Evidence map›Paper›PMID 42415710›Full record

ArticleACS applied materials & interfaces2026

Squeezing Gas Diffusion Electrodes in Zero-Gap CO

Viktor Józó, Soma B Halasi, Dániel Sebők, Ákos Kukovecz, Csaba Janáky, Balázs Endrődi

Abstract read
In one paragraph

Article in ACS applied materials & interfaces, 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
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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

6 authors.

Viktor JózóDepartment of Physical Chemistry and Materials Science, University of Szeged, Rerrich Square 1, H-6720 Szeged, Hungary.
Soma B HalasiDepartment of Physical Chemistry and Materials Science, University of Szeged, Rerrich Square 1, H-6720 Szeged, Hungary.
Dániel SebőkCentre of Excellence for Interdisciplinary Research, Development and Innovation, University of Szeged, Rerrich Béla tér 1, H-6720 Szeged, Hungary.
Ákos KukoveczDepartment of Applied and Environmental Chemistry, University of Szeged, Rerrich Béla tér 1, H-6720 Szeged, Hungary.ORCID 0000-0003-0716-9557
Csaba JanákyDepartment of Physical Chemistry and Materials Science, University of Szeged, Rerrich Square 1, H-6720 Szeged, Hungary.ORCID 0000-0001-5965-5173
Balázs EndrődiDepartment of Physical Chemistry and Materials Science, University of Szeged, Rerrich Square 1, H-6720 Szeged, Hungary.ORCID 0000-0003-3237-9222

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent scientific advancements indicate that the electrochemical reduction of carbon dioxide to carbon monoxide (CO2RR) is approaching industrial viability. Beyond scientific achievements, technology scale-up requires a full understanding of how certain cell components are to be used for long-term optimal performance and of what other challenges are posed by the larger sizes. Here, we investigated in detail how varying the compression ratio of the cathode gas diffusion electrode affects the electrochemical performance, using three fundamentally different carbon-based cathode supports. Electrochemical impedance spectroscopy and microtomography measurements are presented to explain the observed changes in the electrolysis performance, while the cathodes were gradually compressed to below 40% of their original thickness. The optimal compression range depends on the properties of the gas diffusion layer. Notably, a more than 100 μm wide optimal compression range is found for the thick ELAT1400W gas diffusion layer (i.e., a compression to 60-85% of its original thickness), which is further confirmed in 100-h-long experiments.

Indexed as

carbon dioxideCCUCO productionelectrolyzer engineeringGDE

Identifiers

PMID42415710
PMCPMC13397486

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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.