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Bioleaching Modeling-A Review.
Saldaña, Manuel; Jeldres, Matías; Galleguillos Madrid, Felipe M; Gallegos, Sandra; Salazar, Iván; Robles, Pedro; Toro, Norman.
Afiliación
  • Saldaña M; Faculty of Engineering and Architecture, Arturo Prat University, Iquique 1110939, Chile.
  • Jeldres M; Departamento de Ingeniería Química y Procesos de Minerales, Universidad de Antofagasta, Antofagasta 1270300, Chile.
  • Galleguillos Madrid FM; Departamento de Ingeniería Química y Procesos de Minerales, Universidad de Antofagasta, Antofagasta 1270300, Chile.
  • Gallegos S; Centro de Desarrollo Energético Antofagasta, Universidad de Antofagasta, Antofagasta 1271155, Chile.
  • Salazar I; Faculty of Engineering and Architecture, Arturo Prat University, Iquique 1110939, Chile.
  • Robles P; Departamento de Ingeniería Civil, Universidad Católica del Norte, Antofagasta 1270709, Chile.
  • Toro N; Escuela de Ingeniería Química, Pontificia Universidad Católica de Valparaíso, Valparaíso 2340000, Chile.
Materials (Basel) ; 16(10)2023 May 18.
Article en En | MEDLINE | ID: mdl-37241440
The leaching of minerals is one of the main unit operations in the metal dissolution process, and in turn it is a process that generates fewer environmental liabilities compared to pyrometallurgical processes. As an alternative to conventional leaching methods, the use of microorganisms in mineral treatment processes has become widespread in recent decades, due to advantages such as the non-production of emissions or pollution, energy savings, low process costs, products compatible with the environment, and increases in the benefit of low-grade mining deposits. The purpose of this work is to introduce the theoretical foundations associated with modeling the process of bioleaching, mainly the modeling of mineral recovery rates. The different models are collected from models based on conventional leaching dynamics modeling, based on the shrinking core model, where the oxidation process is controlled by diffusion, chemically, or by film diffusion until bioleaching models based on statistical analysis are presented, such as the surface response methodology or the application of machine learning algorithms. Although bioleaching modeling (independent of modeling techniques) of industrial (or large-scale mined) minerals is a fairly developed area, bioleaching modeling applied to rare earth elements is a field with great growth potential in the coming years, as in general bioleaching has the potential to be a more sustainable and environmentally friendly mining method than traditional mining methods.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Materials (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Chile Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Materials (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Chile Pais de publicación: Suiza