Application Note

Whole-particle Liberation Studies
ZEISS Mineralogic 3D

Author:		

Eddy Hill, Ph.D.
Carl Zeiss Microscopy Ltd, Cambourne, UKDate:		November 2021

Light microscopes (LM) and scanning electron microscopes

Mineralogic 3D – Automated Mineralogy(SEM) are routinely used for mineral liberation studies – aZEISS Mineralogic 3D applies 3D X-ray microscopy techniques

measure of how accessible minerals are to the recovery process,and deep learning algorithms to execute automated mineralogy

and of the quality of the feed and the subsequent processing.

analyses in three dimensions (fig 1) that provide particle

An unavoidable requirement for the analysis is that the sample

identification, mineral classification, and data outputs including

be prepared in a manner suitable to the microscope in use.

liberation and association measurements.

Sample preparation is not simply an inconvenience imposed bylab equipment but is integral to the quality of the results andAnalyzing in 3D has three immediate benefits:

the inferences we may make. A poorly prepared sample may

1. The sample preparation process is greatly simplified

suffer density stratification, plucking, doming, agglomeration,

2. There are no stereological assumptions as every grain

pitting, insufficient surface exposure, etc. As well as thesemechanical sample preparation issues, the analysis is limited tois viewed in full
3. The time to actionable data is greatly reduced

the exposed surface of the mineral and therefore influenced bystereological limitations and the assumption that the exposed
surface is representative of the entire sample and a valid
description of the particles present. All these issues conspire
to produce analyses for which the modal mineralogy, grainsize, liberation, and associations information are compromised,regardless of whether the analysis is performed on the LMor with automated mineralogy (AM) software on an SEM.
Over time, techniques have developed to ensure we present
a representative sample for analysis that is devoid of sample
preparation artifacts. For example, the addition of graphite to
the sample to encourage particle separation and discouragedensity stratification, and the analyses of sufficient particles
to confidently describe a set of average particles and minimize
the limitations imposed by stereology (the interpretation of 3D
samples based on 2D information).

Figure 1 Analysis of a comminuted ore with the 3D X-ray microscope reveals thetrue mineral liberation with no mineral hidden by lack of exposure.

In all, sample preparation is a meticulous and time-consuming
activity, taking longer than a day to complete, commencing
with the collection of the material to be analyzed andAnalytical Considerations

progressing through to the final stages of setting in a resin

Sample Preparation

block, grinding, polishing, and coating with a conductive layer.

Unlike the rigorous sample preparation workflow that must be

None of the steps can be circumvented if we are to guarantee

followed to ensure we obtain valid data from an SEM analysis oftrustworthy data.

a comminuted sample, sample preparation for Mineralogic 3D
analysis is rather straightforward. All that is needed is a suitable

In the following text is a description of paradigm shift incontainer or tube to hold the sample and a stopper at either

automated mineralogy that overcomes the issues of attempting

end to help keep it in place. A step of complexity has been

to understand a 3D world by analyzing it on

introduced by the development of a technique that allows for

2D surfaces.

several samples to be mounted in the same sample carrier (tube)
but this falls far short of the intricacies of graphite addition, mix
stirring, setting, grinding, and polishing expected for the SEM
analysis. The result is a simplification of the workflow and a timesavings of several hours.

2Figure 2 Longitudinal cross-section of a 3D scan of ground material. The coarseness of the particles provides a clearer example of the ability of the machine learning
protocol to automatically identify and separate particles from each other.

The addition of graphite to the sample acts to both keep
particles apart, aiding the assessment of liberation andassociations, and to deter gravitational settling in the samples.
Since Mineralogic 3D views the entire sample, including
minerals locked within the particles, gravitational settling is
not a concern. Particle separation is elegantly dealt with by theapplication of machine learning protocols for segmentationthat identify each individual particle as independent from otherparticles that may be in contact with it (Figure 2).
Mineral Classification and Time to Actionable Data
Making full use of the imaging capability of the ZEISS Xradia
X-ray microscopes, enhanced by DeepRecon noise reduction
deep learning algorithms, Mineralogic 3D automaticallyclassifies the mineralogy of the sample based on attentuation
measurements (Figure 3). The ability to classify the mineralogy
in tomographic scans is unique and, when combined with themorphological measurements of the 3D reconstructed entities,
allows the calculation of standard mining relevant outputs

Figure 3 Mineral classification based on beam attenuation measurementse.g., morphological parameters, associations, and liberation.
The ability to measure not just the surface of particles but
their interior mineralogy too adds great value to the data
generated. When assessing the value of the data, we mustalso consider the time lapse between asking a question of thesample and obtaining an answer – if the data is to lead to anaction, rather than an understanding, then it must arrive within
the opportunity window for which it can be actioned. Next
week is too late. Taking full advantage of the simplified sample
preparation workflow, Mineralogic 3D delivers actionable2015105

data in a fraction of the time required by a metallographic
preparation for the SEM.

0SEMSample PrepX-rayAnalysis

Figure 4 The simplicity of sample preparation combined with advanced analyticaltechniques results in a marked time savings in results delivery with Mineralogic 3D3

Figure 5 Modal mineralogy based on the volume of the mineralogy

Measurements
Immediately at the end of the analysis, Mineralogic 3D reports
on modal mineralogy, liberation, associations, particle and grain

Asize, etc. All measurements that are in principle familiar to usersof automated mineralogy on the SEM, however, there are some
subtle and relevant differences between the two techniques.
Sample exposure
Automated mineralogy on the SEM requires particles to be
fixed in resin block that is then ground to expose particle
portions, and polished to present a good surface for analysis.
Grinding and polishing result in the mechanical alteration of
the sample and exposes only a fraction of the particles andB

mineral grains present. With Mineralogic 3D there is nomechanical alteration of the sample necessary and at any time,and every grain in the sample is visible to the analysis.
Modal mineralogy
Modal mineralogy considers the volume of each phase present
in the sample. It need not be exposed on the surface to beaccounted for (Figure 5).

Figure 6 (A) Mechanical alteration of the sample for SEM analysis reveals fractions of particles that the user must accept as true representations of the particle.
(B) With X-ray microscopy, the particle’s mineralogy and its exposure,or lack of, on the surface of the particle is fully recognised and measured.

Liberation
Liberation is purely dependent on the proportionality of thesurface exposure of a particle; for example, a particle whose
surface area is 85% chalcopyrite is considered as liberated
for chalcopyrite. Furthermore, there are no hidden surprises
beneath the surface as the entire particle surface, and interior
mineralogy, is visible, classified, and measured. This results inliberated classifications that have no inherent assumptions,and locked classifications for mineralogies that is truly within
the particle.

4

Figure 7 Liberation based on the mineral’s exposure on the surface of the particle and weighed by volume

Associations
In the 3D world, associations are measured relative to thecontact of surfaces between minerals, rather than the linear
contact observed in SEM analyses. Of course, a locked grainin the particle affects the association measurement in a waythat cannot be measured by 2D techniques.
Summary
Benefitting from advancements in X-ray microscopy andmachine learning, Mineralogic 3D represents a step change
in automated mineralogy. The unique ability to study samples

Contact surface

in 3D, with no obscured mineralogy, without stereologicalartifacts, and obtaining precise data for every particle opens thedoor to a new understanding of the geometallurgical behaviorof ores.

Figure 8 Particle split open to reveal the contact surfaces between minerals.
It is the proportion of the surface to the total surface of the mineral in the sample
that determines the level of association between the minerals.

5Carl Zeiss Microscopy GmbH07745 Jena, Germany
microscopy@zeiss.com
www.zeiss.com/microscopy

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