Interfacial Super‐Assembled Porous CeO<sub>2</sub>/C Frameworks Featuring Efficient and Sensitive Decomposing Li<sub>2</sub>O<sub>2</sub> for Smart Li–O<sub>2</sub> Batteries
Bibliographic record
Abstract
Abstract The Li–O 2 battery (LOB) represents a promising candidate for future electric vehicles owing to its outstanding energy density. However, the practical application of LOB cells is largely blocked by the poor cycling performance of cathode materials. Herein, an ultralong 440‐cycle life of an LOB cell is achieved using CeO 2 nanocubes super‐assembled on an inverse opal carbon matrix as the cathode material without any additives. CeO 2 is proved to be effective for the complete and sensitive decomposition of loosely stacked Li 2 O 2 films during the oxygen evolution reaction process and full accommodation of volume changes caused by the fast growth of Li 2 O 2 films during the oxygen reduction reaction process. The super‐assembled porous CeO 2 /C frameworks satisfy critical requirements including controlled size, morphology, high Ce 3+ /Ce 4+ ratio, and efficient volume change accommodation, which dramatically increase the cycle life of LOB cell to 440 cycles. This study reveals the design strategy for high performance CeO 2 catalyst cathodes for LOB cells and the generation mechanisms of Li 2 O 2 films during the discharge process by using density functional theory calculations, showing new avenues for improving the future smart design of CeO 2 ‐based cathode catalysts for Li–O 2 batteries.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".