Multifunctional Quasi‐Homogeneous Catalysts as a New Catalytic Strategy to Boost the Performance of Li‐O<sub>2</sub> Batteries
Bibliographic record
Abstract
Abstract Li‐O 2 batteries have been considered as a kind of prospective next‐generation batteries due to their ultrahigh energy densities. However, limited capacities, high charge overpotentials, and short lifetime are troubling obstacles for realizing their real‐world implementation. Common strategies, including introducing solid‐state catalysts (SSCs) and redox mediators (RMs), are insufficient to solve these issues. Herein, Ru‐loaded amino‐phenanthroline‐based carbonized polymer dots (RuApCPDs) integrating the catalytic activity of SSCs with the mobility of RMs have been designed to behave as quasi‐homogeneous catalysts in the electrolyte. Their mobile nature can ensure the avoidance of complete coverage of active sites, and the catalytic ability decreases the charge overpotential through co‐deposition with the discharge products. Additionally, the RuApCPDs can also adjust the Li + solvation structure and well protect the Li metal anodes with high stability. As a result, the introduction of RuApCPDs leads to a fivefold increase in discharge capacity, a low charge voltage of 3.75 V, and a running life of 168 cycles (79 cycles without RuApCPDs). The multifunctional quasi‐homogeneous catalyst developed here demonstrates its advantageous potential as a new catalytic strategy for bringing Li‐O 2 batteries to become a viable technology.
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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".