Enhancing Li Ion Conductivity of Garnet-Type Li<sub>5</sub>La<sub>3</sub>Nb<sub>2</sub>O<sub>12</sub> by Y- and Li-Codoping: Synthesis, Structure, Chemical Stability, and Transport Properties
Bibliographic record
Abstract
Novel Li-stuffed garnet-like “Li 5+2 x La 3 Nb 2– x Y x O 12 ” (0.05 ≤ x ≤ 0.75) was prepared via solid-state reaction in air and characterized using ex situ and in situ powder X-ray diffraction (PXRD), 7 Li and 27 Al magic angle spinning nuclear magnetic resonance (MAS NMR), scanning electron microscopy (SEM), thermo-gravimetric analysis (TGA), and AC impedance spectroscopy. Rietveld refinement with the PXRD data confirmed the formation of a cubic, garnet-like Ia -3 d structure. 7 Li MAS NMR showed a single sharp peak close to 0 ppm as the usual trend for fast Li ion conducting garnets. Among the materials studied, “Li 6.5 La 3 Nb 1.25 Y 0.75 O 12 ” showed a very high bulk ionic conductivity of 2.7 × 10 –4 S cm –1 at 25 °C, which is the highest value found in garnet-type compounds, and is only reported for Li 7 La 3 Zr 2 O 12 . The in situ PXRD measurements revealed structural stability up to 400–600 °C after water treatment as well as chemical compatibility with high voltage Li cathodes Li 2 MMn 3 O 8 (M = Co, Fe). The current work demonstrates that slight Al contamination from the Al 2 O 3 crucible, which is commonly observed in this class of materials and was detected by 27 Al MAS NMR, does not affect the Li ionic conductivity and chemical stability of “Li 5+2 x La 3 Nb 2– x Y x O 12 ” garnets. It also shows that Li stuffing is critical to improve further the ionic conductivity of parent compound Li 5 La 3 Nb 2 O 12 . Y 3+ seems to be a very efficient dopant to improve the ionic conductivity of garnets compared to other investigated dopants that include M 2+ (M = alkaline earth metals), In 3+, and Zr 4+ .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".