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Record W2045969791 · doi:10.1021/ie071637v

Aqueous Metronidazole Degradation by UV/H<sub>2</sub>O<sub>2</sub> Process in Single-and Multi-Lamp Tubular Photoreactors: Kinetics and Reactor Design

2008· article· en· W2045969791 on OpenAlexafffund
Melody Blythe Johnson, Mehrab Mehrvar

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAqueous solutionChemistryKineticsDegradation (telecommunications)BicarbonateHydrogen peroxideMetronidazoleChromatographyReaction rate constantNuclear chemistryAnalytical Chemistry (journal)Organic chemistry

Abstract

fetched live from OpenAlex

A kinetic model was developed to predict the removal of aqueous metronidazole utilizing the UV/H 2 O 2 process. The rate constant for the reaction between metronidazole and hydroxyl radicals was determined to be 1.98 × 10 9 M −1 s −1 . The model was able to predict an optimal initial H 2 O 2 dose and the inhibitory effects of high H 2 O 2 doses and bicarbonate ions in the aqueous solution. Simulations were performed for three different photoreactors treating a 6 μM solution of metronidazole at various influent H 2 O 2 doses and photoreactor radii. The predicted removal rates of metronidazole were 4.9−13% and 14−41% for the single-lamp and multilamp photoreactors, respectively. Selection of a photoreactor radius for maximum metronidazole removal varied with influent H 2 O 2 concentration. The lowest operational cost of $0.05 per mmol removed was projected for the multilamp photoreactor. Operationally, it was cost-effective to utilize higher UV lamp output (36W), while keeping influent H 2 O 2 concentration low (25 mg/L).

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)0.001
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 score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.100
GPT teacher head0.300
Teacher spread0.199 · 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

Citations67
Published2008
Admission routes2
Has abstractyes

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