MétaCan
Menu
Back to cohort
Record W2018441539 · doi:10.1179/174328508x283478

Recovery of zinc, gallium and indium from La Oroya zinc ferrite using Na<sub>2</sub>CO<sub>3</sub>roasting

2008· article· en· W2018441539 on OpenAlexfundno aff
P. C. Holloway, Thomas H. Etsell

Bibliographic record

VenueMineral Processing and Extractive Metallurgy Transactions of the Institutions of Mining and Metallurgy Section C · 2008
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Department of Energy
KeywordsRoastingZinc ferriteZincLeaching (pedology)GalliumCalcinationIndiumHydrometallurgyMetallurgyChemistryElectrowinningPrecipitationMaterials scienceInorganic chemistryNuclear chemistrySulfuric acidElectrolyteEnvironmental scienceCatalysis

Abstract

fetched live from OpenAlex

Process flowsheets for the recovery of zinc, indium and gallium from La Oroya zinc ferrite residue (19˙5%Zn, 26˙6%Fe, 0˙052%Ga, 0˙075%In) using Na2CO3 roasting are proposed. While several leaching flowsheets are discussed, the flowsheet where zinc ferrite is roasted with Na2CO3 and MnCO3, followed by two stages of leaching (hot water and H2SO4), iron reduction and precipitation of In and Ga as hydroxides, Fe as FeOOH and zinc as basic zinc sulphate from solution appears to be the most promising option for metals recovery from this material using Na2CO3 roasting. Sulphuric acid for leaching may be regenerated using either Na2SO4 metathesis or solvent extraction/ion exchange and Na2CO3 can be recovered for recycle to roasting from solution using precipitation and calcination of NaHCO3. Future research on these potential flowsheets is required, including possible methods for the recovery of iron, silver and gallium from the various process streams.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.035
GPT teacher head0.254
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), 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

Citations26
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueMineral Processing and Extractive Metallurgy Transactions of the Institutions of Mining and Metallurgy Section CSame topicExtraction and Separation ProcessesFrench-language works237,207