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Record W4361214790 · doi:10.1007/s41918-022-00175-1

Structure, Property, and Performance of Catalyst Layers in Proton Exchange Membrane Fuel Cells

2023· review· en· W4361214790 on OpenAlexafffund
Jian Zhao, Huiyuan Liu, Xianguo Li

Bibliographic record

VenueElectrochemical Energy Reviews · 2023
Typereview
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsProton exchange membrane fuel cellDurabilityMaterials scienceElectrochemistryCharacterization (materials science)CLs upper limitsCatalysisFabricationFuel cellsMembraneChemical engineeringComposite materialNanotechnologyChemistryEngineeringElectrodePhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Catalyst layer (CL) is the core component of proton exchange membrane (PEM) fuel cells, which determines the performance, durability, and cost. However, difficulties remain for a thorough understanding of the CLs' inhomogeneous structure, and its impact on the physicochemical and electrochemical properties, operating performance, and durability. The inhomogeneous structure of the CLs is formed during the manufacturing process, which is sensitive to the associated materials, composition, fabrication methods, procedures, and conditions. The state-of-the-art visualization and characterization techniques are crucial to examine the CL structure. The structure-dependent physicochemical and electrochemical properties are then thoroughly scrutinized in terms of fundamental concepts, theories, and recent progress in advanced experimental techniques. The relation between the CL structure and the associated effective properties is also examined based on experimental and theoretical findings. Recent studies indicated that the CL inhomogeneous structure also strongly affects the performance and degradation of the whole fuel cell, and thus, the interconnection between the fuel cell performance, failure modes, and CL structure is comprehensively reviewed. An analytical model is established to understand the effect of the CL structure on the effective properties, performance, and durability of the PEM fuel cells. Finally, the challenges and prospects of the CL structure-associated studies are highlighted for the development of high-performing PEM fuel cells.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.942
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.021
GPT teacher head0.238
Teacher spread0.217 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations149
Published2023
Admission routes2
Has abstractyes

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