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Record W2523634565 · doi:10.1002/cjce.22691

Degradation of residual dyes in textile wastewater by ozone: Comparison between mixed and bubble column reactors

2016· article· en· W2523634565 on OpenAlexvenueno aff
Giuseppe Actis Grande, Giorgio Rovero, Silvio Sicardi, Mirco Giansetti

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsnot available
Fundersnot available
KeywordsDyeingWastewaterOzoneBubble column reactorPulp and paper industryDegradation (telecommunications)BubbleChemistryTextileTextile industryWaste managementChemical engineeringEnvironmental scienceMaterials scienceEnvironmental engineeringOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

A noticeable amount of dyes may remain in the wastewater downstream of dyeing facilities giving anaesthetic colourations as well as environmental concerns. Conventional biological treatment alone cannot guarantee a sufficient decolouration and tertiary treatments have to be necessarily considered. Two oxidation schemes by ozone were considered in this work. A bubble column reactor (as a benchmark, in agreement with industrial applications) and a recycle well‐mixed reactor were compared to reach the highest decolouration of standard dyes. In addition, hydrodynamic and ultrasonic cavitation were considered in the recycled well‐mixed reactor to intensify its performance. The decolouration analysis was carried out for two dye classes (reactive and disperse), characterized by very different physical and chemical features. It appeared that some benefit was brought by ultrasound cavitation in the case of disperse dye only, while the degradation of the reactive dye was not intensified by the above hydraulic phenomenon. Ozone treatment was protracted to obtain different decolouration degrees of wastewater generated by wool dyeing. The resulting water was tested as a recycled process fluid to prepare fresh dyeing liquors, where devising the minimum decolouration degree became one of the quality specifications for recycling water back to dyeing.

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 score0.126
Threshold uncertainty score0.233

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 head0.196
Teacher spread0.188 · 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

Citations12
Published2016
Admission routes1
Has abstractyes

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