Uptake of CO<sub>2</sub> in Layered P2-Na<sub>0.67</sub>Mn<sub>0.5</sub>Fe<sub>0.5</sub>O<sub>2</sub>: Insertion of Carbonate Anions
Bibliographic record
Abstract
Batteries based on sodium layered transition metal oxides are a promising alternative to current state-of-the-art lithium-ion systems for large-scale energy storage, resulting in recent intensive efforts to develop high-energy density, low cost, stable cathode materials. Some of the most promising degrade on exposure to ambient atmosphere; however, the process is not understood. Here, using neutron/X-ray diffraction coupled with mass spectroscopy and thermal analysis, we reveal the nature of the reactivity. We demonstrate the unprecedented insertion of carbonate ions in the vacancy-rich layered structure of P2-Na 0.67 [Mn 0.5 Fe 0.5 ]O 2 on exposure to CO 2 and moisture, concomitant with oxidation of Mn(III) to Mn(IV). The material exhibits much higher charge/discharge polarization and lower capacity than rigorously air-protected P2-Na 0.67 [Mn 0.5 Fe 0.5 ]O 2; a detailed study by online electrochemistry mass spectroscopy reveals that the inserted carbonate ions decompose during electrochemical charging, accounting for the differences observed between the first and second cycles. Furthermore, we show that Ni-substituted materials P2-Na 0.67 [Ni x Mn 0.5+ x Fe 0.5−2 x ]O 2 are less prone to such reactivity and thus are more promising candidates for scalable processing. Understanding these mechanisms provides a vital guide for future sodium metal oxide battery research.
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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".