Revealing Na<sup>+</sup> Dynamics in the Na<sub>4</sub>Sn<sub>2</sub>Ge<sub>5</sub>O<sub>16</sub> Solid Electrolyte Material Using <sup>23</sup>Na Solid-State NMR Spectroscopy and Computational Methods
Bibliographic record
Abstract
Na 4 Sn 2 Ge 5 O 16 is a novel Na + conductor that can be utilized in the next generation of all-solid-state Na + batteries (ASSNIBs). 23 Na ssNMR experiments were carried out on the Na 4 Sn 2 Ge 5 O 16 phase to investigate the Na + dynamics for the three unique crystallographic Na sites under multiple field strengths (20, 11.7, and 7 T). However, completely resolving the fast exchange Na2 and Na3 pair (4c sites) in the 23 Na NMR spectra (Na2–3 resonance) was nontrivial under the available experimental conditions. The subsequent relaxation study supports that the Na2–3 peaks are dynamically mediated, in contrast to immobile Na1 peaks. To further understand the dynamic effects on the 23 Na NMR spectra, 1D and 2D 3QMAS 23 Na spectra under various magnetic field strengths were analyzed to establish possible ranges of “averaged” quadrupolar parameter values for the two sites. With the assistance of density functional theory (DFT)-based CASTEP calculations, simulated lineshapes of the Na1 site (8d) are established, which exhibit excellent agreement with the experimentally determined ones. Subsequently, the EXchange Program for RElaxing Spin Systems (EXPRESS) script was employed to simulate the Na2–3 peaks under dynamic conditions, with a final estimated exchange rate of 2 × 10 5 Hz. This work paves the way for future studies of Na + transport at the molecular level in fast-conducting Na-based solid electrolytes (SEs).
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".