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Record W2617706228 · doi:10.1039/c7cc02113e

Insights into the mechanism of electrocatalysis of the oxygen reduction reaction by a porphyrinic metal organic framework

2017· article· en· W2617706228 on OpenAlexaff
Mathieu Lions, Jean Bernard Tommasino, Raphaël Chattot, Brian Abeykoon, Nathalie Guillou, Thomas Devic, Aude Demessence, Luis Cardenas, Frédéric Maillard, Alexandra Fateeva

Bibliographic record

VenueChemical Communications · 2017
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsCanadian Nautical Research Society
FundersUniversité de LyonCentre National de la Recherche Scientifique
KeywordsElectrocatalystOxygen reduction reactionChemistryMechanism (biology)PhotochemistryMetal-organic frameworkReduction (mathematics)OxygenReaction mechanismOxygen reductionCombinatorial chemistryCatalysisElectrochemistryOrganic chemistryElectrodeAdsorptionPhysical chemistry

Abstract

fetched live from OpenAlex

Metal Organic Frameworks (MOFs) have been recently proposed as promising electrocatalysts, yet the exact nature of the mechanisms in play has not been addressed in depth. By comparing the electrocatalytic activity of a MOF for the oxygen reduction reaction (ORR) and the corresponding molecular building units through electrochemical techniques, here, we investigate the nature of the catalytic sites, their redox states and the electron transfer pathways.

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)0.001
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 score0.045
Threshold uncertainty score0.579

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.001
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 head0.013
GPT teacher head0.247
Teacher spread0.234 · 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

Citations84
Published2017
Admission routes1
Has abstractyes

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