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Record W2107805730 · doi:10.1002/cjce.21849

Optimisation of photo‐Fenton‐like degradation of aqueous polyacrylic acid using Box‐Behnken experimental design

2013· article· en· W2107805730 on OpenAlexafffundvenue
Samira Ghafoori, Mehrab Mehrvar, Philip K. Chan

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBox–Behnken designResponse surface methodologyPolyacrylic acidAqueous solutionDegradation (telecommunications)Design of experimentsStatistical analysisChemistryMaterials scienceChemical engineeringChromatographyMathematicsComputer scienceComposite materialPolymerOrganic chemistryEngineeringStatistics

Abstract

fetched live from OpenAlex

Abstract The effectiveness of photo‐Fenton‐like process to degrade aqueous polyacrylic acid (PAA) is investigated in a batch recirculation system using two photoreactors in series. The response surface methodology (RSM) using the Box–Behnken experimental design combined with quadratic programming is employed for the experimental design, the statistical analysis and the optimisation. The effects of the initial concentration of PAA, the initial concentration of H 2 O 2 :Fe 3+ , pH and the recirculation rate on the percent removal of total organic carbon (TOC)and the ‘pseudo’‐second order rate constant as the process responses are studied. The statistical analysis of the results indicates a satisfactory prediction of the system behaviour by the developed quadratic models. Optimum operating conditions to maximise the percent TOC removal are also determined.

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)0.000
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 score0.072
Threshold uncertainty score0.674

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 head0.016
GPT teacher head0.204
Teacher spread0.189 · 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

Citations38
Published2013
Admission routes3
Has abstractyes

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