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Record W3154665351

Phosphonic acid functionalized proton exchange membranes for PEM fuel cells

2000· article· en· W3154665351 on OpenAlexvenueno aff
Charles H. Stone, T S Daynard, L-Q Hu, Chin Hao Mah, A. Steck

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2000
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsnot available
Fundersnot available
KeywordsProton exchange membrane fuel cellSulfonic acidFuel cellsIon exchangeMembraneIonomerProtonMaterials scienceChemistryChemical engineeringIonPolymer chemistryOrganic chemistryEngineeringPolymerBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

In recent years there has been a shift from sulfonic acid to phosphonic acid functionality as the preferred potential polymeric material for application in proton exchange membrane (PEM) fuel cells. This paper explores the synthesis of poly(trifluorostyrene)-based ionomers which contain as their ion exchange functionality the phosphonic acid grouping. The paper describes details of preparation, characteristics of the material and indications of fuel cell performance capabilities. Results show that while these materials do provide indication of demonstrable performance in experimental fuel cells, at their present stage of development they do not appear to be a serious threat to the more standard sulfonic acid-based ionomers for application in commercial fuel cell products. 14 refs., 5 figs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.009
GPT teacher head0.209
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2000
Admission routes1
Has abstractyes

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