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AZtecMineral: Dedicated mineralogy on multi-purpose SEM

AZtecMineral is a powerful, automated, Mineral Liberation Analysis solution. It enables ore characterisation, provides vital data on metal recovery and enables process yield characterisation using multipurpose SEMs. It is also a valuable tool for the characterisation of rocks in research environments, enabling the automation of otherwise laborious optical analyses.

Exploiting the performance of up to 4 of Oxford Instruments’ large area SDDs (Ultim Max), it provides accurate classification of minerals at speeds comparable to dedicated systems – but with the flexibility to perform other investigations as required.


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AZtecMineral is a powerful, automated, Mineral Liberation Analysis solution. It enables ore characterisation, provides vital data on metal recovery and enables process yield characterisation using multipurpose SEMs.

Exploiting the performance of Oxford Instruments’ large area SDDs (Ultim Max), it provides accurate classification of minerals at speeds comparable to dedicated systems – but with the flexibility to perform other investigations as required.

Automated mineral characterisation

  • Reporting modal mineralogy
  • Liberation yields
  • Mineral associations
  • Particle and grain size distribution
  • Classification against a database of over 5000 minerals

Applications

  • Precious metal recovery (PGM)
  • Base metal recovery
  • Iron ore characterisation
  • Coal (mineral impurity analysis)
  • Thin section characterisation
  • Modal mineralogy

Performance

  • High speed acquisition using Ultim® Max technology
  • Automated analysis over wide area, resolution at the nanoscale
  • Take advantage of AZtec's Tru-Q® quantification algorithms

Flexibility

  • Works with most SEMs
  • Can be retrofitted to existing systems
  • Grain relocation for more detailed analysis using WDS, EBSD and complementary EDS techniques
  • Upgrade paths include large area mapping, quantitative EDS mapping and more

AZtecMineral automatically analyses grains over a large area of the sample, typically several square centimetres.

Because of the resolution achieved, information on individual grains is available from the same acquisition.

  • Samples can be either grain mounts, polished specimens or thin sections
  • Particles, and the grains within them, are detected using the atomic number contrast derived from a backscattered electron image
  • A combination of X-ray data and morphological data from the BSE image is used to identify the minerals
  • Both morphological and phase information from each grain is stored in a database from which it can be retrieved and re analysed in greater detail at any time
  • Stores all map, pole figure, measurement, subset and material settings within each dataset
  • Phase identification is performed by real-time full quantitative analysis during the acquisition (including AZtec’s Tru-Q processing). This delivers the accuracy needed to distinguish chemically similar phases
  • The relationship between the individual grains and the parent particles is maintained for further post-processing.
  • The post-processing module provides direct and convenient access to the data via a graphical user interface
  • Information is provided for individual grains as well as statistical information over the whole sample: mineral abundance, mineral associations, liberation, grain size distributions, common perimeter associations and particle associations as well as cumulative liberation yield graphs (depending on sample type).
  • Mineral grains can be classified against a database containing in excess of 5,000 reference minerals. An automated approach identifies groups of grains with similar compositions for comparison against the database.

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Application Notes using AZtecMineral

Fast Characterisation of Minerals with Similar Crystal Structures

Combining electron backscatter diffraction (EBSD) and energy dispersive X-ray spectroscopy (EDS) techniques for geological sample characterisation, helps to unlock even more information on the likely formation and history of the sample.

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