Structural Complexity and Electrical Properties of the Garnet-Type Structure LaLi<sub>0.5</sub>Fe<sub>0.2</sub>O<sub>2.09</sub> Studied by <sup>7</sup>Li and <sup>139</sup>La Solid State NMR Spectroscopy and Impedance Spectroscopy
Bibliographic record
Abstract
Garnet-like structures containing lithium are of interest for applications in lithium ion batteries because of their inherent lithium ion conductivity and stability against chemical reaction with Li. Here, a series of materials, with parent composition LaLi 0.5 Fe 0.2 O 2.09, are synthesized using solid-state chemistry, and characterized, in terms of their structure, using a combination of powder X-ray diffraction (PXRD), 7 Li, and 139 La solid-state NMR, which reveal disorder on the Li and Fe sites in the lattice. The 7 Li spectra comprise a set of peaks that are distinguished based on their T 1 relaxation properties, as a diamagnetic set and a paramagnetic set of peaks. The 139 La spectra include two La environments, one well-defined, with a C Q of 56 MHz ± 1 MHz and asymmetry parameter, η of 0.05 ± 0.05, and a second, which experiences a range of local environments, because of the Li/Fe substitution, and has a C Q of 29 MHz ± 2 MHz, and η of 0.6 ± 0.1. The dynamics within the materials were characterized using impedance spectroscopy, and trends were correlated with the lithium content and structural features. The best conductivity was determined for the parent material, LaLi 0.5 Fe 0.2 O 2.09, after sintering at 850 °C. The complex 7 Li and 139 La NMR spectra, interpreted together with (PXRD) data, indicate that the increasing concentration of lithium in the material populates an iron site with excess lithium, in a range of possible local environments, which appears to decrease the total ionic and electronic conductivity.
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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".