Evidence map›Paper›PMID 40938006›Full record

ArticleNanomaterials (Basel, Switzerland)2025

Effect of the Microstructure of Carbon Supports on the Oxygen Reduction Properties of the Loaded Non-Noble Metal Catalysts.

Dan Ma, Yudong Zhang, Menghan Liang, Runyu Niu, Yao Ge, Yanan Zou, Xiaorui Dong

Abstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Dan MaSchool of Energy and Power Engineering, North University of China, Taiyuan 030051, China.
Yudong ZhangSchool of Energy and Power Engineering, North University of China, Taiyuan 030051, China.ORCID 0009-0002-8023-8774
Menghan LiangSchool of Energy and Power Engineering, North University of China, Taiyuan 030051, China.
Runyu NiuSchool of Energy and Power Engineering, North University of China, Taiyuan 030051, China.
Yao GeChongqing University Industrial Technology Research Institute, Chongqing 400030, China.
Yanan ZouCollege of Mechanical Engineering, University of South China, Hengyang 421001, China.
Xiaorui DongSchool of Energy and Power Engineering, North University of China, Taiyuan 030051, China.

Funding

Yanan Zou No.52306248
6 · The paper itself

Abstract

The development of efficient non-noble metal catalysts is critical for advancing sustainable fuel-cell technologies. This study investigates the effect of carbon support microstructure on the oxygen reduction reaction (ORR) performance of Fe-N-C catalysts. By precisely tuning the pyrolysis temperature of activated carbon (AC) between 600 and 1000 °C, we elucidate the mechanistic influence of the physicochemical characteristics of the carbon support on the ORR activity of the supported catalyst. Increasing the pyrolysis temperature enhanced the electrical conductivity of the carbon support, thereby improving the ORR performance of the catalyst. However, while the defect density and specific surface area of the carbon support initially increased with increasing pyrolysis temperature, they declined when elevated temperatures were used (e.g., 1000 °C), leading to reduced ORR activity. The AC-900 support, pyrolyzed at 900 °C, exhibited an optimal balance of a high surface area, abundant defects, and superior conductivity. An Fe phthalocyanine/AC-900 catalyst synthesized using the AC-900 support exhibited excellent ORR activity (

Indexed as

carbon supportsmicrostructurenon-noble metal catalystsoxygen reduction reactionpyrolysis temperature

Identifiers

PMID40938006
PMCPMC12430596

What OpenQuestion holds

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Registered trials

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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.