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Record W4391486216 · doi:10.3390/min14020162

Chalcopyrite Leaching in Ferric Sulphate: The Effect of Fe3O4-CuFeS2 Galvanic Couple on the Cu Dissolution

2024· article· en· W4391486216 on OpenAlexaff
Kolela J. Nyembwe, Elvis Fosso‐Kankeu, F.B. Waanders, Bhekie B. Mamba, Martin Mkandawire

Bibliographic record

VenueMinerals · 2024
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsCape Breton University
FundersUniversity of South AfricaUniversity of JohannesburgNorth-West University
KeywordsDissolutionChalcopyriteLeaching (pedology)Galvanic cellFerricMagnetiteChemistryInorganic chemistryMetallurgyMaterials scienceCopperGeologyPhysical chemistry

Abstract

fetched live from OpenAlex

Galvanic interactions present alternative strategies to achieve a more efficient Cu dissolution from CuFeS2. The present work studied the interaction between chalcopyrite–magnetite (CuFeS2-Fe3O4) in acidified ferric sulphate Fe2(SO4)3-H2SO4 at a solution pH of 1.8 and a temperature of 25 or 50 °C. The addition of Fe3O4 to CuFeS2 forms a galvanic couple, which positively impacts the dissolution of Cu. The results showed that the presence of Fe3O4 led to high and fast Cu dissolution rates and decreased significantly the activation energy, from 83 to 57 kJ/mol. In addition to that, the solid residues revealed that CuFeS2 dissolution produced intermediate Cu-S-rich phases: CuS, Cu2S and Cu5FeS4, which appeared to envelop CuFeS2, had no observable intermediate phase while in the presence of Fe3O4. The results showed that 94% of Cu could be recovered after 5 h of leaching at 50 °C at a Fe3O4/CuFeS2 ratio of 4:1 and a 460 mV Ag/AgCl solution potential. The findings of this study present an option for efficient Cu dissolution from CuFeS2 in ferric sulphate at atmospheric pressure.

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)0.001
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 score0.875
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.253
Teacher spread0.240 · 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
Published2024
Admission routes1
Has abstractyes

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