Crystallization behavior and ionic conductivity of NASICON type glass-ceramics containing different amounts of B2O3
Bibliographic record
Abstract
In this research, glass-ceramics belonging to the system of Li2O-TiO2-P2O5 were prepared by the addition of different amounts of B2O3. The glass formation ability of the starting glass materials along with the crystallization trend as well as ionic conductivity of the corresponding glass-ceramics were also examined. Starting glasses were obtained through the melt quenching technique and glass-ceramics specimens were prepared through one-step heat treatment. The glass-ceramic samples were then examined through X-ray diffractometry, differential thermal analysis, electrochemical impedance spectroscopy, and scanning electron microscopy. According to the obtained results, the addition of a 2.5 mole% of B2O3 to the glass composition led to a sharp increase in ionic conductivity at room temperature. So that the bulk conductivity of the specimen heat treated at 950 °C for 2 h was measured to be 1.17 × 10-3 Scm-1, which was 10 times bigger than that of the base glass-ceramic with no additive. It also decreased the crystallization temperature and viscosity of the parent glass, resulting in increased crystallinity while further addition of B2O3 drained the conductivity and crystallinity of 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".