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Record W2107451193 · doi:10.1039/c2cp44270a

RuO2/TiSi2/graphene composite for enhanced photocatalytic hydrogen generation under visible light irradiation

2012· article· en· W2107451193 on OpenAlexaff
Zhigang Mou, Shunli Yin, Mingshan Zhu, Yukou Du, Xiaomei Wang, Ping Yang, Junwei Zheng, Cheng Lü

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2012
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsUniversity of Toronto
FundersPriority Academic Program Development of Jiangsu Higher Education InstitutionsNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsGraphenePhotocatalysisMaterials scienceComposite numberX-ray photoelectron spectroscopyOxideDiffuse reflectance infrared fourier transformScanning electron microscopeFourier transform infrared spectroscopyHydrogen productionVisible spectrumHydrogenChemical engineeringPhotochemistryNanotechnologyChemistryComposite materialOptoelectronicsCatalysisOrganic chemistry

Abstract

fetched live from OpenAlex

A novel composite composed of TiSi(2), graphene and RuO(2) nanoparticles was fabricated by a one-pot deposition method using reduced graphene oxide (RGO) as a supporting matrix and RuCl(3) as the RuO(2) precursor. The resulting RuO(2)/TiSi(2)/RGO composite was characterized by scanning electron microscopy, X-ray diffraction, Fourier transform infrared spectra, X-ray photoelectron spectroscopy, UV-vis diffuse reflectance spectra, photoelectrical response and electrochemical impedance spectra. The results indicated that the three components in the composite were effectively contacted, thus facilitating the photogenerated charges transfer and separation through multiple routes. By using the composite as a photocatalyst for visible-light water splitting the average hydrogen production rate could reach 97.5 μmol h(-1) g(-1), which is higher than that from RuO(2)/TiSi(2) and pure TiSi(2) systems under the same conditions.

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 score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.016
GPT teacher head0.275
Teacher spread0.259 · 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

Citations39
Published2012
Admission routes1
Has abstractyes

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