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Mineralogical Testing Capabilities

PMC was a pioneer in the TIMA TESCAN Integrated Mineral Analyzer Scanning Electron Microscope (SEM)

PMC provides mineralogical characterization, data evaluation, and bench-scale metallurgical testing for the mineral industry for greenfield and brownfield projects. Our team incorporates the use of advanced mineralogical methods and approaches combined with laboratory metallurgical evaluation to provide accurate and relevant data.  PMC was an early adopter and helped develop the TIMA system.  TIMA is an upgrade on the previous QEMSCAN technology.  


Understanding the relationships between ore and the gangue is vital to realize the full potential of an ore body.  Our goal is to bridge the gap between geology and metallurgy.  We utilize all the tools in the toolbox and use mineralogy in combination with metallurgical testing to inform and guide efficient test programs

Mineralogical Characterization

PMC provides mineral analysis and characterization using our TIMA system on all kinds of samples including surface or outcrop grab samples, chip samples, drill core, or from process streams 

PMC's team can help determine process relevant mineralogical parameters such as

  • Mineral type and abundance

  • Mineral associations

  • Liberation and surface area exposure

  • Elemental Deportment

  • Particle and Grain Size Distribution


This information serves as the basis for understanding mineral processing performance.  PMC has developed several programs with different focuses based on specific needs and minerals or metals of interest.  Some examples are listed here but PMC can always develop a customized program.

Mineral Deportment
Tescan Integrated Mineral Analyzer TIMA QEMSCAN

Rapid Ore Characterization (ROC)

PMCʼs Rapid Ore Characterization (ROC) package provides quick turnaround, semi-quantitative data for preliminary evaluation of mineral processing product streams. A single "As Received" sample is examined using a TIMA Scanning Electron Microscope looking at mineral types and abundance, mineral associations, liberation and surface area exposure, elemental deportment and grain size analysis.  Combining multiple samples across the process allows for rapid auditing.


Size-by-Size Mineralogy

The size-by-size analysis approach is a well established mineralogical method providing the same characterization information as the Rapid Ore Characterization except avoids the risk of bias from the wide range of particle sizes by screening samples into different size fractions to be analyzed separately. 


The additional information provides valuable insights by identifying and quantifying factors that control ore behaviour during processing and tailings disposal. Grind Size prediction and Grade-Recovery predictions are achievable using this methodology and have been proven accurate to laboratory and plant performance. Key to this approach is the integration of analytical, sampling and other cross-disciplinary heuristics to ensure high-precision and accurate data.

Gold Deportment

Many approaches can be taken to characterize the ore which may occur as complex fine grained gold, ultra-fine grained gold, coarse nuggety gold and complex As-rich refractory gold. The approach taken will be dictated by the nature of the ore or plant product, the amount of sample material available, the gold grade and the grain size distribution.  For operating plants it is an opportunity to understand feed conditions and gold losses.


In the case of initial gold showings and early deposit drilling a reasonably comprehensive study should be undertaken to provide maximum mineralogical information that can assess the future drilling, and impact on the future processing circuit and recovery. An initial detailed characterization can be carried out on selected representative ore types chosen to provide reasonable coverage of the gold grade range present as well as geological and / or mineralogical differences that may be present.


Geometallurgy is the combination of geology, geostatistics, and extractive metallurgy to create a predictive model for an Orebody and Operation over the life of the orebody. This entails a cross-disciplinary approach to address complexities in an ore body and ore/processing interdependencies to understand and optimize the resource economics. 

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