Highly Active and Durable Core–Corona Structured Bifunctional Catalyst for Rechargeable Metal–Air Battery Application
Bibliographic record
Abstract
A new class of core-corona structured bifunctional catalyst (CCBC) consisting of lanthanum nickelate centers supporting nitrogen-doped carbon nanotubes (NCNT) has been developed for rechargeable metal-air battery application. The nanostructured design of the catalyst allows the core and corona to catalyze the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR), respectively. These materials displayed exemplary OER and ORR activity through half-cell testing, comparable to state of the art commercial lanthanum nickelate (LaNiO(3)) and carbon-supported platinum (Pt/C), with added bifunctional capabilities allowing metal-air battery rechargeability. LaNiO(3) and Pt/C are currently the most accepted benchmark electrocatalyst materials for the OER and ORR, respectively; thus with comparable activity toward both of these reactions, CCBC are presented as a novel, inexpensive catalyst component for the cathode of rechargeable metal-air batteries. Moreover, after full-range degradation testing (FDT) CCBC retained excellent activity, retaining 3 and 13 times greater ORR and OER current upon comparison to state of the art Pt/C. Zinc-air battery performances of CCBC is in good agreement with the half-cell experiments with this bifunctional electrocatalyst displaying high activity and stability during battery discharge, charge, and cycling processes. Owing to its outstanding performance toward both the OER and ORR, comparable with the highest performing commercial catalysts to date for each of the respective reaction, coupled with high stability and rechargeability, CCBC is presented as a novel class of bifunctional catalyst material that is very applicable to future generation rechargeable metal-air batteries.
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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".