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Record W2916164677 · doi:10.1149/2.0661904jes

Editors' Choice—Methanol Electrooxidation with Platinum Decorated Hematene Nanosheet

2019· article· en· W2916164677 on OpenAlexaff
Zishuai Zhang, Minnan Ye, Edward J. Harvey, Géraldine Merle

Bibliographic record

VenueJournal of The Electrochemical Society · 2019
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsMontreal General HospitalMcGill University
Fundersnot available
KeywordsNanosheetElectrocatalystCyclic voltammetryMethanolMaterials scienceScanning electron microscopeExfoliation jointX-ray photoelectron spectroscopyPlatinumOxideTransmission electron microscopyChemical engineeringAnodeCatalysisMethanol fuelInorganic chemistryGrapheneChemistryElectrodeElectrochemistryNanotechnologyComposite materialOrganic chemistryMetallurgy

Abstract

fetched live from OpenAlex

Developing a durable electrocatalyst with a high methanol oxidation reaction activity is highly important for anode design in direct methanol fuel cells. To that end, Pt-hematene sheets have been successfully synthesized by ultrasonic exfoliation followed by a double pulse deposition strategy to adjust the Pt loading. The morphology, structure, and composition of this new class of Pt decorated metal oxide nanosheet have been characterized by transmission electron microscopy, scanning electron microscopy and X-ray photoelectron spectroscopy. Electrocatalytic characteristics have been systematically investigated by cyclic voltammetry and compared with commercial Pt/C catalyst. The novel Pt-hematene sheets exhibit a good mass activity with a low peak potential but most of all show an enhanced tolerance to the intermediates of methanol oxidation.

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)0.002
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0230.012

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 head0.004
GPT teacher head0.204
Teacher spread0.200 · 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

Citations12
Published2019
Admission routes1
Has abstractyes

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Same venueJournal of The Electrochemical SocietySame topicElectrocatalysts for Energy ConversionFrench-language works237,207