MétaCan
Menu
Back to cohort

Optimizing interlayer thickness for enhanced performance and chemical durability in sandwich-structured PEM fuel cells

2025· article· en· W4415545521 on OpenAlexfundno aff
Zulfi Gautama, Inho Yang, Norihiro Fukaya, Mustafa Ercelik, M.S. Ismail, Stephen Matthew Lyth, Kazunari Sasaki, Masamichi Nishihara

Bibliographic record

VenueJournal of Power Sources · 2025
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceJST-Mirai ProgramEngineering and Physical Sciences Research CouncilRoyal Society of ChemistryRoyal Society of Canada
KeywordsDurabilityNafionElectrolyteProton exchange membrane fuel cellMembranePolymerChemical stability

Abstract

fetched live from OpenAlex

Polymer electrolyte membrane (PEM) fuel cells are a leading technology for clean energy conversion, but their widespread adoption is hindered by the trade-off between high performance and long-term chemical durability. Here, we report an engineered multilayer PEM that sandwiches a gas barrier interlayer between cast Nafion outer layers. A blend of poly(vinyl alcohol) and poly(vinylsulfonic acid) (PVA/PVS) is used as the interlayer material, designed to suppress gas crossover and mitigate chemical attack without sacrificing ionic conductivity. The optimized membrane (designated PVA-100) has an interlayer loading of 100 μg/cm 2 and achieves power density equivalent to pristine Nafion at 0.6 V. Crucially, under accelerated stress testing, this membrane exhibits 1.8x higher chemical durability compared with a conventional membrane, maintaining superior voltage stability and superior power output retention at 0.6 V. These findings establish interlayer engineering as a scalable and effective strategy to overcome the durability–performance trade-off in PEM fuel cells. • Multilayer PEMs designed with a PVA/PVS gas barrier interlayer. • Effect of interlayer thickness on PEFC performance is systematically studied. • Optimized interlayers do not negatively impact initial cell performance. • Significantly improved durability compared to equivalent Nafion membranes. • More stable rated power output than Nafion during the durability test.

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 categoriesnone
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 score0.012
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.004
GPT teacher head0.203
Teacher spread0.199 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Power SourcesSame topicFuel Cells and Related MaterialsFrench-language works237,207