Evidence map›Paper›PMID 39478040›Full record

ArticleNature communications2024

Resolving optimal ionomer interaction in fuel cell electrodes via operando X-ray absorption spectroscopy.

Mengnan Wang, Jiaguang Zhang, Silvia Favero, Luke J R Higgins, Hui Luo, Ifan E L Stephens, Maria-Magdalena Titirici

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

7 authors.

Mengnan WangDepartment of Chemical Engineering, Imperial College London, London, SW7 2AZ, UK.
Jiaguang ZhangDepartment of Chemistry, University of Lincoln, Lincoln, LN6 7TS, UK.
Silvia FaveroDepartment of Chemical Engineering, Imperial College London, London, SW7 2AZ, UK.
Luke J R HigginsDiamond Light Source, Harwell Science & Innovation Campus, Didcot, OX11 0DE, UK.
Hui LuoDepartment of Chemical Engineering, Imperial College London, London, SW7 2AZ, UK.
Ifan E L StephensDepartment of Materials, Royal School of Mines, Imperial College London, London, SW7 2BP, UK. i.stephens@imperial.ac.uk.ORCID http://orcid.org/0000-0003-2157-492X
Maria-Magdalena TitiriciDepartment of Chemical Engineering, Imperial College London, London, SW7 2AZ, UK. m.titirici@imperial.ac.uk.ORCID http://orcid.org/0000-0003-0773-2100

Funding

RCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/L015277/1RCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/W031019/1Royal Academy of Engineering 1819\2\60
6 · The paper itself

Abstract

To bridge the gap between oxygen reduction electrocatalysts development and their implementation in real proton exchange membrane fuel cell electrodes, an important aspect to be understood is the interaction between the carbon support, the active sites, and the proton conductive ionomer as it greatly affects the local transportations to the catalyst surface. Here we show that three Pt/C catalysts, synthesized using the polyol method with different carbon supports (low surface area Vulcan, high surface area Ketjenblack, and biomass-derived highly ordered mesoporous carbon), revealed significant variations in ionomer-catalyst interactions. The Pt/C catalysts supported on ordered mesoporous carbon derived from biomass showed the best performance under the gas diffusion electrode configuration. Through a unique approach of operando X-ray Absorption Spectroscopy combined with gas sorption analysis, we were able to demonstrate the beneficial effect of mesopore presence for optimal ionomer-catalyst interaction at both molecular and structural level.

Identifiers

PMID39478040
PMCPMC11525635

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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.