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Record W1968217126 · doi:10.1021/ie900906e

CFD Modeling of Metronidazole Degradation in Water by the UV/H<sub>2</sub>O<sub>2</sub> Process in Single and Multilamp Photoreactors

2010· article· en· W1968217126 on OpenAlexafffund
Masroor Mohajerani, Mehrab Mehrvar, Farhad Ein‐Mozaffari

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAlkalinityHydrogen peroxideChemistryAqueous solutionDistilled waterDegradation (telecommunications)UltravioletTurbulenceAnalytical Chemistry (journal)ChromatographyMaterials scienceThermodynamicsOrganic chemistry

Abstract

fetched live from OpenAlex

A dynamic model for the degradation of aqueous metronidazole by hydrogen peroxide and ultraviolet irradiation processes (UV/H 2 O 2 ) as an advanced oxidation technology (AOT) in a single lamp tubular photoreactor as well as in a multilamp tubular photoreactor is developed. The model contains the main chemical and photochemical reactions in a medium flowing in the turbulent regime. The optimal hydrogen peroxide concentrations of 75, 150, and 200 mg L −1 were predicted for different alkalinity concentrations of 0, 1.5, and 3 μM, respectively. The model is validated with distilled water as well as alkaline water at different alkalinity concentrations. The model is validated by using the experimental data reported in the open literature. The velocity field and concentration profiles for the turbulent flow using the k −ε model are determined by computational fluid dynamics (CFD).

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)0.001
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 score0.042
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.034
GPT teacher head0.273
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 teacher head, 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

Citations34
Published2010
Admission routes2
Has abstractyes

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