Al(OP)4F2 with Al—F—Al cross-linking (high Ea) and, simultaneously, more flexible regions of phosphate chains containing P—F··(Na+)n bonds (low Ea); this results in a topologically and dynamically heterogeneous structure as evidenced by the increased variability in Ea with higher AlF3 content. The decreasing size of the CRR reflects the increased heterogeneity: at low AlF3 the CRR is large, while at high AlF3 (high heterogeneity), the CRR is significantly smaller (by a factor of 103). Finally, we relate the heterogeneity to other macroscopic properties, such as Tg and mechanical properties.
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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".