Evidence map›Paper›PMID 41745496›Full record

ReviewMembranes2026

Structural Design and Performance Optimization of Proton Exchange Membranes for Water Electrolysis: A Review.

Yi Chen, Hongyang Ma, Benjamin S Hsiao

Abstract readReview
In one paragraph

Review in Membranes, 2026. 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

3 authors.

Yi ChenState Key Laboratory of Organic-Inorganic Composites, Beijing University of Chemical Technology, Beijing 100029, China.
Hongyang MaState Key Laboratory of Organic-Inorganic Composites, Beijing University of Chemical Technology, Beijing 100029, China.
Benjamin S HsiaoDepartment of Chemistry, Stony Brook University, Stony Brook, NY 11794-3400, USA.ORCID 0000-0002-3180-1826

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The trade-off between the ionic conductivity and the stability of the proton exchange membrane (PEM) is a major concern in the development of PEM water electrolysis (PEMWE). This review focuses on the design and fabrication of homogeneous and composite PEMs for water electrolysis and establishes the structure-performance relationships between the membrane chemical/physical structures and their efficiency metrics-specifically, proton conductivity, hydrogen permeability, and chemical and mechanical stability. A special focus is placed on the fundamental connection between the microstructure and performance of membrane materials. At the molecular level, we systematically illustrate the design principles for main chains, side chains, and sulfonate groups, covering both fluorinated PEMs (encompassing perfluorinated and partially fluorinated membranes) and non-fluorinated PEMs (including aromatic polymers with heteroatom backbones and all-carbon backbones). At the macroscopic level, the review provides an in-depth exploration of two primary modification strategies: creating composites with organic polymers and with inorganic nanofillers. In summary, this review elucidates how these composite approaches leverage material synergies to improve the membrane's mechanical integrity, proton conduction efficiency, and chemical resistance and offers a theoretical framework for the rational design of next-generation, high-performance PEMs to advance the commercialization of PEMWE technology.

Indexed as

compositeionic conductivityPEMPEMWEstabilitystructure–performance relationship

Identifiers

PMID41745496
PMCPMC12942330

What OpenQuestion 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 OpenQuestion graph.