Perovskite–Nitrogen‐Doped Carbon Nanotube Composite as Bifunctional Catalysts for Rechargeable Lithium–Air Batteries
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Bibliographic record
Abstract
Developing an effective bifunctional catalyst is a significant issue, as rechargeable metal-air batteries are very attractive for future energy systems. In this study, a facile one-pot process is introduced to prepare an advanced bifunctional catalyst (op-LN) incorporating nitrogen-doped carbon nanotubes (NCNTs) into perovskite La0.5 Sr0.5 Co0.8 Fe0.2 O3 nanoparticles (LSCF-NPs). Confirmed by half-cell testing, op-LN exhibits synergistic effects of LSCF-NP and NCNT with excellent bifunctionality for both the oxygen reduction reaction and the oxygen evolution reaction. Furthermore, op-LN exhibits comparable performances in these reactions to Pt/C and Ir/C, respectively, which highlights its potential for use as a commercially viable bifunctional catalyst. Moreover, the results obtained by testing op-LN in a practical Li-air battery demonstrate improved and complementary charge/discharge performance compared to those of LSCF-NP and NCNT, and this confirms that simply prepared op-LN is a promising candidate as a highly effective bifunctional catalyst for rechargeable metal-air batteries.
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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 it