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Record W2565137896 · doi:10.1039/c6cp08055c

Mechanism and kinetics of the electrocatalytic reaction responsible for the high cost of hydrogen fuel cells

2016· article· en· W2565137896 on OpenAlexaff
Tao Cheng, William A. Goddard, Qi An, Hai Xiao, Boris V. Merinov, Sergey I. Morozov

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2016
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsProcess Simulations Limited (Canada)
FundersDivision of Chemical, Bioengineering, Environmental, and Transport SystemsNational Science Foundation
KeywordsMetadynamicsChemistryReaction mechanismHydrogenElectrolysis of waterKineticsActivation energyReaction rateElementary reactionChemical kineticsCatalysisPhysical chemistryComputational chemistryMolecular dynamicsElectrolysisElectrolyteOrganic chemistryElectrode

Abstract

fetched live from OpenAlex

O and O*; third, O* hydrolysis using surface water to produce two *OH and finally *OH hydration to water. Water formation is the rate-determining step (RDS) for potentials above 0.87 Volt, the normal operating range. Considering the Eley-Rideal (ER) mechanism involving protons from the solvent, we predict the free energy reaction barrier at 298 K for water formation to be 0.25 eV for an external potential below U = 0.87 V and 0.41 eV at U = 1.23 V, in good agreement with experimental values of 0.22 eV and 0.44 eV, respectively. With the mechanism now fully understood, we can use this now validated methodology to examine the changes upon alloying and surface modifications to increase the rate by reducing the barrier for water formation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.008
GPT teacher head0.210
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), 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

Citations62
Published2016
Admission routes1
Has abstractyes

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