Mineral Liberation Analysis – Automated Mineralogy
Liberation analysis is a forensic analysis of the minerals in the process metallurgy streams investigating the minerals and their texture in order to optimise the extraction process. Examination of the particles in the process streams determines the efficiency of the process of separating ore from the gangue minerals.
Feed, concentrate and tails
Liberation analysis
Improved recovery
Mineral Textures and Metallurgical Processing Parameters
The texture of the minerals is critical to determining the processing parameters.
- Mineral grain size versus particle size determines the target grinding size of the particles,
- Mineral associations determine the degree of floatability , dissolution and reagent consumers
- Mineral associations determine how hard the ore is the reagents required for
- Mineral chemistry determines the element stoichiometry and purity of the mineral
Mineral textural information is crucial to the design and optimisation of metallurgy processes. Automated mineralogy generates mineral textural information to optimise individual processes such as grind size, reagent, flotation and regrind strategies for your process. Samples can be taken from various points in the process and analysed in near real time. By acquiring this data in a timely fashion, you are able to fine tune your entire process on the fly to maximise recovery, reduce energy consumption and increase profitability.
The following graphic demonstrates where automated mineralogy can be implemented in your metallurgy process design to bring about process improvements including increased efficiency, increased recovery, lowering running costs, ultimately improving your bottom line.
Importance of Liberation Analysis
Liberation analysis is used to determine the degree to which valuable minerals are separated from gangue (worthless minerals or materials) in a sample of ore or rock. This analysis is particularly important in mineral processing and mining industries.
Determining Mineral Liberation
Correct and careful sample preparation is crucial for SEM-based liberation analysis to obtain an accurate representation of the grain shapes and sizes. At the AMI we have developed best practice sample preparation methods for a wide range of commodities.
Once prepared and loaded into the TESCAN TIMA at the AMI, the samples are scanned, and the images are carefully analysed to determine which minerals are “liberated” or separated from the gangue minerals. Some valuable minerals are enclosed within or attached to gangue minerals and are therefore not liberated, whereas discrete, free grains are classed as liberated.
Liberation analysis is crucial for optimising mineral processing operations as it helps mining companies understand the efficiency of their ore separation techniques. High liberation indicates that valuable minerals are well-separated from gangue, making it easier and more cost-effective to extract and process the valuable materials.
Determining the degree of liberation is essential for assessing the economic viability of a mining project. If valuable minerals are tightly bound to gangue minerals, the cost of separation and processing may outweigh the potential profit.
Mineral Liberation Analysis and the Mineral Content of a Deposit
Liberation analysis also aids in estimating the overall mineral content of a deposit accurately. By quantifying how much valuable mineral is effectively recoverable, mining engineers and geologists can make informed decisions about resource development.
Efficient liberation crucially reduces the environmental impact of mining operations. When valuable minerals are well-liberated, less waste material needs to be processed and disposed of, leading to reduced energy consumption and environmental disturbance.
Liberation Analysis and Specific Mineral Grades
For industries that rely on specific mineral grades and purities, liberation analysis ensures that the final product meets the required specifications. It helps maintain consistent quality and purity levels in mineral processing.