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Record W2086538382 · doi:10.2202/1542-6580.1243

Phenomenological Kinetics of Isothermal Wet Air Oxidation: Operating Severity Factor and Recalcitrance Index

2005· article· en· W2086538382 on OpenAlexaff
Khaled Belkacemi, Safia Hamoudi

Bibliographic record

VenueInternational Journal of Chemical Reactor Engineering · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsChemistryPollutantKineticsReactivity (psychology)Isothermal processAlkylMoleculeAcetic acidEnvironmental chemistryOrganic chemistryChemical engineeringThermodynamics

Abstract

fetched live from OpenAlex

In the present investigation, the kinetics governing wet air oxidation (WAO) of organic pollutants is modeled by two distinct parallel kinetic terms corresponding to a readily oxidizable and a recalcitrant structural parts of the pollutant molecule involving the concept of thermodynamic severity factor. The developed model was successfully applied to several classes of organic water pollutants including phenolic compounds as well as mono- and di-carboxylic acids. In the offshoot of the model, a recalcitrance index was proposed classifying the pollutant molecules according to their resistance to oxidation. For the carboxylic acids, it was found that the recalcitrance towards WAO was inversely correlated to the molecular size and weight. Acetic acid proved to be the more recalcitrant component. As for the phenolic compounds, the oxidation efficiency was shown to be affected by the nature of the substitutents present on the phenolic ring. The electron donating substitutents such as alkyl groups (CH3 or –C2H5) confer to the molecule an enhanced reactivity towards WAO. On the contrary, electron-accepting substitutents, such as methoxy groups, lower the oxidation and consequently enhance the recalcitrance.

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 score0.010
Threshold uncertainty score0.381

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 head0.008
GPT teacher head0.231
Teacher spread0.223 · 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

Citations4
Published2005
Admission routes1
Has abstractyes

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