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Record W2111785156 · doi:10.1021/es200676z

Processing of Arsenopyritic Gold Concentrates by Partial Bio-Oxidation Followed by Bioreduction

2011· article· en· W2111785156 on OpenAlexafffund
Alex Hol, Renata D. van der Weijden, Gus Van Weert, Peter Kondos, C.J.N. Buisman

Bibliographic record

VenueEnvironmental Science & Technology · 2011
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsBarrick Gold (Canada)
FundersBarrick Gold Corporation
KeywordsSulfurChemistryPyriteHydrogen sulfideArsenopyriteSulfide mineralsSulfideEnvironmental chemistryTailingsInorganic chemistryMineralogyCopperOrganic chemistryChalcopyrite

Abstract

fetched live from OpenAlex

Gold is commonly liberated from sulfide minerals by chemical and biological oxidation. Although these technologies are successful, they are costly and produce acidic waste streams. Removal of mineral-sulfur to overcome the mineralogical barrier could also be done by bioreduction, producing hydrogen sulfide (H(2)S). To make the sulfur within these minerals available for bioreduction, the use of partial bio-oxidation as a pretreatment to oxidize the sulfides to elemental sulfur was investigated in gas lift loop reactor experiments. Experiments at 35 °C using a refractory concentrate showed that at pH 2 arsenopyrite is preferentially partially oxidized over pyrite and that elemental sulfur can be subsequently converted into H(2)S at pH 5 via bioreduction using H(2) gas. A single partial bio-oxidation/bioreduction treatment increased the gold recovery of the concentrate from 6% to 39%. As elemental sulfur seems to inhibit further oxidation by covering the mineral surface, several treatments may be required to reach a gold recovery >90%. Depending on the number of treatments this method could be an interesting alternative to bio-oxidation.

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 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 score0.025
Threshold uncertainty score0.379

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 studies0.0000.001
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 head0.007
GPT teacher head0.195
Teacher spread0.187 · 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

Citations9
Published2011
Admission routes2
Has abstractyes

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