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Record W7117454420 · doi:10.1021/acsenergylett.5c03632

Free-Standing Catalyst Layers Based on Porous Polymer Composites with Tailored Mass Transport Properties for AEM Water Electrolysis

2025· article· en· W7117454420 on OpenAlexafffund
Anna Volz, B. Chen, L. Sanderson, M. Ulbricht, S. Holdcroft, Lukas Fischer

Bibliographic record

VenueACS Energy Letters · 2025
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaDeutsche Forschungsgemeinschaft
KeywordsElectrolysis of waterElectrolysisCathodeElectrodePorosityCatalysisComposite numberCoatingPolymerCurrent density

Abstract

fetched live from OpenAlex

Anion-exchange membrane water electrolysis (AEMWE) for green hydrogen (H 2 ) production is hindered by safety-critical H 2 crossover. Current gas management strategies often overlook the role of catalyst layer (CL) porosity, primarily because conventional ink coating and drying preparation creates dense CLs. Here, we introduce free-standing, fully conductive polymer composite CLs with defined pore structures and high porosities (∼50–75%), which are fabricated through scalable film casting and nonsolvent phase separation of electrode pastes (matrix polymer, carbon filler, nickel catalyst, and solvent). These free-standing CLs can be simply cold-pressed into membrane electrode assemblies (MEAs), enabling high current density AEMWE operation (>3 A/cm 2 ). Crucially, gas–liquid transport within these CLs can be engineered through their pore structure to mitigate H 2 crossover. A free-standing cathode CL with good bubble-releasing characteristics reduced H 2 crossover at 0.75 A/cm 2 to 1% in O 2, compared to 2.5% for a CL with suppressed bubble release and 2.3% for a conventional Ni felt.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.341
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.181
Teacher spread0.174 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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