Nanocarbons and Their Hybrids as Electrocatalysts for Metal‐Air Batteries
Bibliographic record
Abstract
Owing to high energy density, metal-air batteries are considered as one of the cutting-edge and promising technologies for future power sources in different electronic applications, including transportation, portables, and stationary. Generally, metal-air batteries are composed of a metallic anode with high energy density and a cathodic air electrode with an open structure which are separated by an aqueous or organic electrolyte. In order to commercialize such systems, several challenges associated with metal-air batteries must be conquered. Particularly, it is extremely demanded to develop cheap, highly efficient, and durable catalytic materials for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) at air-breathing electrode to increase the performance and operational life of metal-air batteries. Among different types of catalytic materials, this chapter is focused on the most recently studied nanocarbon-based electrocatalysts and their hybrids for metal-air batteries. Nanostructured carbons can be used as either metal-free catalysts themselves or supports for other types of catalysts. Because of the high surface area, excellent electrical conductivity, and good chemical and mechanical stability of nanocarbons, they are highly potential to enhance the performance and life cycle of electrodes and hence the metal-air batteries. In this chapter, first, the most important challenges related to air electrodes in metal-air batteries are discussed. Then, three categories of comprehensively studied nanocarbons and their hybrids for the ORR and OER are selectively reviewed for the two most attractive metal-air batteries, namely Zinc-air and Li-air batteries: metal-free nanocarbons (e.g., graphene or carbon nanotubes), noble metal nanocarbons (e.g., Pt-graphene), and metal oxide nanocarbons (e.g., LaNiO3-nitrogen-doped carbon nanotubes). Next, the remarkable ORR/OER and battery performance of different nanocarbonaceous catalysts are compared to each other. Finally, as still there are some shortcomings to be overcome for the nanocarbonaceous electrodes, some future research directions are suggested for efficient development of air electrodes in 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".