Improving Molybdenum Flotation Efficiency and Recovery

Achieving high molybdenum recovery and concentrate grade is paramount for economic viability and resource efficiency. However, flotation processes often face challenges like low recovery rates and suboptimal efficiency due to factors like ore variability, reagent imbalance, and suboptimal operating conditions. Based on systematic research and optimization studies , here are key strategies to significantly improve Mo flotation performance:

Optimize Flotation Reagent Regime:

Collector Selection & Dosage: This is paramount. Test different collectors (e.g., specific xanthates, thiocyanates) tailored to the ore's mineralogy. Determine the optimal dosage through rigorous testing. Under-dosing leads to poor recovery; over-dosing reduces selectivity, increases costs, and can float unwanted minerals. Target maximum hydrophobicity of molybdenite.

Frother Optimization: Choose frothers (e.g., MIBC, Pine Oil) that generate stable, fine, and uniform bubbles (~0.2mm diameter is often optimal). Fine bubbles provide a larger surface area for particle attachment. Optimize dosage for sufficient froth stability without excessive viscosity.

Strategic Use of Modifiers & Depressants:

pH Modifiers: Maintain pulp pH within the optimal range (typically 10-11 for Mo). Lime is commonly used to achieve this alkaline environment, enhancing collector action and depressing pyrite. Precise pH control is critical.

Depressants: Use depressants (e.g., Sodium Silicate, starches, tannins) effectively to suppress gangue minerals (especially silicates and sulfides like pyrite). This improves concentrate grade by reducing contamination. Optimize type and dosage for maximum selectivity.

Control Pulp Density (Solids Concentration):

Research consistently shows an optimal range, often around 25-35% solids, with a peak near 30%. Pulp that is too dilute (<25%):

Reduces particle-bubble collision frequency.

Dilutes reagent concentration, reducing effectiveness.

Increases water and energy consumption.

Pulp that is too dense (>35%):

Increases viscosity, hindering bubble dispersion and rise.

Promotes particle-particle interactions (slime coating) and particle aggregation, reducing flotation efficiency.

Can overload froth handling.

Maintaining ~30% solids maximizes particle-bubble contact while ensuring good pulp fluidity.

Optimize Flotation Time and Bubble Characteristics:

Flotation Time: Determine the optimal residence time. Too short (

Bubble Size: Control bubble size primarily through frother type/dosage and air flow rate. Bubbles around 0.2mm diameter are often ideal. Larger bubbles (>0.5mm) have less surface area and provide poor attachment. Very fine bubbles (<0.1mm) can create excessively stable froth, increase pulp viscosity, and hinder drainage, reducing overall efficiency and concentrate grade. Aim for bubbles small enough for high surface area but large enough for efficient rise and drainage.

Manage Slime and Ore Variability:

Slime Control: Excessive fine particles ("slimes") generated during grinding can be detrimental. They consume large amounts of reagents, can coat valuable mineral surfaces ("slime coating"), and increase pulp viscosity. Strategies include:

Optimizing grind size to liberate without over-grinding.

Using slime depressants (like sodium silicate).

Considering de-sliming steps (e.g., hydrocyclones) before flotation if slimes are severe.

Ore Characterization: Understand the specific mineralogy, liberation characteristics, and inherent floatability of the ore feed. Regularly monitor feed characteristics and adjust operating parameters accordingly. Batch testing for new ore types is essential.

Implement Process Control and Monitoring:

Utilize online sensors (pH, density, level, possibly reagent analyzers) and automation systems to maintain key parameters (pH, pulp density, reagent dosages, air rates) consistently at their optimal setpoints.

Regular sampling and assaying of feed, concentrate, and tailings are crucial for tracking performance (Recovery, Grade) and identifying issues early.

Statistical analysis of plant data helps identify correlations and further optimization opportunities.

Conclusion:

Improving molybdenum flotation efficiency is not about adjusting a single parameter but involves the holistic optimization of multiple inter