Thesis
Development of a geometallurgical data set for the prediction of operating conditions to beneficiate base metal sulphide ore via flotation
Honours, Murdoch University
2017
Abstract
The optimisation and process development surrounding the beneficiation of nickelcopper sulphide ores is of fundamental importance when considering the continued rise in global demand for base metals. The selective sequential flotation of these ores is accompanied with various processing challenges due to the low-grade and mineralogical complexity associated with such deposits.
One of the greatest challenges faced during the flotation stage is the successful separation of the nickel and copper valuable minerals from the pyrrhotite gangue, significantly decreasing the grade and recovery of the final products. Utilisation of the TETA/sulphite depressant system has proven to significantly improve the flotation process, however its dosage requirements have been found to vary extensively between ore types. The investigations undertaken throughout this thesis project and the subsequent findings discussed in this report have allowed for a greater insight involving this system and its influence on the selective sequential flotation process.
The research undertaken throughout this project focuses on the mineralogy of nickelcopper sulphide ores and their subsequent concentration. Mineralogical and metallurgical analysis of this work has found that the individual mineral compositions within an ore have a large impact of its response to flotation processes and the successful separation of copper and nickel concentrates.
This thesis paper emphasises the fundamental importance of a holistic approach in order to understand the interactions and mechanisms involved in the selective flotation of nickel-copper sulphides. This will allow for the optimisation and development of operations with improved process control systems and the ability to predict mineral flotation behaviours with variations in ore type.
Details
- Title
- Development of a geometallurgical data set for the prediction of operating conditions to beneficiate base metal sulphide ore via flotation
- Authors/Creators
- Lia Cherico
- Contributors
- Aleksandar Nikoloski (Supervisor)
- Awarding Institution
- Murdoch University; Honours
- Identifiers
- 991005541980807891
- Murdoch Affiliation
- School of Engineering and Information Technology
- Language
- English
- Resource Type
- Thesis
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