Evidence map›Paper›PMID 39683814›Full record

ReviewMolecules (Basel, Switzerland)2024

Iron Porphyrin-Based Composites for Electrocatalytic Oxygen Reduction Reactions.

Stennard Leetroy George, Linkai Zhao, Ziyi Wang, Zhaoli Xue, Long Zhao

Abstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Stennard Leetroy GeorgeSchool of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, China.ORCID 0009-0008-5614-7761
Linkai ZhaoSchool of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, China.
Ziyi WangSchool of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, China.
Zhaoli XueSchool of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, China.
Long ZhaoSchool of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, China.ORCID 0000-0001-5896-9226

Funding

National Natural Science Foundation of China 22075110
6 · The paper itself

Abstract

The oxygen reduction reaction (ORR) is one of the most critical reactions in energy conversion systems, and it facilitates the efficient conversion of chemical energy into electrical energy, which is necessary for modern technology. Developing efficient and cost-effective catalysts for ORRs is crucial for advancing and effectively applying renewable energy technologies such as fuel cells, metal-air batteries, and electrochemical sensors. In recent years, iron porphyrin-based composites have emerged as ideal catalysts for facilitating effective ORRs due to their unique structural characteristics, abundance, advances in synthesis, and excellent catalytic properties, which mimic natural enzymatic systems. However, many articles have focused on reviewing porphyrin-based frameworks or metalloporphyrins in general, necessitating research specifically addressing iron porphyrin. This review discusses iron porphyrin as an effective catalyst in ORRs. It provides a comprehensive knowledge of the application of iron porphyrin-based composites for electrocatalytic ORRs, focusing on their properties, synthesis, structural integration with conductive supports, catalytic mechanism, and efficacy. This review also discusses the challenges of applying iron porphyrin-based composites and provides recommendations to address these challenges.

Indexed as

axial ligandselectrocatalystsfunctional group effectsiron porphyrinsoxygen reduction reactionsubstituent effects

Identifiers

PMID39683814
PMCPMC11643590

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.