ABSTRACT
Process mineralogy of copper and lead concentrates and MLA data calibration
Emilie Ré, Agnico Eagle Mines, QC, Canada
Raphaël Mermillod-Blondin, Agnico Eagle Mines, QC, Canada
Hassan Bouzahzah, Unité de Recherche et de Service en Technologie Minérale, Université du Québec en AbitibiTémiscamingue, QC, Canada
Jean-François Wilhelmy, COREM, QC, Canada
Mostafa Benzaazoua, Université du Québec en Abitibi-Témiscamingue, QC, Canada
Two copper and lead concentrates from the LaRonde mill were analyzed using MLA technology (Mineral Liberation
Analyzer) to identify the contaminants and to quantify their size distribution and liberation. The MLA mineral
quantification was compared with traditional mineralogical techniques (Scanning Electron Microscopy, Optical
Microscopy, X-Ray Diffraction and Chemistry). The reliability of the MLA data was then assessed (minerals
identification, minerals quantification, particles sizing and liberation quantification). Different well-known materials
were prepared from pure minerals and analyzed with the MLA.
MLA concentrates analyses have shown that lead concentrate is mainly contaminated by pyrite and sphalerite. These
minerals are liberated above 70 % and at a floatable size around 15 to 35 µm (Figure 1). Surface activation by
dissolved lead from galena is therefore assumed for these contaminants.
Figure 1 – 3D diagram presenting pyrite iron content versus liberation and size of the particles
The use of standard samples showed that mineral quantification and size distribution given by the MLA are consistent
with chemical and laser particle sizer analyses. Investigation led to conclude that the MLA liberation measurement is
biased by the stereological effect. The resulting overestimation was confirmed by modeling (Figure 2).
Figure 2 – Liberation frequency of standard material (black) by MLA (blue) and modeling (red)
The MLA characterization emphasizes the source of contamination in the LaRonde copper and lead concentrates which
is linked to liberated and size-floatable sulfides. Understanding of the liberation overestimation by the MLA, based on
the analyses of standard samples, enabled to shift our processing issues cause identification from a surface chemistry
problem to a potential liberation problem. Calibrating and including ore texture and stereological bias in the MLA data
interpretation should lead to improved results.
KEYWORDS
Quantitative mineralogy, MLA, liberation, standards, stereology, chalcopyrite, galena