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Record W2083739577 · doi:10.1021/ie051098z

Photodegradation of Benzoic Acid over Metal-Doped TiO<sub>2</sub>

2006· article· en· W2083739577 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.

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2006
Typearticle
Languageen
FieldEnergy
TopicTiO2 Photocatalysis and Solar Cells
Canadian institutionsWestern University
Fundersnot available
KeywordsDopantPhotocatalysisPhotodegradationMaterials scienceX-ray photoelectron spectroscopyInorganic chemistryDiffuse reflectance infrared fourier transformRaman spectroscopyMetalTitanium dioxideDopingPhotoluminescenceBenzoic acidNuclear chemistryChemistryChemical engineeringCatalysisOrganic chemistryOptics

Abstract

fetched live from OpenAlex

A modified sol−gel method was employed to synthesize metal-doped TiO 2 with varied dopant concentrations using titanium butoxide and metal nitrate hydrate as the precursors and hydrothermal posttreatment. The prepared samples were characterized by XRD, XPS, TEM, BET, UV−vis/diffuse reflectance, PZC measurement, Raman spectroscopy, photoluminescence, and fluorescence lifetime, while the photocatalytic activities were tested using benzoic acid as the model compound. Ga-doped TiO 2 exhibits the highest photoactivity among the prepared metal-doped TiO 2 photocatalysts. This is most likely due to the good dispersion of Ga dopant onto the surface of TiO 2, adequate surface area, and decrease of recombination center on the surface of Ga-doped TiO 2 photocatalyst. The optimum dopant concentration was found to be 0.1 wt % for Ga-doped TiO 2 .

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)0.001
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 score0.006
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.044
GPT teacher head0.278
Teacher spread0.234 · 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