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Record W2053219917 · doi:10.1179/cmq.2006.45.2.135

KINETICS OF TRITHIONATE DEGRADATION

2006· article· en· W2053219917 on OpenAlexfundno aff
N. AHERN, David Dreisinger, Gus Van Weert

Bibliographic record

VenueCanadian Metallurgical Quarterly · 2006
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaAngloGold AshantiBarrick Gold Corporation
KeywordsMaterials science

Abstract

fetched live from OpenAlex

Thiosulfate has shown promise as an alternative to cyanide for gold leaching. However, one of the limitations is high thiosulfate consumption. Thiosulfate degradation is not completely understood. Of the degradation products, trithionate is a concern in the resin recovery of gold and is persistent in solution. Very little is known about the expected behaviour of trithionate both with respect to its formation and to its interaction with other solution species.The focus of this work was to further the understanding of the behaviour of trithionate in gold leach solutions. −d[ S3O62− ]dt=(k3[ NH4+ ]+k2[ NH3 ]+k1[ OH− ]+k0[ S3O62− ]) The degradation kinetics was determined in systems resembling gold leaching solutions and a kinetic model was derived as expressed in Equation 1 for aqueous ammoniacal solutions. (1) The presence of lower concentrations of thiosulfate catalyzed the reaction, while excess thiosulfate inhibited it. Cupric copper was not found to have any effect under the conditions tested.L’hyposulfite s’est montré prometteur comme substitut du cyanure pour la lixiviation de l’or. Cependant, l’une des limitations est la consommation élevée d’hyposulfite. La dégradation de l’hyposulfite n’est pas entièrement comprise. Parmi les produits de la dégradation, le trithionate est une préoccupation dans la récupération à la résine de l’or et est persistant en solution. On connaît très peu du comportement attendu du trithionate tant en ce qui a trait à sa formation qu’à son interaction avec d’autres espèces en solution.L’objet de ce travail consistait à mieux comprendre le comportement du trithionate dans les solutions de lixiviation de l’or. On a determiné la cinétique de la dégradation dans des systèmes qui ressemblaient aux solutions de lixiviation de l’or et l’on a dérivé un modèle cinétique tel qu’exprimé à l’Équation 1 pour les solutions aqueuses ammoniacales. −d[ S3O62− ]dt=(k3[ NH4+ ]+k2[ NH3 ]+k1[ OH− ]+k0[ S3O62− ]) Les plus faibles concentrations d’hyposulfite agissaient comme catalyseur de la réaction alors que l’excès d’hyposulfite l’inhibait. On a trouvé que le cuivre cuivrique n’avait aucun effet sous les conditions évaluées.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.010
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.004

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 head0.006
GPT teacher head0.179
Teacher spread0.173 · 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

Citations9
Published2006
Admission routes1
Has abstractyes

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