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Record W2144204054 · doi:10.5539/ijc.v2n2p10

Photocatalytic Degradation of Phenol using Fe-TiO2 by Different Illumination Sources

2010· article· en· W2144204054 on OpenAlexvenueno aff
Reyad Shawabkeh, Omar A. Khashman, Gasan I. Bisharat

Bibliographic record

VenueInternational Journal of Chemistry · 2010
Typearticle
Languageen
FieldEnergy
TopicTiO2 Photocatalysis and Solar Cells
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryPhenolAqueous solutionPhotocatalysisTitanium dioxideReaction rate constantDegradation (telecommunications)Visible spectrumIrradiationCatalysisNuclear chemistryPhotochemistryHydrothermal circulationKineticsInorganic chemistryChemical engineeringOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

A Fe-doped titanium dioxide (Fe-TiO2) was prepared using hydrothermal method and used for degradation of phenol from aqueous solution. The samples were characterized by X-ray diffraction (XRD) and showed a presence of both TiO2 and Fe2O3 peaks. The photocatalytic activity of Fe-TiO2 catalyst was evaluated for oxidation of phenol in aqueous solution using different illumination sources. Visible light irradiation from sun, UV light sources with 190 and 390 nm, fluorescence and dark environment were used and found that the degradation of phenol was in the order of 7.8%, 12%, 7.5%, 6.8% and 5% obtained after 24 h, respectively. It was found that the increase in exposure time to UV, the increase in solution temperature and pH have increased the rate of phenol degradation in solution. This rate was best fitted using first order kinetic model with reaction constant of .

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 score0.002
Threshold uncertainty score0.005

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)0.0000.000

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 head0.009
GPT teacher head0.245
Teacher spread0.235 · 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

Citations23
Published2010
Admission routes1
Has abstractyes

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