Synthesis, Structure and Li Ion Conductivity of Garnet-like Li<sub>5+2x</sub>La<sub>3</sub>Nb<sub>2-x</sub>Sm<sub>x</sub>O<sub>12</sub>(0 ≤ x ≤ 0.7)
Bibliographic record
Abstract
Here, we report the synthesis, structure and Li ion conductivity of new Sm-doped garnet-type Li 5+2x La 3 Nb 2-x Sm x O 12 (0 ≤ x ≤ 0.7). Powder X-ray diffraction showed the formation of cubic garnet structure up to x = 0.3. Above x = 0.3 impurity phases were observed, due to LiNbO 3 (the joint committee on powder diffraction standards (JCPDS) card No. 01-074-2239), LiSmO 2 (JCPDS Card No. 01-073-1061) and Sm 2 O 3 (JCPDS Card No. 15-0813). The cubic cell constant increased from 12.774(2) Å (x = 0) to 12.851(2) Å (x = 0.3). Scanning electron microscopy showed that Sm-doping results in an increase in density of the samples, as a result of improved particle-to-particle contact. Among the samples investigated, Li 5.6 La 3 Nb 1.7 Sm 0.3 O 12 , showed the highest conductivity of ∼10 −5 S cm −1 at 24°C which is an order of magnitude higher than that of the parent compound, Li 5 La 3 Nb 2 O 12. The activation energy in the temperature range 25–225°C decreased with an increase in Sm-dopant in Li 5+2x La 3 Nb 2-x Sm x O 12 (0.45 eV for x = 0.05 to 0.38 eV for x = 0.3). Fourier transform infrared spectroscopy studies revealed the presence of Li 2 CO 3 in both aged and fresh samples, while thermogravimetric analysis results showed that fresh samples exhibit a lower weight loss compared to the aged samples.
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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".