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Record W4401478008 · doi:10.1016/j.mineng.2024.108873

Establishing an optimized flotation scheme for a complex Base-Metal sulfide ore using a modified xanthate reagent scheme

2024· article· en· W4401478008 on OpenAlexaff
Daniel S. Hamilton, Wonjae Chang, Kerry N. McPhedran

Bibliographic record

VenueMinerals Engineering · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMinerals Flotation and Separation Techniques
Canadian institutionsGlobal Institute for Water SecurityUniversity of Saskatchewan
Fundersnot available
KeywordsXanthateReagentSulfideBase metalBase (topology)Froth flotationScheme (mathematics)ChemistryMetalMetallurgyInorganic chemistryMaterials scienceMathematicsOrganic chemistry

Abstract

fetched live from OpenAlex

• Froth reagent scheme for complex base-metal sulphide ore. • Recoveries of 84.0% and 83.8% for chalcopyrite and sphalerite. • Optimum recovery at 3 min grinding and pH 6. • SEM images show co-occurring copper and zinc. Generating a flotation reagent scheme for a complex base-metal sulphide ore using reagents that are commonly found in mineral processing can be a challenging, complex process. Ensuring that optimum operating conditions including particle size, pH, types of reagents, and dosages of reagents are found is critical in establishing a foundation for future research. A modified xanthate reagent scheme was chosen using potassium amyl xanthate (PAX) as the collector, methyl isobutyl carbinol (MIBC) as the frother, copper sulphate as activator, carboxy methyl cellulose (CMC) and zinc sulphate as depressants. The operating conditions that generated the highest recoveries and grades for copper and zinc were found using a grinding time of 3 min and a slightly acidic medium of pH 6 achieving maximum recoveries of 84.0% and 83.8% for chalcopyrite and sphalerite, and grades of 3.9 and 21.0, respectively. These results allow for comparisons to industrial results with ore of a similar composition while simultaneously providing a baseline in which to evaluate the results of future, innovative research.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.717
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.062
GPT teacher head0.303
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.

Study designSimulation or modeling
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

Citations2
Published2024
Admission routes1
Has abstractyes

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