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Record W2314724060 · doi:10.1149/1.3242365

Preparation and Characterization of DMFC Electrodes and MEAs

2009· article· en· W2314724060 on OpenAlexaff
Xinzhong Xue, Christina Bock, B. MacDougall, David Kingston

Bibliographic record

VenueECS Transactions · 2009
Typearticle
Languageen
FieldEngineering
TopicGas Sensing Nanomaterials and Sensors
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMaterials scienceElectrodeAnodeNafionCatalysisChemical engineeringMembraneCharacterization (materials science)Layer (electronics)Composite materialIonomerElectrochemistryNanotechnologyChemistryPolymerOrganic chemistry

Abstract

fetched live from OpenAlex

A stencil method, that utilizes a dried powder made of the catalyst and the Nafion ionomer phase, is used to make catalyst layers and membrane electrode assemblies (MEAs). The influence of different hot-pressing conditions on the DMFC performance and various properties of the MEAs, in particularly on the properties of the anode, are investigated and compared to MEAs made by the conventional spray method. The highest DMFC performance is achieved using MEAs made by stenciling. It is also found that the membrane resistance (Rm), the resistance to proton transport within the catalyst layer (Rp) and the charge transfer resistance (Rct) towards the CH3OH oxidation reaction are lower for stenciled vs. sprayed anodes.

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 score0.060
Threshold uncertainty score0.200

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 head0.005
GPT teacher head0.197
Teacher spread0.192 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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