Lithium ion conductivity, crystallization tendency, and microstructural evolution of LiZrxTi2-x(PO4)3 NASICON glass-ceramics (x = 0 - 0.4)
Bibliographic record
Abstract
In this research, NASICON type (LiZrXTi2-X(PO4)3) glass-ceramics were fabricated (x = 0.1, 0.2, 0.3, 0.4). Lithium-ion conductivity along with the crystallization tendency and microstructural features were examined in this regard. Parent glasses obtained through melt quenching were converted to the glass-ceramic specimens after one-step heat treatment procedure. The resultant glass-ceramics were deeply explored by means of different techniques including scanning electron microscope, differential thermal analysis, X-ray diffractometry, and ionic conductivity measurements. According to the obtained results, presence of Zr4+ ions in the glass network and its gradual increase caused the enhanced crystallization temperature as well as declined crystallinity and microstructure coarsening. In all studied glass-ceramics, LiT2(PO4)3 solid solution was the dominant crystalline phase and Zr4+ ions partly substituted in the structure of this crystalline phase. Moreover, presence of Zr4+ ions in the glass composition resulted in diminished lithium-ion conductivity of corresponded glass-ceramics at ambient temperature. Consequently, total conductivity of specimen with the highest level of ZrO2 (x = 0.4) was measured to be 0.78 x 10-5 Scm-1, being considerably less than ionic conductivity of the base (x = 0) glass-ceramic (3.04 x 10-5 Scm-1). It seems that less crystallinity of ZrO2 containing glass-ceramics decreases required connectivity between the lithium-ion free paths and is responsible for the diminished ionic conductivity of these specimens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".