Evidence map›Paper›PMID 40971421›Full record

ArticleScience advances2025

Nanofiber membranes for enhanced performance and optimization of proton exchange membrane fuel cells.

Heng Zhai, Jianuo Chen, Chen Meng, Xiaochen Yang, Zeyu Zhou, Ling Ai, Jiashen Li, Thomas S Miller, Maria Perez-Page, Stuart M Holmes

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Science advances, 2025. 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. Review
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

10 authors.

Heng ZhaiDepartment of Chemical Engineering, The University of Manchester, Manchester M13 9PL, UK.ORCID 0000-0002-8884-3058
Jianuo ChenDepartment of Chemical Engineering, The University of Manchester, Manchester M13 9PL, UK.ORCID 0000-0003-4019-0737
Chen MengDepartment of Materials, The University of Manchester, Manchester M13 9PL, UK.ORCID 0000-0001-5540-553X
Xiaochen YangDepartment of Chemical Engineering, The University of Manchester, Manchester M13 9PL, UK.
Zeyu ZhouDepartment of Chemical Engineering, The University of Manchester, Manchester M13 9PL, UK.
Ling AiDepartment of Chemical Engineering, The University of Manchester, Manchester M13 9PL, UK.ORCID 0009-0002-6293-9817
Jiashen LiDepartment of Materials, The University of Manchester, Manchester M13 9PL, UK.ORCID 0000-0001-7333-5280
Thomas S MillerElectrochemical Innovation Lab, Department of Chemical Engineering, University College London, London WC1E 7JE, UK.ORCID 0000-0002-2224-5768
Maria Perez-PageDepartment of Chemical Engineering, The University of Manchester, Manchester M13 9PL, UK.ORCID 0000-0002-9706-7492
Stuart M HolmesDepartment of Chemical Engineering, The University of Manchester, Manchester M13 9PL, UK.ORCID 0000-0002-6269-9043

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Proton exchange membranes (PEMs) are critical to fuel cell performance, where ion transport, catalyst activity, and mass transfer determine efficiency and durability. However, conventional membranes in PEM fuel cells often suffer from hydrogen crossover, limited conductivity, and poor interfacial stability. To address these challenges, this study develops a nanofiber membrane system with synergistic structural and interfacial enhancement. Through nanofiber architecture and surface engineering, the membrane balances proton conductivity, mechanical strength and electrochemical performance. The sandwich-structure nanofiber membrane (SSNFM) achieves a peak power density of 942 mW cm

Identifiers

PMID40971421
PMCPMC12448063

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.