Dielectric characteristics of fast Li ion conducting garnet-type Li5+2xLa3Nb2 xYxO12 (x = 0.25, 0.5 and 0.75)
Bibliographic record
Abstract
Here, we report the dielectric characteristics of Li-stuffed garnet-type Li5+2xLa3Nb2−xYxO12 (x = 0.25, 0.5 and 0.75) in the temperature range about −53 to 50 °C using AC impedance spectroscopy. All the investigated Li-stuffed garnet compounds were prepared, under the same condition, using conventional solid-state reaction at elevated temperature in air. The Nyquist plots show mainly bulk contribution to the total Li+ ion conductivity for Li5.5La3Nb1.75Y0.25O12 (Li5.5–Nb) and Li6La3Nb1.5Y0.5O12 (Li6–Nb), while both bulk and grain-boundary effects are visible in the case of Li6.5La3Nb1.25Y0.75O12 (Li6.5–Nb) phase at ∼−22 °C. Non-Debye relaxation process was observed in the modulus AC impedance plots. The dielectric loss tangent of Li5+2xLa3Nb2−xYxO12 are compared with that of the corresponding Ta analogue, Li5+2xLa3Ta2−xYxO12 and showed a decrease in peak intensity for the Nb-based garnet samples which may be attributed to a slight increase in their Li+ ion conductivity. The relative dielectric constant values were also found to be higher for the Ta member (>60 for Li5+2xLa3Ta2−xYxO12) than that of the corresponding Nb analogue (∼50 for Li5+2xLa3Nb2−xYxO12) at below room temperature. A long-range order Li+ ion migration pathway with relaxation time (τ0) 10−18–10−15 s and an activation energy of 0.59–0.40 eV was observed for the investigated Li5+2xLa3Nb2−xYxO12 garnets and is comparable to that of the corresponding Ta-based Li5+2xLa3Ta2−xYxO12 garnets.
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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
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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".