An Unexpected Pathway: <sup>6</sup>Li-Exchange NMR Spectroscopy Points to Vacancy-Driven Out-of-Plane Li-Ion Hopping in Crystalline Li<sub>2</sub>SnO<sub>3</sub>
Bibliographic record
Abstract
The development and engineering of new materials for modern electrochemical energy-storage systems requires an in-depth understanding of Li-ion dynamics, not only on the macroscopic length scale but also from an atomic-scale point of view. Hence, the study of suitable model systems is indispensable to understand the complexity of nonmodel systems already applied, for example, as active materials in rechargeable batteries. Here, Li 2 SnO 3 served as such a model system to enlighten the elementary steps of ion hopping between the three magnetically distinct Li sites. Through high-resolution 1D and 2D NMR spectroscopies, we probed the favored exchange pathway. Both 1D and 2D NMR spectroscopies point to nonuniform ion dynamics and two independent exchange processes perpendicular to the ab plane, namely, between the sites 4e [Li(3)] and 8f [Li(1)] and between 4e and 4d [Li(2)]. 6 Li selective-inversion NMR spectroscopy confirmed extremely slow Li exchange and yielded hopping rates on the order of 3 s –1 for 4e–8f and 0.7 s –1 for 4e–4d. Altogether, the findings provide evidence for a three-site, two-exchange model describing Li hopping along the c axis rather than in the Li-rich ab plane as one would expect at first glance. This unexpected result can, however, be understood when the site preference of Li vacancies is considered. Recent theoretical calculations predicted the preferred formation of Li vacancies at the Li(3) sites. This allows for localized Li-ion exchange involving Li(3), thus, perfectly corroborating the present findings obtained by 6 Li MAS NMR spectroscopy.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".