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Record W2797026340 · doi:10.30638/eemj.2018.048

REMOVAL OF AQUEOUS Cu(II) WITH NATURAL KAOLIN: KINETICS AND EQUILIBRIUM STUDIES

2018· article· en· W2797026340 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnvironmental Engineering and Management Journal · 2018
Typearticle
Languageen
FieldMaterials Science
TopicCrystallization and Solubility Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsKineticsAqueous solutionNatural (archaeology)ChemistryThermodynamicsChemical engineeringPhysical chemistryGeologyPhysicsEngineering

Abstract

fetched live from OpenAlex

Copper pollution is common across the world and has caused serious public health problems recently.Among the conventional methods, adsorption has proved effective, economic, versatile and simple for the removal of aqueous Cu(II) contaminants.Deposits of natural Kaolin are abundant around the world, and are regarded as valueless due to its limited usage in industry.In this study, the adsorption behavior of natural Kaolin towards Cu(II) was evaluated.According to the results, the isothermal adsorption data are well fitted with Sips model, and the adsorption capacity of natural Kaolin to Cu(II) is determined to be 76 mg/g.Several factors can affect the adsorption performance of Cu(II), including dosage of adsorbent, initial Cu(II) concentration, solution pH, temperature and contact time.The kinetics data are also well predicted by the pseudo-first order kinetics and the pseudo-second order kinetics; the equation of the intraparticle diffusion model could be considered as a supplement.The thermodynamic behavior reveals the endothermic and spontaneous nature of the adsorption.The mechanism for the adsorption behavior was studied based on XRD spectra, and ion-exchange reaction and surface complexation were regarded as predominant.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.778
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 head0.008
GPT teacher head0.212
Teacher spread0.204 · 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