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Record W2276589167 · doi:10.1021/acsami.5b10234

High Efficiency Photoelectrocatalytic Methanol Oxidation on CdS Quantum Dots Sensitized Pt Electrode

2016· article· en· W2276589167 on OpenAlexafffund
Chunyang Zhai, Mingshan Zhu, Fenzhi Pang, Duan Bin, Cheng Lü, M. Cynthia Goh, Ping Yang, Yukou Du

Bibliographic record

VenueACS Applied Materials & Interfaces · 2016
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsUniversity of Toronto
FundersPriority Academic Program Development of Jiangsu Higher Education InstitutionsNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsMaterials scienceCyclic voltammetryX-ray photoelectron spectroscopyChronoamperometryDielectric spectroscopyCadmium sulfidePhotocatalysisPhotocurrentDiffuse reflectance infrared fourier transformMethanolVisible spectrumQuantum dotElectrodeCadmium selenidePhotochemistryCatalysisElectrochemistryInorganic chemistryChemical engineeringNanotechnologyChemistryOptoelectronicsOrganic chemistry

Abstract

fetched live from OpenAlex

A cadmium sulfide quantum dots sensitized Pt (Pt-CdS) composite was synthesized using a solvothermal method and characterized by transmission electron microscopy (TEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and UV-vis diffuse reflectance spectroscopy. The catalytic properties of the as-prepared electrode for methanol oxidation were evaluated by cyclic voltammetry (CV), chronoamperometry, electrochemical impedance spectrum (EIS) and photocurrent responses. The as-prepared Pt-CdS electrode displayed a significant enhancement in the electrocatalytic activity and stability for methanol oxidation in the presence of visible light irradiation. The synergistic effect of both the electro- and photocatalytic reaction contributes to this enhanced catalytic performance. Our result suggests a new paradigm to construct photoelectrocatalysts with high performance and good stability for direct methanol fuel cells with the assistance of visible-light illumination.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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

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 head0.009
GPT teacher head0.248
Teacher spread0.239 · 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

Citations135
Published2016
Admission routes2
Has abstractyes

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