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Record W2097730444 · doi:10.1139/s06-006

Behavior of complexing ligands during coagulationflocculation by ferric chloride: A comparative study between sewage water and an engineered colloidal model

2006· article· en· W2097730444 on OpenAlexvenueno aff
Antoine El Samrani, Naïm Ouaïni, Bruno Lartiges, Véronique Kazpard, A Ibrik, Zeinab Saad

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2006
Typearticle
Languageen
FieldEnergy
TopicIron oxide chemistry and applications
Canadian institutionsnot available
Fundersnot available
KeywordsFlocculationFerricChemistryCoagulationSulfateChloridePhosphateInorganic chemistryColloidOrganic chemistry

Abstract

fetched live from OpenAlex

In this work, a comparative study is conducted on sewage as an example of a natural water system and on an engineered colloidal model. The two water systems were treated by coagulation–flocculation with ferric chloride. Affinity of phosphate and sulfate used as complexing ligands to coagulant species was studied within the two systems. Aggregation dynamics were followed with jar tests and laser diffraction. Sulfate and phosphate were determined by using ion chromatography. Atomic absorption spectroscopy (AAS) and transmission electron microscopy coupled with energy dispersive X-ray spectrometry were used for elemental and ionic analysis of P, Fe, S, SO 4 , and PO 4 in supernatants and sediments. Investigation of ligands revealed that phosphate and iron(III) species make strong complexes that enhance aggregation velocity, whereas sulfate is weakly complexed with iron(III) species. It can be released in suspensions without any consequences on aggregation dynamics.Key words: aggregation, coagulant species, complexing ligands, coagulation, flocculation.

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 score0.229
Threshold uncertainty score0.341

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 head0.015
GPT teacher head0.242
Teacher spread0.227 · 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
Published2006
Admission routes1
Has abstractyes

Explore more

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