An Improved Understanding of Li<sup>+</sup> Hopping Pathways and Rates in Li<sub>3</sub>Fe<sub>2</sub>(PO<sub>4</sub>)<sub>3</sub> Using Selective Inversion <sup>6</sup>Li NMR Spectroscopy
Bibliographic record
Abstract
6 Li selective inversion NMR experiments are used to reveal Li ion exchange rates and energy barriers for Li ion hopping in monoclinic Li 3 Fe 2 (PO 4 ) 3 . The three crystallographically unique Li sites in this material are well resolved by magic-angle spinning, thus allowing for the examination of all three exchange processes. We have revisited this material using selective inversion to probe dynamics, and energy barriers over the temperature range 268–397 K are found to be 0.37 ± 0.07, 0.53 ± 0.02, and 0.52 ± 0.03 eV for the three unique exchange pairs. The results presented here are consistent with the known Li 3 Fe 2 (PO 4 ) 3 crystal structure. The selective inversion experiment is more robust than 2D EXSY for the determination of energy barriers by NMR; this can be attributed to the efficiency of the one-dimensional technique, and an exchange model that accounts for multisite exchange and fast spin–lattice relaxation. Moreover, bond valence sum density maps provide a meaningful depiction of lithium ion diffusion pathways in this material that complement the NMR results.
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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 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".