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Record W2791302263 · doi:10.1002/ente.201700934

The Influence of Pt Surface Area on the Photo‐Enhancement of the Methanol Oxidation Reaction

2018· article· en· W2791302263 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnergy Technology · 2018
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsOntario Tech University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMethanolCatalysisIrradiationPhotochemistryChemistryRedoxPhotocatalysisInorganic chemistryMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The methanol oxidation reaction (MOR) on both Pt/TiO 2 /C and Pt/C‐based electrodes can be photo‐enhanced by illuminating the electrodes with UV light. This fact has called into question the role of TiO 2 in the photo‐enhancement of MOR when Pt is present. To examine this further, we have studied the change in the photo‐enhancement of methanol electro‐oxidation with Pt surface area. For each catalyst, there was greater MOR activity in the presence of UV‐irradiation. However, upon potential cycling, there was a faster decline in MOR activity in the presence of UV‐irradiation compared to the MOR activity in the dark. A linear relation between the decay in methanol oxidation current with the decay in Pt surface area for both catalysts was observed. This strongly suggests that irradiation enhances the methanol oxidation process on the Pt surface. When TiO 2 is present, it has a synergetic electronic effect that further enhances the oxidation process on the Pt surface.

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.

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 score0.233
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.215
Teacher spread0.208 · 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