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Record W2407373136 · doi:10.1515/ijcre-2016-0024

Photodegradation Efficiencies in a Photo-CREC Water-II Reactor Using Several TiO <sub>2</sub> Based Catalysts

2016· article· en· W2407373136 on OpenAlex
Benito Serrano, Jesus Moreira del Rio, Jesus Fabricio Guayaquil, Hugo de Lasa

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

VenueInternational Journal of Chemical Reactor Engineering · 2016
Typearticle
Languageen
FieldEnergy
TopicTiO2 Photocatalysis and Solar Cells
Canadian institutionsWestern University
Fundersnot available
KeywordsAnatasePhotodegradationPhotocatalysisCatalysisPhenolPhotochemistryChemical engineeringCrystallinityMaterials scienceChemistryOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

Abstract This study reports phenol degradation using several TiO 2 photocatalysts (DP25, Anatase 1, Hombikat UV-100, Anatase 2) in a Photo-CREC Water-II Reactor. The physicochemical properties of the photocatalysts used, such as crystallinity, superficial area, and pore size distribution are reported. Reactor efficiencies are calculated using both Quantum Yields (QYs) and Photochemical and Thermodynamic Efficiency Factors (PTEFs). This is accomplished using phenol and phenol intermediate photoconversion rates. This allows the determination of hydroxyl radical consumption rates, at every step of the photodegradation process. With these data, and with the absorbed photon rates, energy efficiencies are calculated. It is shown that for the best performing photo catalysts the maximum QYs reach 50 % levels. These favourable photoconversion efficiencies confirm the critical importance of having available highly performing photocatalysts and photoreactors, such is the case of Photo-CREC Water-II Reactor unit.

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)0.000
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 score0.013
Threshold uncertainty score0.622

Codex and Gemma teacher scores by category

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 head0.010
GPT teacher head0.218
Teacher spread0.208 · 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