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Record W2001222972 · doi:10.1021/ie061586m

Removal of Methyl Mercaptide by Iron/Cerium Oxide−Hydroxide in Anoxic and Oxic Alkaline Media

2007· article· en· W2001222972 on OpenAlexafffund
Cătălin Florin Petre, Faı̈çal Larachi

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryHydroxideAnoxic watersInorganic chemistryOxideSulfurEnvironmental chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The oxidation of methyl mercaptide by Fe/Ce oxide−hydroxide was studied as a potential approach to deal with the methyl mercaptan contamination from total reduced sulfur (TRS) emissions in the pulp and paper industry. The reaction was studied in aqueous solutions at 22 °C and different alkaline pH values (10.5−12) both in anoxic and oxic conditions. Mercaptide reactivity was strongly dependent on pH in anoxia, whereas in oxic conditions it was noticeably higher but tributary of dissolved oxygen (DO 2 ). Interference with bisulfide comixed with mercaptide caused an inhibition in the conversion for both pollutants. Such inhibition was due to the incipient polysulfides formed via bisulfide oxidation. On the contrary, the mercaptide conversion was found to improve at the expense of bisulfide when large quantities of exogenous polysulfides were present initially in the reaction medium. The conversion of mercaptide was unaffected with the comixing of dimethyl sulfide. The oxidation of methyl mercaptide by the O 2 /Fe/Ce oxide−hydroxide system did not affect the reoxidative regeneration of surface Fe(III) by DO 2 . This feature pinpoints the sine qua none condition for a redox process based on the O 2 /Fe/Ce oxide−hydroxide system to remove methyl mercaptan in pulp and paper emissions.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.858

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.038
GPT teacher head0.304
Teacher spread0.266 · 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
Published2007
Admission routes2
Has abstractyes

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