Advancements in the application and mechanism of fine-grained mineral flotation collectors
Notice bibliographique
Résumé
The poor floatability of fine- and ultrafine-grained minerals, including sulfide and oxide minerals, is a huge issue confronting the mineral industry. Collectors are critical to the flotation of fine-grained minerals; therefore, developing high efficiency collectors has always been a hot research topic for industries and academia. This work has systematically reviewed the advancements in the development of collectors for fine mineral flotation in the last decades as well as provides an outlook for prospective studies. Collectors can be divided into sulfide and oxide mineral collectors, which can be further divided into ionic collectors, nonionic collectors, nonpolar oily collectors, nanocollectors, and biologic collectors based on their chemical composition. For sulfide minerals, ionic collectors mainly include xanthate, phosphate, and diethyldithiocarbamate, which are soluble in water and are able to dissociate sulfur-containing anions to interact with sulfide minerals. Some oily collectors and nanocollectors can also be used for the flotation of ultrafine sulfide minerals. For oxide minerals, the commonly used anionic collectors are hydroxamate, phosphate, arsenate, and fatty acid, while cationic collectors mainly comprise amine collectors. Nonionic and biologic collectors are used in oxide mineral flotation. Mechanisms underpinning the adsorption of collectors on the mineral surface include electrostatic interactions, chelation interactions, hydrogen bonding, chemical bonding, and metal-ion coordination. In addition, composite collectors, such as anionic/anionic collectors, anionic/cationic collectors, cationic/cationic collectors, and ionic/nonionic collectors, exhibit high collection capability for fine-grained minerals compared to single collectors. This is because they can promote collector adsorption on mineral surfaces through a series of synergistic interactions, such as co-adsorption, charge compensation, function complementarity, and variations in the critical micelle concentration. The rapid development of computational chemistry and artificial intelligence can help in investigating the quantitative relationship between the molecular structures of collectors and their collecting capability for fine minerals, thereby promoting the development of highly efficient novel collectors that uses shorter time for flotation. Increased effort is required for the development and utilization of harmless green collectors due to the rigid environmental requirement, and they are vital to the development of the mineral industry. In addition, nanocollectors will also gain increasing attention due to their unique physical and chemical properties and advantages over conventional collectors. Therefore, this paper is of great guiding significance for the development and application of fine-grained mineral flotation collectors.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».