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Record W3195354198 · doi:10.2166/wst.2021.309

Amberlite IRC-718 ion chelating resin extraction of hazardous metal Cr (VI) from aqueous solutions: equilibrium and theoretical modeling

2021· article· en· W3195354198 on OpenAlexaff
Abdelhamid Addala, Moussa Boudiaf, Maria Elektorowicz, Embarek Bentouhami, Yacine Bengeurba

Bibliographic record

VenueWater Science & Technology · 2021
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsConcordia University
FundersDirection Générale de la Recherche Scientifique et du Développement Technologique
KeywordsAmberliteChemistryChromiumAdsorptionIon exchangeIon-exchange resinAqueous solutionLangmuir adsorption modelInorganic chemistryMetalMetal ions in aqueous solutionIonPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Under varied conditions, the IRC 718 ion-exchange resin is used to extract chromium (VI) ions from aqueous solutions. On chromium (VI) removal effectiveness, the effects of adsorption dosage, contact time, beginning metal concentration, and pH were examined. The batch ion exchange process reached equilibrium after around 90 minutes of interaction. With an initial chromium (VI) concentration of 0.5 mg/dm3, the pH-dependent ion-exchange mechanism revealed maximal removal in the pH 2.0–10 range. The adsorption mechanism occurs between Cr (VI) determined as the electron acceptor, and IRC 718 determined as the electron donor. The equilibrium ion-exchange potential and ion transfer quantities for Amberlite IRC 718 were calculated using the Langmuir adsorption isotherm model. The overall ion exchange capacity of the resin was determined to be 187.72 mg of chromium (VI)/g of resin at an ideal pH of 6.0.

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 score0.392
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.254
Teacher spread0.238 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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