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Enregistrement W2297775475 · doi:10.14288/1.0079242

The use of strong brine and HCl solutions to process nickel sulfide concentrates

2010· article· en· W2297775475 sur OpenAlexaff
Ganbold Malkhuuz

Notice bibliographique

RevuecIRcle (University of British Columbia) · 2010
Typearticle
Langueen
DomaineEngineering
ThématiqueMetal Extraction and Bioleaching
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésBrineNickelSulfideNickel sulfideChemistryEnvironmental science

Résumé

récupéré en direct d'OpenAlex

The mixture of hydrochloric acid and magnesium chloride is a good lixiviant for the processing of sulfide minerals, concentrates and matte samples. The proton activity in this mixture deviates positively from ideal activity. This enhances the leaching power to break sulfide lattices down and to dissolve metals into solution. Magnesium (chloride) was chosen because it is one of a few reusable salts among alkali and alkali earth metal chlorides. The thermodynamic properties of this mixture are best characterized by activity coefficients of contributing ions in solution. The activity coefficient of hydrochloric acid in this mixture was measured at a total ionic strength of two at temperatures of 25, 35, and 45°C applying the Electro Motive Force (EMF) measurement method. Further measurements at higher temperatures and higher ionic strengths were complicated due to unstable readings of the potentials. Therefore, a mathematical method published by Meissner was utilized to calculate the activity coefficients of hydrochloric acid and magnesium chloride in a mixture. Based on these calculations, individual ion activities were assigned using Bates’ equation and Jansz’s approach of applying variable water activities, hydration numbers and osmotic coefficients. Based on the individual ion activity, pH values were estimated for solutions where measurements were not applicable. As part of the thermodynamic studies of this mixture, the solubility limit of MgCl₂ in hydrochloric acid solutions was investigated. The solubility of MgCl₂ in water was measured as 485.6 g/l at 22°C and 557 g/l at 82.5°C. The solubility of MgCl₂ in 6m HCl solutions was measured as 243 g/l at 22°C and 452 g/l at 82.5°C. Furthermore, the leaching chemistry of individual sulfide minerals-pyrite, millerite, troilite, heazelwoodite, violarite, and chalcopyrite were investigated in MgCl₂-HC1 solutions. Pyrite was the most refractory mineral. About 6% iron was extracted in the mixture of 2m MgCl₂ and 3-10m of HCl at 60°C. Over 90% of iron was extracted from troilite in the mixture of 2m MgCl₂ and 3m HCl. Millerite dissolved at acid concentrations greater than 6m HCl. At 60°C, 60% of nickel was extracted in the mixture of 2m MgCl₂ and 10m HCl. The dissolution results of these minerals were consistent with the thermodynamic predictions. About 20% of the nickel from violarite was extracted in mixtures with 1-6m HCI. The nickel extractions were increased up to 30% in mixtures of 10m HCl. About 60% of the heazelwoodite was dissolved in the mixture of 2m MgCl₂ and 1m HCl. The heazelwoodite dissolution was consistent with the thermodynamic predictions described in section 2.2.6. In all above cases, the leaching time was 24 hours. Chalcopyrite partially leached (~22%) in the mixtures with 7m HCl at 100°C. It dissolved forming cupric chloride, ferric chloride and the hydrogen sulfide gas (RXN 4.4 in section 4.4.3). No phase transformation (copper enriched product such as covellite) was observed. The results of individual mineral leaching experiments suggested the possibilities and conditions to process commercial sulfide products in this mixture. Two sulfide concentrates and a matte sample supplied by BHP Billiton were studied. Low MgO concentrate that consists of mainly pentlandite and pyrrhotite yielded 95% Ni, 87% Fe, 81% Co and 58% Cu extractions in solutions of 8m HCl and 2m MgCl₂ with a retention time of 2 hours. The solid residue in this case contained mainly pyrite, talc and quartz. The high MgO concentrate that consists of mainly pentlandite yielded 95% Ni, 84% Fe, 75% Co and 19% Cu extractions in the mixtures of 6m HCl and 2m MgCl₂ at 100°C. The leach time was one hour. The leach residue in this case contained mostly quartz and talc. The addition of 0.5m cupric or ferric chloride to leach solutions of low MgO concentrate did not improve metal extractions due to the formation of copper and sulfur enriched layers on the particle surface. The reason is explained by the strong tendency of cupric or ferric ions to react with product gases such as H₂S and H₂ forming copper sulfide or elemental sulfur, respectively. The additions of either cupric or ferric chlorides to leach solutions of high MgO concentrate leaching also retarded metal dissolution. The reason of this low metal recovery is believed to be a formation of sulfur and oxidized layers on the surface of the particles. This low metal extraction is also explained by the same phenomenon as above in the case of ferric addition. The pentlandite, which is the main composition of the feed, remained substantially unleached. Nickel matte that mainly consisted of heazelwoodite yielded over 99% metal extractions in 6m acid solutions; however, the same metal extractions were obtained in 3m HCl mixtures with the exception of copper. The leach residue, where the highest metal extractions were obtained, consisted of 60% suredaite (a mixture of arsenic, sulfur and copper) in addition to 20% sulfur, according to the XRD and SEM-EDX. Low copper extraction from this sample was caused by the strong tendency of cupric ion to precipitate in the presence gases from heazelwoodite dissolution.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,971
Score d'incertitude au seuil0,992

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,016
Tête enseignante GPT0,187
Écart entre enseignants0,171 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2010
Routes d'admission1
Résumé présentoui

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