High‐Performance Manganese Hexacyanoferrate with Cubic Structure as Superior Cathode Material for Sodium‐Ion Batteries
Bibliographic record
Abstract
Abstract Sodium manganese hexacyanoferrate (Na x MnFe(CN) 6 ) is one of the most promising cathode materials for sodium‐ion batteries (SIBs) due to the high voltage and low cost. However, its cycling performance is limited by the multiple phase transitions during Na + insertion/extraction. In this work, a facile strategy is developed to synthesize cubic and monoclinic structured Na x MnFe(CN) 6 , and their structure evolutions are investigated through in situ X‐ray diffraction (XRD), ex situ Raman, and X‐ray photoelectron spectroscopy (XPS) characterizations. It is revealed that the monoclinic phase undergoes undesirable multiple two‐phase reactions (monoclinic ↔ cubic ↔ tetragonal) due to the large lattice distortions caused by the Jahn–Teller effects of Mn 3+ , resulting in poor cycling performances with 38% capacity retention. The cubic Na x MnFe(CN) 6 with high structural symmetry maintains the structural stability during the repeated Na + insertion/extraction process, demonstrating impressive electrochemical performances with specific capacity of ≈120 mAh g −1 at 3.5 V (vs Na/Na + ), capacity retention of ≈70% over 500 cycles at 200 mA g −1 . In addition, the TiO 2 //C‐MnHCF full battery is fabricated with an energy density of 111 Wh kg −1 , suggesting the great potential of cubic Na x MnFe(CN) 6 for practical energy storage applications.
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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".