Tracking Sodium-Antimonide Phase Transformations in Sodium-Ion Anodes: Insights from Operando Pair Distribution Function Analysis and Solid-State NMR Spectroscopy
Bibliographic record
Abstract
Operando pair distribution function (PDF) analysis and ex situ (23)Na magic-angle spinning solid-state nuclear magnetic resonance (MAS ssNMR) spectroscopy are used to gain insight into the alloying mechanism of high-capacity antimony anodes for sodium-ion batteries. Subtraction of the PDF of crystalline NaxSb phases from the total PDF, an approach constrained by chemical phase information gained from (23)Na ssNMR in reference to relevant model compounds, identifies two previously uncharacterized intermediate species formed electrochemically; a-Na(3-x)Sb (x ≈ 0.4-0.5), a structure locally similar to crystalline Na3Sb (c-Na3Sb) but with significant numbers of sodium vacancies and a limited correlation length, and a-Na(1.7)Sb, a highly amorphous structure featuring some Sb-Sb bonding. The first sodiation breaks down the crystalline antimony to form first a-Na(3-x)Sb and, finally, crystalline Na3Sb. Desodiation results in the formation of an electrode formed of a composite of crystalline and amorphous antimony networks. We link the different reactivity of these networks to a series of sequential sodiation reactions manifesting as a cascade of processes observed in the electrochemical profile of subsequent cycles. The amorphous network reacts at higher voltages reforming a-Na(1.7)Sb, then a-Na(3-x)Sb, whereas lower potentials are required for the sodiation of crystalline antimony, which reacts to form a-Na(3-x)Sb without the formation of a-Na(1.7)Sb. a-Na(3-x)Sb is converted to crystalline Na3Sb at the end of the second discharge. We find no evidence of formation of NaSb. Variable temperature (23)Na NMR experiments reveal significant sodium mobility within c-Na3Sb; this is a possible contributing factor to the excellent rate performance of Sb anodes.
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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 | 0.000 | 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) | 0.000 | 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".