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Record W2803458341 · doi:10.3390/wevj8020431

Techno-Economics of a New High Throughput Process for Proton Exchange Membranes Manufacturing

2016· article· en· W2803458341 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueWorld Electric Vehicle Journal · 2016
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsNational Research Council Canada
FundersSimon Fraser University
KeywordsCommercializationProton exchange membrane fuel cellProcess engineeringCastingMembraneManufacturing engineeringProcess (computing)BifunctionalProduction (economics)Fuel cellsMaterials scienceThroughputBiochemical engineeringComputer scienceEngineeringChemical engineeringChemistryBusinessComposite materialCatalysisOrganic chemistryTelecommunications

Abstract

fetched live from OpenAlex

NRC developed an innovative process for efficiently producing one of the PEMFC key components; the polymeric electrolyte. The process developed is based on the use of bifunctional additives and highthroughput melt-processing technologies. This work demonstrates the Techno-economic Cost Modeling (TCM) methodology to model the economics of production scale-up of NRC technology, and to analyze the feasibility of commercialization for different Fuel Cell Vehicles (FCV) annual production scenarios. Results were compared with the SOTA process used to manufacture e-PTFE reinforced composite perfluorosulfonic acid (PFSA) membranes based on solution-casting.

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.

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 score0.299
Threshold uncertainty score0.464

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 head0.011
GPT teacher head0.215
Teacher spread0.204 · 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