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Record W2795376325 · doi:10.1039/c8cp01315b

Unifying theoretical framework for deciphering the oxygen reduction reaction on platinum

2018· article· en· W2795376325 on OpenAlexafffund
Jun Huang, Jianbo Zhang, Michael Eikerling

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2018
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsBurnaby HospitalSimon Fraser University
FundersCentral South UniversityNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsTafel equationCatalysisElectrolyteElectrochemistryChemistryPlatinumOxygenOxygen reductionExchange current densityNanotechnologyElectrochemical energy conversionOxygen reduction reactionElectrodeCombinatorial chemistryChemical physicsMaterials scienceOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Rapid conversion of oxygen into water is crucial to the operation of polymer electrolyte fuel cells and other emerging electrochemical energy technologies. Chemisorbed oxygen species play double-edged roles in this reaction, acting as vital intermediates on one hand and site-blockers on the other. Any attempt to decipher the oxygen reduction reaction (ORR) must first relate the formation of oxygen intermediates to basic electronic and electrostatic properties of the catalytic surface, and then link it to parameters of catalyst activity. An approach that accomplishes this feat will be of great utility for catalyst materials development and predictive model formulation of electrode operation. Here, we present a theoretical framework for the multiple interrelated surface phenomena and processes involved, particularly, by incorporating the double-layer effects. It sheds light on the roles of oxygen intermediates and gives out the Tafel slope and exchange current density as continuous functions of electrode potential. Moreover, it develops the concept of a rate determining term, which should replace the concept of a rate determining step for multielectron reactions, and offers a new perspective on the volcano relation of the ORR.

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 categoriesMeta-epidemiology (narrow)
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 score0.062
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.258
Teacher spread0.245 · 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.

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

Citations106
Published2018
Admission routes2
Has abstractyes

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