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Record W2954518178 · doi:10.1039/c9ee00867e

Non-PGM electrocatalysts for PEM fuel cells: effect of fluorination on the activity and stability of a highly active NC_Ar + NH<sub>3</sub> catalyst

2019· article· en· W2954518178 on OpenAlexafffund
Gaixia Zhang, Xiaohua Yang, Marc Dubois, Michael Herraiz, Régis Chenitz, Michel Lefèvre, Mohamed Cherif, François Vidal, Vassili P. Glibin, Shuhui Sun, Jean‐Pol Dodelet

Bibliographic record

VenueEnergy & Environmental Science · 2019
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsWestern UniversityInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of CanadaElectrochemical SocietyChina Scholarship CouncilInstitut national de la recherche scientifiqueInnovationsfondenToyota USA
KeywordsCatalysisProton exchange membrane fuel cellChemistryFuel cellsInorganic chemistryChemical engineeringMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

F 2 -Fluorination of Fe/N/C catalysts poisons FeN 4 , but not CNx sites. Main causes of instability in PEMFCs are either FeN 4 demetalation for Fe/N/C or H 2 O 2 when FeN 4 sites are poisoned by fluorination or absent as in MOF_CNx_Ar + NH 3 .

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)0.001
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 score0.009
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.003
GPT teacher head0.187
Teacher spread0.183 · 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

Citations82
Published2019
Admission routes2
Has abstractyes

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