$Biooxidation of refractory sulfide-bearing ore using feroplasma acidophilum: Efficiency assessment and machine learning based prediction$

Biooxidation of refractory sulfide-bearing ore using feroplasma acidophilum: Efficiency assessment and machine learning based prediction

The adhesive properties of microorganisms on the surface of minerals play an important role in the biooxidation efficiency of sulfidic refractory gold ores. In this research, the simultaneous effects of monosaccharides, ore content, pyrite content, and time on the activity and growth rate of Ferropl...

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Bibliographic Details
Main Authors:	Mohammad Hossein Karimi Darvanjooghi, Usman T. Khan, Sara Magdouli, Satinder Kaur Brar
Format:	Article
Language:	English
Published:	Elsevier 2024-01-01
Series:	Current Research in Biotechnology
Subjects:	Gold recovery Biooxidation Experimental data Mchine learning Genetic programming Artificial neural network model
Online Access:	http://www.sciencedirect.com/science/article/pii/S2590262824000054

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