Highly Stable Na<sub>2/3</sub>(Mn<sub>0.54</sub>Ni<sub>0.13</sub>Co<sub>0.13</sub>)O<sub>2</sub> Cathode Modified by Atomic Layer Deposition for Sodium‐Ion Batteries
Bibliographic record
Abstract
For the first time, atomic layer deposition (ALD) of Al2 O3 was adopted to enhance the cyclic stability of layered P2-type Na2/3 (Mn0.54 Ni0.13 Co0.13 )O2 (MNC) cathodes for use in sodium-ion batteries (SIBs). Discharge capacities of approximately 120, 123, 113, and 105 mA h g(-1) were obtained for the pristine electrode and electrodes coated with 2, 5, and 10 ALD cycles, respectively. All electrodes were cycled at the 1C discharge current rate for voltages between 2 and 4.5 V in 1 M NaClO4 electrolyte. Among the electrodes tested, the Al2 O3 coating from 2 ALD cycles (MNC-2) exhibited the best electrochemical stability and rate capability, whereas the electrode coated by 10 ALD cycles (MNC-10) displayed the highest columbic efficiency (CE), which exceeded 97 % after 100 cycles. The enhanced electrochemical stability observed for ALD-coated electrodes could be a result of the protection effects and high band-gap energy (Eg =9.00 eV) of the Al2 O3 coating layer. Additionally, the metal-oxide coating provides structural stability against mechanical stresses occurring during the cycling process. The capacity, cyclic stability, and rate performance achieved for the MNC electrode coated with 2 ALD cycles of Al2 O3 reveal the best results for SIBs. This study provides a promising route toward increasing the stability and CE of electrode materials for SIB application.
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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 | 0.001 | 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".