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Record W1975656500 · doi:10.1081/ss-120023417

Separation of Cobalt from a Nickel-Hydrometallurgical Effluent Using an Emulsion Liquid Membrane

2003· article· en· W1975656500 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

VenueSeparation Science and Technology · 2003
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChemistryCobaltNickelExtraction (chemistry)EmulsionHydrometallurgyCobalt extraction techniquesChlorideMembraneInorganic chemistryEffluentAqueous solutionAqueous two-phase systemChromatographyOrganic chemistrySulfuric acidWaste management

Abstract

fetched live from OpenAlex

The mechanism of cobalt extraction by a tri-alkyl-amine hydrochloride (TAAHCl) was studied. Based on extraction solution chemistry, a mathematical expression was derived to identify metal transfer mechanisms. Both experimental results and theoretical consideration identified anions as the most favorable species for ion exchange with chloride anions in protonated TAAHCl. A new emulsion liquid membrane (ELM) system using TAAHCl as carriers was tested for the separation of cobalt from a nickel hydrometallurgical waste effluent. The effect of complex agent addition, carrier concentration, and acidity of the internal and external aqueous phases on cobalt extraction efficiency was investigated. Under optimum conditions, the enrichment of cobalt with a recovery rate of 99.8% was obtained by a one-stage process. The treated effluent contained mainly nickel, which is suitable for further nickel recovery, while the cobalt in the separated internal phase can be recovered as a value added by-product.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score0.475

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 studies0.0000.000
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 head0.022
GPT teacher head0.319
Teacher spread0.297 · 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