Di-metal Element Substitution of Al3+ and Ti4+ in Improving Electrochemical and Structural Behavior of Ceramic Solid Electrolytes
Bibliographic record
Abstract
Mechanical milling method is performed to prepare Li1+xAlxTixSn2-2xP3O12 (x = 0.2, 0.4, 0.6, 0.8) NASICON-based ceramic solid electrolyte at 650 o C. X-ray diffraction (XRD) showed that Li1.4Al0.4Ti0.4Sn1.2P3O12has almost pure compound that is isostructural to LiSn2(PO4)3 and the addition of Al 3+ and Ti 4+ have reduced the cell volume of the electrolytes.Side occupancy factor studies verified that the electrolyte with x = 0.4 possessed Sn:Ti:Al ratio close to the theoritical ratio.Field emission scanning electron microscopy analysis portrayed that all electrolytes have flaky type morphology.From electrochemical impedance spectroscopy (EIS) analysis, the highest value achieved is 4.74 × 10 -6 S cm -1 at x = 0.4.The substitutions of di-metal have affected the bulk resistance of the electrolytes.Dielectric constant of the electrolyte is at maximum when x = 0.4.The electrolytes follow non-Debye behavior as it shows a variation of relaxation times.
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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 | 0.001 | 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".