chapter 6: results and discussion
TRANSCRIPT
CHAPTER 6: RESULTS AND DISCUSSION
6.1 SAMPLING PROCEDURE: UG2 TAILINGS SAMPLE AND RCCs.
6.1.1 The selection and splitting process for the preparation of the UG2 HG
FT composite sample (UG2 Tailings sample)
As indicated in section 3.4 the majority of chrome present in the UG2 Reef
exploited by the platinum producers deports to the tailings stream from the
Concentration process. It was logical therefore to target the tailings stream as the
primary source for chromitite crystals.
A representative bulk sample or composite sample was prepared from monthly
composite UG2 Tailing samples for the years of 2006 and 2007. Composite
sampling is a technique used to create a representative sample by the
homogenization of multiple representative samples. Laboratories custom design
composite sampling procedures to ensure that the resultant sample complies with
specific objectives and statistical assumptions. Composite samples are generally
prepared for the following reasons:
• They are more representative of mean concentration than would be
achieved by the same number of individual samples.
• They may reduce sampling cost.
• They may be prepared and stored in order to provide future cross
referencing for that particular sample type and grade.
• They may also be stored and kept for future validation of techniques where
reference samples are not available.
• To minimize storage requirements that would otherwise be necessary for
numerous individual samples.
In total, 14 samples were selected in order to produce a weighted bulk composite
sample size of 30 kg which would be sufficient for the various analytical
procedures such as Pb-FA and NiS-FA. Sufficient sample was also needed for the
64
extraction of chromitite crystals for the mineralogy study. Samples and masses
used are listed in Table 6.1.
Table 6.1 UG2 Tailings samples selected.
SAMPLES: MC UG2 HG FT
WEIGHT (Kg)
January 2006 2
April 2006 2
May 2006 3
June 2006 2
July 2006 2
August 2006 2
September 2006 2
June 2007 2
July 2007 2
August 2007 2
September 2007 2
October 2007 2
November 2007 2
December 2007 3
Total weight 30
Each monthly composite sample consisted of 10 kg sample portions, which were
first tumbled for 30 min to address any segregation of the sample that may have
occurred during the storage period and then the required weight of sample, as per
Table 6.1, was transferred into a clean plastic container for further preparation.
65
The steps followed in preparing homogenised sample splits are as indicated in
Figure 6.1.
The 30 kg composite UG2 Tailings sample was tumbled for 1 hour.
The 30 kg portion was then split into
10 portions of 3 kg each.
Each 3 kg split was tumbled for ½
hour.
Two 3 kg splits were selected randomly and combined to give a 6
kg portion. The 6 kg portion was tumbled for a ½ hour.
Three 3 kg split portions were
selected randomly and combined to give a 9 kg portion. The 9 kg
portion was tumbled for a ½ hour.
Figure 6.1 Summary of the sampling steps.
66
The homogenised sample splits were distributed for analysis to various sections.
One 6 kg portion was retained for extraction of the chromitite crystals. Two 9 kg
portions were submitted to the Assay and IPGM sections of Impala laboratory
respectively for precious metal analysis. The balance of the samples were retained
for further analysis.
The total platinum group metal (TPGM) analysis of the UG2 Tailings composite
sample by Pb-FA collection technique was compared to the average of the
individual TPGM results obtained from weighted Monthly Composite Tailings
samples as shown in Table 6.1 for homogeneity testing. This test was performed
by analysing 6 x 150 g portions of the sample together with the in-house Final
Tailings Quality Control Standard over a period of 5 days. The average TPGM
results are shown in Table 6.2.
Table 6.2 The average TPGM results obtained in mg kg-1 (ppm) for
homogeneity testing using the Pb-FA collection technique.
Weighted Monthly Composite UG2
Tailings samples
TPGM
Mean ± SD
UG2 Tailings composite sample
TPGM
Mean ± SD
1.05 ± 0.10
1.04 ± 0.07
Good agreement was obtained between the average TPGM result of the UG2
Tailings sample compared to the average TPGM result of the weighted UG2
Tailings samples. The TPGM result is within the 95 % confidence limit of the
method. This was not just an indication of homogeneity, but also indicated how
reproducible the Pb-FA collection technique can be when executed under
controlled conditions.
6.1.2 Extraction of the residual chromitite crystals (RCCs)
Having established that the tailings sample was truly representative, one 6 kg
portion of the UG2 Tailings sample was submitted for extraction of the residual
67
chromitite crystals using an alkaline fusion procedure. This procedure is described
in Chapter 5, section 5.9.4. After the extraction of the residual chromitite crystals,
they were further boiled in aqua regia for one hour to remove any entrained PGM
minerals that may have been attached to the grain boundaries in the crystals.
Although most PGEs are profitably recovered from the UG2 ore; minerals such as
chromite, gangue minerals and PGEs associated with silicates are generally lost to
the tailings dams. The UG2 Tailings material is siliceous in character containing
approximately 25% silica (SiO2) and therefore required a basic flux for
decomposition.
Alkali metal carbonates and hydroxides such as Na2CO3, KOH and NaOH are
basic fluxes which attack acidic material and readily form alkali silicates. In the
case of the tailings sample, a basic flux mixture of KOH and Na2CO3 removed
approximately 98% of the silicate composition as indicated by the ICP-OES
analysis of the RCCs. The residual SiO2 composition was indicated to be
< 0.566%.
From the 6 kg composite UG2 Tailings sample, approximately 1.1 kg of RCCs
were recovered from the alkaline fusion procedure, or approximately 18% by
mass. The RCCs were then split into 4 equal fractions for NiS-FA analysis,
microwave dissolution and Te co-precipitation analysis, mineralogy studies and
particle size distribution analysis.
6.1.3 Particle size analysis: UG2 Tailings sample
The old terminology “grading analysis” has been replaced by “particle size”
analysis, which is a more accurate description of the classification of finely
divided material. [1]
Laboratory techniques such as FA-Pb and NiS-FA require a specific particle size
distribution. Prior to evaluation therefore it was critical to confirm that the sample
particle size distribution at least met the minimum criteria. In practice however,
68
particle size analysis is fundamental in the control of Concentrator operations
where the achievement of specific particle size through crushing, milling and
classification is a prerequisite for selective flotation of the PGEs. UG2 Operations
therefore, target a particle size distribution of approximately 70% < 75 μm after
milling and classification.
It was assumed therefore that the UG2 Tailings sample utilized would meet the
particle size criteria, which was subsequently confirmed by the Impala Operations
management. The particle size as mentioned above is more than sufficient for
laboratory techniques such as Pb-FA and NiS-FA collection, which only require a
particle size distribution of 85% < 150 μm. For the most part, fire assay
laboratories have as part of their quality control process, regular confirmation of
the performance of their pulveriser circuits.
6.1.4 Particle size distribution analysis: RCCs
To the naked eye, the residual chromitite crystals appeared extremely fine,
although different particle sizes were apparent. During the initial optimisation
phase using microwave and hotplate digestion, it was evident that not all the
sample dissolved. According to Reddy et al. [71] to obtain reproducible data by wet
chemical attack, a uniform sample mesh size of 200 – 250 must be present
otherwise discrete noble metal minerals may not be completely occluded within
grains and would therefore not be effectively dissolved by acid attack. A mesh
size of 200 – 250 is equivalent to 63 – 75 μm.
Particle size distribution analysis was performed using a laser particle size
analyzer: Saturn DigiSizer 5200. This instrument uses a CCD detector, Mie theory
and provides the highest analytical resolution achievable from laser particle size
analysers. The Saturn DigiSizer automatically measures particle sizes ranging
from 0.1 to 1000 μm quickly and accurately. A crystal fraction of 200 g was
analyzed repeatedly with the entire particle size range recorded and ascribed
median or mean particle diameters. The results were graphically generated
emphasising the capability of the laser scattering particle size analyser in
characterizing the chromite sample, refer to Appendix 1, section 1.1.
69
Statistics support reporting of particle size analysis as percentiles rather than
discrete percentages. Percentiles are a way of tabulating data which falls above
and below a given value [72,73]. The results are presented in this manner in Table
6.3. The 50th percentile (median) gave a value of 276.6 μm at or below, which 50
percent of the observations were found. Similar logic applied to the 10th, 25th, 75th
and 90th percentiles selected.
Table 6.3 Particle size analysis displayed as percentiles for the chromite sample.
Selected percentile ranges Diameter (μm) 90.0 538.5 75.0 406.0 50.0 276.6 25.0 156.3 10.0 89.55
Logic and prior experience with techniques such as NiS-FA suggested that finer
particles would dissolve easier when digested by microwave or hotplate digestion
as smaller particles would have a larger surface area exposed to acid attack.
Considering also that the hardness of chromite is between, 5.5 and 6.5, it was
decided to grind the chromitite sample such that 95 % of the particles would
measure < 5 μm to assist digestion. A Mccrone micronizing mill was used to mill
200 g of the sample which was accomplished by micronising 5g fractions
consecutively for 5 min each and thereafter the fractions were re-combined and
tumbled. The microwave digestion procedure was repeated on the sub-micron
samples and then the entire sample was successfully dissolved for further
evaluation.
6.2 AN ASSESSMENT OF THE CALIBRATION PROCEDURE USED
FOR THE BASE METAL ANALYSIS OF THE UG2 TAILINGS SAMPLE
6.2.1 Construction of the calibration program: FTAILS
It is critical to construct a calibration program whereby the calibration standard
extends over the concentration range of the samples under investigation. In
70
practise, due to high base metal concentration and extended concentration ranges
for each element (inter-elemental ratios), it is generally complicated and time
consuming to construct appropriate calibration programs for the variety of sample
matrices found in the mining industry. For this research work, however, the
appropriate data for the construction of a new calibration range for the UG2
Tailings sample was the UG2 Tailings base metal data which was readily
available having previously been analysed by the Impala laboratory over the prior
three months. The base metals of interest were Cr, Fe, Ca, Si, Mg, Al, Mn, Ti, Ni
and Co. The relevant statistics and histograms for these elements were assessed to
establish their expected concentration ranges with an aim to cost-effectively
construct a calibration line of acceptable uncertainty. A calibration program
consisting of six calibration standards, including a blank, was constructed with the
following characteristics:
• A mid-point was included which was as close as possible to the expected
analyte concentration such that the uncertainty would be at minimum at
the mid-point of the line.
• Two calibration standards were included with property values which were
similar to the highest and lowest concentration values expected.
• A calibration standard with an analyte concentration which was somewhat
higher and lower than the expected value was included.
• Calibration standards were spread evenly to cover the range.
The calibration program procedure consisted of four divisions:
• A calibration standard concentration expressed in mg L-1.
• A calibration standard concentration converted to mass %.
• A pipetting scheme.
• Matrix composition.
The calibration program was successfully constructed for the analysis of the UG2
Tailings sample and may be referred to in Section 1.2 of Appendix 1.
71
6.2.2 Optimisation and calibration process
Given the unique base metal matrix of UG2 tailings, the ICP-OES was optimised
using the software function Automax prior to the base metal analysis of the UG2
Tailings sample. A combination of the V-Groove nebulizer in conjunction with
the Sturman-Masters spray chamber was used as this was recommended for
sample solutions which contained high dissolved solids. The operating conditions
are summarized in Table 6.4.
Table 6.4 ICP-OES instrumental operating conditions employed for the base
metal analysis of the UG2 Tailings sample.
Operating conditions Specifications
Power (kW) 1.45
PlasFlow (L/min) 15.0
AuxFlow (L/min) 1.50
NebFlow (L/min) 0.60
Replicate Time (s) 15.0
Stab Time (s) 10
View height (mm) 10
Sample Uptake (s) 20
Rinse time (s) 30
Pump Rate (rpm) 15
Integration times were determined by aspirating the tails QC Standard 4 solution
at 5, 10, 15 and 20 second integration times respectively. The percent %RSD for
the different lines were calculated and assessed. The % RSD for most lines was
less than 0.5% for the different integration times which indicated good precision.
72
It was decided to use 10 seconds as the integration time for the analysis of the
base metals.
During the optimisation of the calibration program the following analytical lines
were selected and are displayed in Table 6.5.
Table 6.5 Selected analytical wavelength lines
Element Analytical wavelengths λ nm
Reported oxide %
Chromium Cr 206.55 Cr 267.72
Cr2O3
Iron Fe 238.20 Fe 259.94
Fe2O3
Calcium Ca 317.93 Ca 396.84
CaO
Silica Si 185.01 Si 288.15
SiO2
Magnesium Mg 279.80 Mg 280.27
MgO
Aluminium Al 237.31 Al 396.15
Al2O3
Manganese Mn 294.92 Mn 259.37
MnO
Titanium Ti 36.121 TiO2
Nickel Ni 231.60 Ni 221.64
Ni
Cobalt Co 230.78 Co 228.61
Co
Although the new CCD echelle grating based ICP-OES technology enables the
selection of many analytical wavelength lines for each element prior experience
has shown that the most sensitive lines still produce results of better precision and
accuracy. Line selection depends on many factors which include:
• The final concentration in solution, as high concentration results in the
selection of less sensitive lines to prevent over exposure and poor
precision.
73
• The sample matrix, which can cause interference effects due to its spectral,
physical and chemical properties.
The blank and highest calibration standards were aspirated to generate scans for
selection of the appropriate analytical wavelengths. The scans were evaluated for
interference and appropriate background corrections made.
6.2.3 Assessment of the regression parameters using regression statistics
Least squares linear regression is a statistical method used to summarise the
degree of association between two variables. The method works by determining
the best curve through the data which minimizes the sum of squares of residuals.
Regression data contains some uncertainty on the slope and intercept and the
uncertainty is quantified in a number of ways e.g. standard deviations of the mean
(standard error), t-values, p-values and confidence limits. [74] The statistical
software used to generate the regression parameters for evaluation was MS Office
EXCEL 97. This software was used to assess the regressions for linear range,
dynamic range, sensitivity, linear correlation coefficient and calibration
uncertainty. An example of two summary sheets displaying the regression
parameters can be found in Section 1.3 of Appendix 1.
To obtain a general idea of the performance of the VARIAN VISTA-PRO ICP-
OES for measurement of the base metals, a comparison of the regression data
obtained for each wavelength was made. A summary of the regression analysis of
the calibrations is shown in Table 6.6. The regression statistics presented in Table
6.6 are limited to those analytical wavelengths which were chosen for reporting
purposes.
Table 6.6 Summary of the regression parameters of the calibrations performed
for base metal emissions at different wavelengths using the VARIAN VISTA -
PRO ICP-OES
Wavelength
Λ r2 a Sa B Sb Sy/x
Cr 206.55 0.9990 400.73 248.76 427.53 7.59 386.49
74
Fe 259.94 0.9990 1675.62 1558.76 5622.18 97.51 2068.91
Ca 317.93 0.9962 1820.71 591.29 5749.54 205.02 907.04
Si 288.15 0.9995 1384.14 730.79 3897.81 51.98 855.47
Mg 279.80 0.9993 449.26 262.99 1381.82 17.91 364.41
Al 396.15 0.9996 689.04 3837.10 18458.72 178.56 6085.73
Mn 294.92 0.9998 252.37 67.78 33417.36 177.80 115.74
Ti 336.12 0.9996 4016.18 2632.38 137191.03 1381.01 4494.82
Ni 231.60 0.9997 28.33 4.21 1342.91 11.04 7.18
Co 228.61 0.9998 31.72 4.24 3664.06 22.53 7.66
r2 = correlation coefficient, a = intercept, Sa = uncertainty in the intercept,
b = slope, Sb = uncertainty in the slope, Sy/x = random calibration uncertainty,
The regression data was assessed as follows:
• The correlation coefficient (r2) measures the linear relationship between
two variables i.e. concentration versus intensity. The statistical data
showed that r and r2 point to almost positive linearity for the elements Cr,
Fe, Ca, Si, Mg, Al, Mn, Ti, Ni and Co. Thus, the linear relationship may
have been statistically significant, but it did not prove linearity or
adequacy of the fit.
• An ANOVA manipulation was also performed on the regression data to
prove linearity and to test for the dynamic range. This implied working in
that region of the calibration curve where the graph starts to plateau. This
is very much reality when constructing an extended calibration range. The
statistical data showed that the F-values pointed to significant linearity,
since Fcalc > Fcrit for the elements Cr, Fe, Ca, Si, Mg, Al, Mn, Ti, Ni and
Co.
• The sensitivity of an instrument is constant within the linear portion of the
calibration graph, but progressively decreases as the calibration line
approaches the horizontal. Thus, the method is analytically sensitive if b ≠
0. The analytical sensitivity of the method appeared to be satisfactory for
the elements Cr, Fe, Ca, Si, Mg, Al, Mn, Ti, Ni and Co.
75
• The calibration was also tested for good precision and whether the range
was acceptable. Since Sb < Sy/x, good precision was indicated for the
elements Cr, Fe, Ca, Si, Mg, Al, Mn and Ti, excluding Ni and Co. It is
known that precision or uncertainties about measurement decrease for
elements at low concentrations close to the LOD in a Na2O2 matrix. This
was true for Ni and Co.
• When a calibration range is inadequate it is considered unacceptable. This
can be resolved by including additional standards or by spacing the
calibration standards more appropriately. Since Sa > Sb, the calibration
range was acceptable for the elements Cr, Fe, Ca, Si, Mg, Al and Ti, but
not so for Mn, Ni and Co. The first calibration standard for the elements
Mn, Ni and Co was between 0.1 to 1 %, which was too close to the LOD
for a Na2O2 matrix. Thus, the range would have been improved if the first
calibration standard had been excluded for those elements.
The regression data obtained for sulphur and phosphorus was poor and was
therefore excluded from the analysis as it was below the limit of detection (LOD)
of the ICP-OES for these elements. The calibration data was, however, accepted
for all the elements of interest and the base metal analysis proceeded with
confidence, at the 95% confidence level for the UG2 Tailings composite samples.
6.2.4 Limit of detection (LOD) and limit of quantification (LOQ)
It is important to know the LOD and LOQ values of a specific method when
analyzing samples at trace level concentration. The LOD is influenced by
different factors such as the instrument type, instrumental drift, the calibration
range, the variation due to day to day preparation, matrix composition of the
samples, the preparation of the calibration standards, purity of the reagents and the
chemicals used.
The LOD refers to the least amount of material an analyst can detect
because it yields an instrumental response significantly greater than the
blank, which corresponds to a signal three times the noise level of the
background [55,58]. LOQ is the lowest amount of an analyte in a sample that
76
can be quantitatively determined with suitable uncertainty and corresponds to
10 times the noise to background signal [55, 58]. These definitions are supported
by the International Union of Pure and Applied Chemistry (IUPAC) and are now
very common. The calculations used for the determination of the LOD and LOQ
values are described in the summary sheets displaying the regression parameters
in Section 1.2 of Appendix 1. The LOD and LOQ values are presented in Table
6.7.
Table 6.7 LOD and LOQ values calculated for the tailings calibration program.
Wavelength (λ)
LOD (%) LOQ (%)
Cr 206.55 2.71 9.04 Fe 259.94 1.10 3.68 Ca 317.93 0.473 1.58 Si 288.15 0.658 2.20
Mg 279.80 0.791 2.64 Al 396.15 0.989 3.30 Mn 294.92 0.010 0.035 Ti 336.12 0.098 0.328 Ni 231.60 0.016 0.054 Co 228.61 0.006 0.021
The major composition of the samples constituted the elements Cr, Fe, Si, Ca, Mg
and Al, which were reported as mass %. LOD and LOQ values are not critical for
elements which report at such high concentration level and hence, the regression
statistics presented in Table 6.5 are more applicable for those elements. The
samples also contained the elements Ni, Co, Mn and Ti at trace level
concentration close to the calibration program LOD. The overall composition of
the UG2 Tailings sample is presented in Table 6.7. Nickel reported 0.103 %, TiO2
0.685 % and MnO 0.202 %, which are all above the method LOQ and were
therefore accepted. Co reported below the LOQ of 0.021 %.
6.3 AN ASSESSMENT OF THE CALIBRATION PROCEDURE USED
FOR THE PGE ANALYSIS OF THE UG2 TAILINGS SAMPLE
6.3.1 Optimisation and calibration process of the program: Dilution (DIL)
77
Optimisation and calibration processes were performed by the Impala laboratory
in accordance with their quality control procedures and approved technical reports
retained for reference. These technical reports contain the following information:
• ICP-OES operation conditions
• Calibration data from every calibration program, to include any statistical
analysis performed e.g. regression analysis, LOD and LOQ
• Method validation performance parameter data, to include any statistical
analysis performed e.g. accuracy, precision and proficiency testing
• Results, discussion and recommendations
Calibration programs: DIL and General (GEN) are used successfully on a daily
basis by the Impala laboratory for consistent analysis of low and high grade PGE
mining samples for metal accounting purposes. Based on its successful use in
industry, it was decided that the DIL program should be used for the PGE analysis
of the UG2 Tailings sample. An assessment of the DIL program’s regression
statistics is not discussed as this has been previously covered in a technical report
MPL 11/03/D/IPGM/4 – The commissioning of the IRIS INTREPID II XDL [ ].
Table 6.8 contains the wavelength and spectral interferences which were
identified for PGE analysis.
Table 6.8 The wavelength and interference lines selected for PGE analysis
Wavelength (λ) Spectral Interferences
Pt 214.42
Pt 265. 95
-
Chromium
Pd 340.45 -
Au 242.79 -
Rh 343.48 -
Ru 240.27 Iron
Ir 212.68 Nickel
78
Software mathematically corrects for interference using the function; Internal
elemental correction (IEC).
Principles of the actual NiS-FA technique were covered extensively in Chapters: 3
and 5 of this dissertation. The technique removes the sample matrix and pre-
concentrates the PGEs for analysis. Although the matrix is removed, the elements
Ni, Cu, Cr and Fe are sometimes present in final solution at low levels, not more
than 50 mg L-1. These elements form part of the calibration program to monitor
the effectiveness of the leaching step in the NiS-FA process. K-factors for the
IECs were calculated and applied to the analytical program.
BM and PGE data obtained for the UG2 Tailings sample are displayed in
Appendix 1, section 1.4.
6.4 DETERMINATION OF THE BASE METALS COMPOSITION OF
THE UG2 TAILINGS SAMPLE
6.4.1 Base metal composition of the UG2 Tailings sample
Based on its successful employment in the platinum industry for similar
application, the VARIAN VISTA PRO ICP-OES was used for the determination
of the base metals, Cr, Fe, Ca, Si, Mg, Al, Mn, Ti, Ni and Co. The composite
sample was dissolved using a Na2O2 fusion technique. In order to perform
statistical analysis, reproducibility data was collected by fusing the sample in
quadruplicate over a period of 5 days to collect a minimum of 20 observations.
The composite sample was prepared with an Impala in-house reference standard
ICL and the reference standard SARM 64, which is commercially available. The
base metal concentration for UG2 Tailings sample is detailed in Figure 6.3. The
major components of the composite sample were: SiO2, 24.80 %, Cr2O3, 21.78 %,
Fe2O3, 19.06 %, MgO, 13.66 %, Al2O3, 13.19 % and CaO, 4.89 % confirming the
siliceous nature of the tailings material. The minor components of the composite
sample were TiO2, 0.685 %, MnO, 0.211 %, Ni, 0.103% and Co, less than 0.021
%.
79
Figure 6.2 The base metal concentration of the UG2 Tailings sample
6.4.2 Accuracy of the method
Having determined the base metal composition of the UG2 tailing sample it was
critical to verify the accuracy of the method for the unique material matrix which
was not dissimilar to the chromite crystals matrix which was to be evaluated
thereafter. Accuracy is the closeness of agreement between a test result and an
accepted reference value. [74]
The accuracy of a method is usually established by analysing an appropriate
certified reference material (CRM) which is representative of the matrix of the
material under investigation. Generally speaking there is a shortage of matrix
matched reference materials in the mining industry. In practise therefore,
laboratories normally prepare in-house quality control (QC) standards which are
either certified using available CRMs or they are sent to accredited laboratories in
the field for validation of the standard.
For the determination of base metals, the in-house QC standard ICL and SARM
64 were analysed on a daily basis with the UG2 Tailings sample for quality
control purposes. The ICL in-house QC standard values utilised reported within
the certified limits at 95% confidence level. The reference material SARM 64 was
80
only certified for PGEs, but preliminary base metal values were available and are
shown in Table 6.9. This reference material is of UG2 Tailings origin and
representative of the UG2 Tailings sample composition. Good agreement was
found between the results obtained for SARM 64 and the preliminary values
established for Cr2O3, SiO2, MgO, MnO, Ni and Co, but less so for Fe2O3 and
CaO.
Recovery tests are also accepted for proving accuracy.The total percentage base
metal recovery obtained by analysing SARM 64 was 99.76 %, indicating good
recovery.
As a further check, the base metal composition of the UG2 Tailings sample as
determined was compared with a library of historical data for similar sample types
at Impala laboratory.
Although, accuracy was not proven with certainty, the comparison data displayed
good agreement and good recoveries were achieved and thus the base metal
results were accepted for the project.
Table 6.9 Comparing base metal results obtained for SARM 64 to the
preliminary values of SARM 64.
Base metals
Mean ± SD %
Non Certified %
Cr2O3 29.68 ± 0.68 30.5
Fe2O3 22.36 ± 0.68 24.4
CaO 3.63 ± 0.38 2.23
SiO2 15.67 ± 0.97 15.5
MgO 10.86 ± 0.31 11
Al2O3 16.64 ± 0.66 15.1
MnO 0.211 ± 0.003 0.2
TiO2 0.499 ± 0.021 N.D.
Ni 0.099 ± 0.007 0.097
Co 0.025 ± 0.003 0.023
N.D. – Not determined
81
6.4.3 Precision of the results
Before utilising the method for the evaluation of the RCCs it was critical to
establish the precision of the method for the sample type. Reproducibility data
was obtained over a period of 5 days and statistical analysis performed on the data
after the application of a Grubb’s test to identify outliers. No outliers were
identified. The precision of the method was expressed as percent relative standard
deviation (% RSD) and is shown in Table 6.10.
Table 6.10 The mean and % RSD values obtained when analysing the UG2
Tailings sample for base metals.
Cr2O3 %
Fe2O3 %
CaO %
SiO2 %
MgO%
Al2O3%
MnO%
TiO2 %
Ni %
Co %
Mean 21.78 19.06 4.89 24.80 13.19 13.66 0.156 0.411 0.103 < 0.23
SD 0.63 0.73 0.35 1.49 0.38 0.72 0.005 0.012 0.010 0.002
%RSD 2.90 4.14 7.22 6.02 2.89 5.25 3.16 2.84 10.18 9.95
N 20 20 20 20 20 20 20 20 20 20
Once again the data produced was compared to historical industrial data recorded
for this method and sample type which indicated that RSD’s of less than 5% were
generally obtainable which was achieved in the experimental for the elements
Cr2O3, Fe2O3, MgO, MnO and TiO2, but not for Al2O3, CaO, SiO2, Ni and Co.
It was known from previous test work that impurities such as Ca, Al and Si may
be present in Na2O2 as a flux even though the standards and samples were matrix
matched with Na2O2 used and HNO3 as far as possible, which would explain the
poorer precision for these elements. In the commercial world, the oxides of Si, Ca
and Al have little influence on the process and are not required for metal
accounting purposes. As such, the method is not fully customised to achieve
optimum precision for these elements, however data is collated over time to
improve the overall precision of these elements for quality control.
In respect of Ni and Co the Horwitz Trumpet theory [73] explains that the %RSD
increases as concentration decreases. Since Ni reported at a trace concentration of
82
0.103 % and Co reported below the LOQ of the method which was < 0.23 %, this
obviously impacted upon precision for these elements. From prior experience, it
is also known that Na2O2 fusion is not suitable for the accurate determination of
concentrations below 500 mg L-1 which level of accuracy was not considered
critical for this determination. Figure 6.4 illustrates the relationship between
concentration and %RSD results obtained for base metal analysis.
Figure 6.3 Illustrating the relationship between the %RSD and mean results
obtained for the base metal analysis of the UG2 Tailings sample
6.5 DETERMINATION OF THE PGEs COMPOSITION OF THE UG2
TAILINGS COMPOSITE SAMPLE
6.5.1 PGEs composition of the UG2 Tailings sample
As mentioned previously, since the ICP-OES is extensively and successfully
employed in the determination of PGEs at low concentrations in the platinum
industry the IRIS INTREPID II XDL ICP-OES was selected for the determination
of Pt, Pd, Rh, Au, Ru and Ir prepared by the NiS-FA technique. In order to
perform statistical analysis, reproducibility data was collected by fusing the
sample in quadruplicate over a period of 3 days to collect a minimum of 12
observations. In parallel, the same sample was fused using the Pb-FA technique
for the TPGM value which represents the platinum group metals (Pt, Pd, Rh and
83
Au) combined as a quality control procedure to check the inter-elemental ratios.
The UG Tailings sample was prepared using an Impala in-house quality control
standard QCFT 2 and a reference standard SARM 64, which is commercially
available. The PGE results obtained for the UG2 Tailings sample are shown in
Figure 6.5.
The PGEs composition of the UG2 Tailings sample was: Pt 0.7 mg kg-1, Pd 0.39
mg kg-1, Au 0.01 mg kg-1, Rh 0.16 mg kg-1, Ru 0.27 mg kg-1 and Ir 0.07 mg kg-1.
In commercial practise as discussed in Chapter 3, section 3.4.1, recoveries of
approximately 80% of the platinum group metals are achieved from the flotation
of UG2 concentrate. This means approximately 20% of the platinum group metals
are lost to the tailings. The determination of PGEs in the UG2 Tailings sample
supported the loss of non- liberated precious metal to the tailings.
Figure 6.4 PGEs results obtained for the UG2 Tailings sample
6.5.2 Accuracy of the method
To establish the accuracy of the PGEs analyses, and thereby verify the accuracy of
the method, an in-house QC standard QCFT 2 and SARM 64 (of UG2 tailings
origin) were analysed on a daily basis with the UG2 Tailings sample. The values
obtained for the in-house QC standard QCFT 2 reported within the certified limits
as established by the Impala laboratory. The values obtained for SARM 64 with
84
certified values (C.V.) for PGEs are shown in Table 6.11. Good agreement was
found between the results reported for SARM 64 and the certified values of
SARM 64 for the elements Pt, Pd, Au, Rh, Ru and Ir. The PGEs results obtained
for the analysis of UG2 Tailings sample were therefore verified and accepted for
the project.
Table 6.11 Comparison of the PGEs results obtained for analysis of SARM 64
and its certified values (C.V.).
PGEs Mean ± SD
mg kg-1
C.V. ± SD
mg kg-1
Platinum 0.48 ± 0.06 0.475 ± 0.036 Palladium 0.19 ± 0.03 0.210 ± 0.038
Gold 0.01 ± 0.00 0.018 ± 0.008 Rhodium 0.08 ± 0.02 0.080 ± 0.012
Ruthenium 0.23 ± 0.02 0.240 ± 0.032 Iridium 0.06 ± 0.01 0.052 ± 0.011
6.5.3 Precision of the results
Reproducibility data was obtained over a period of 3 days and statistical analysis
performed on the data after identification of outliers. The precision of the method
was expressed as % RSD and is shown in Table 6.12.
Table 6.12 Illustrating the mean and %RSD values obtained for the PGE
analysis of the UG2 Tailings sample
Platinum
mg kg-1
Palladium
mg kg -1
Gold
mg kg-1
Rhodium
mg kg-1
Ruthenium
mg kg-1
Iridium
mg kg-1
Mean 0.70 0.39 0.01 0.16 0.27 0.07 SD 0.70 0.06 0.003 0.02 0.03 0.01
%RSD 10.55 14.81 28.75 9.77 10.82 12.33 n 10 10 10 10 10 10
Three outliers were identified and excluded per daily batch which was in
accordance with Impala’s laboratory Standard Practise Manual, Volume 11,
85
Section 114: Method validation procedure. Precision at these trace level
concentrations is acceptable when the %RSD is between 10 – 15 % which was
true for the elements Pt, Pd, Rh, Ru and Ir, but not so for Au. Gold and Iridium
occur at ultra trace levels and RSD levels of up to 25 % are not uncommon for
these metals in tailings material. As before, Horwitz Trumpet theory explains that
the %RSD increases as the concentration decreases.
Figure 6.6 illustrates the relationship between concentration and %RSD obtained
for the PGEs analysis.
Figure 6.5 Illustrating the relationship between the mean and %RSD results
obtained for PGEs analysis of the UG2 Tailings sample.
6.6 AN ASSESSMENT OF THE CALIBRATION PROCEDURE USED
FOR THE BASE METAL ANALYSIS OF THE RCCs
6.6.1 Optimisation and calibration process
A calibration program was successfully constructed for the analysis of the RCCs
based on SARM 9 chromite composition values and is included in section 1.3 of
Appendix 1. The ICP-OES operating conditions were optimised in accordance
with the operations manual of the SPECTRO GENESIS for the determination of
the base metals in the RCCs. The V-Groove nebulizer in conjunction with the
86
Scott spray chamber was used during analysis. The operating conditions were as
summarized in Table 6.13.
Table 6.13 ICP-OES operating conditions employed for the base metal analysis
of the RCCs
Operating conditions Specifications
Power (kW) 1.40
PlasFlow (L/min) 14.0
AuxFlow (L/min) 1.00
NebFlow (L/min) 0.85
Replicate Time (s) 15.0
Stab Time (s) 10
Sample Uptake (s) 25
During the optimisation of the calibration program the following analytical lines
were selected and are displayed in Table 6.14.
Table 6.14 Selected analytical wavelength lines
Element Analytical wavelengths λ nm
Reported oxide %
Chromium Cr 205.55 Cr 283.56
Cr2O3
Iron Fe 244.45 Fe 259.94
Fe2O3
Magnesium Mg 279.80 Mg 280.27
MgO
Aluminium Al 394.40 Al 396.15
Al2O3
Manganese Mn 257.61 Mn 259.37
MnO
Titanium Ti 336.12 TiO2
Vanadium V 292.46 V 311.07
V2O5
Cobalt Si 251.61 SiO2
87
The blank and highest calibration standards were aspirated to generate scans for
selection of the appropriate analytical wavelengths. The scans were evaluated for
interference and appropriate background corrections made. The Chromium lines
mentioned in Table 6.5 is different to the Chromium lines chosen in Table 6.14.
The reason for this is that two different ICP-OES instruments were used during
analysis and analytical lines were chosen, based on good linearity and to prevent
overexposure of the lines which resulted in poor regressions.
6.6.2 Assessment of the regression parameters using regression statistics
The statistical software used to generate the regression parameters for evaluation
was MS Office EXCEL 97. This software was used to assess the regressions for
linear range, dynamic range, sensitivity, linear correlation coefficient and
calibration uncertainty. To obtain a general idea of the performance of the
SPECTRO GENESIS ICP-OES for measurement of the base metals, a
comparison of the regression data obtained for each wavelength was made. A
summary of the regression analysis of the calibrations is shown in Table 6.15. The
regression statistics presented in Table 6.15 are limited to those analytical
wavelengths which were chosen for reporting purposes.
Table 6.15 Summary of the regression parameters obtained for different
wavelengths using the SPECTRO GENESIS ICP-OES during base metal analysis
of the RCCs.
Wavelength Λ
r2 a Sa B Sb Sy/x
Cr 283.56 0.9990 -0.0050 0.015 0.0283 0.00052 0.0179
Fe 259.94 0.9998 -0.0223 0.035 0.220 0.0018 0.04186
Mg 279.80 0.9992 -18.058 24.24 130.99 2.55 31.31
Al 396.15 0.9978 0.8174 2.828 9.04 0.304 3.65
Mn 259.37 0.9999 58.49 2346.96 889423.1 4858.38 2806.09
Ti 336.12 0.9940 127585.4 63837.4 946307.5 73581.47 66238.47
V 292.46 0.9999 12634.29 977.29 252968.8 1175.40 1166.17
Si 251.61 0.9944 82522.14 35574.3 6877966 514382.8 389186.3
88
r2 = correlation coefficient, a = intercept, Sa = uncertainty in the intercept,
b = slope, Sb = uncertainty in the slope, Sy/x = random calibration uncertainty,
The regression data was assessed as follows:
• The correlation coefficient (r2) measures the linear relationship between
two parameters i.e. concentration versus intensity. The statistical data
showed that r and r2 point to almost positive linearity for the elements Cr,
Fe, Mg, Al, Mn, Ti, V and Si. Thus, the linear relationship may have been
statistically significant, but it did not prove linearity or adequacy of the fit.
• An ANOVA manipulation was also performed on the regression data to
prove linearity and to test for the dynamic range. This implied working in
that region of the calibration curve where the graph starts to plateau. The
statistical data showed that the F-values pointed to significant linearity,
since Fcalc > Fcrit for the elements Cr, Fe, Mg, Al, Mn, Ti, V and Si.
• The sensitivity of the instrument is constant within the linear portion of the
calibration graph, but progressively decreases as the calibration line
approaches the horizontal. Thus, the method is analytically sensitive if
b ≠ 0. The analytical sensitivity of the method appeared to be satisfactory
for the elements Cr, Fe, Mg, Al, Mn, Ti, V and Si.
• The calibration was also tested for good precision and whether the range
was acceptable. Since Sb < Sy/x, good precision was indicated for the Cr,
Fe, Mg and Al, but not for Mn, Ti, V and Si. It is known that precision or
uncertainties about measurement decreases for elements reporting close to
the LOD of the method.
• When a calibration range is inadequate it is considered unacceptable. This
can be resolved by including additional standards or by spacing the
calibration standards more appropriately. Since Sa > Sb, the calibration
range was acceptable for the elements Cr, Fe, Mg and Al, but not for Mn,
Ti, V, and Si. The first calibration standard for the elements Mn, Ti, V and
89
Si was between 0.1 to 0.4 %, which was too close to the LOD of the
method. Thus, the range would have been improved if the first calibration
standard had been excluded for those elements.
The calibration data was accepted for all the elements of interest and the base
metal analysis proceeded for the RCCs.
6.6.3 Limit of detection (LOD) and limit of quantification (LOQ)
It is especially important to know the LOD and LOQ values of the calibration
method for the elements Mn, Ti, V and Si, as these elements are at trace level
concentration. The LOD is influenced by different factors such as the instrument
type, the instrumental drift, the calibration range, the variation due to day to day
preparation, the matrix composition of the samples, the preparation of the
calibration standards, the purity of the reagents and the chemicals used. The LOD
and LOQ values are presented in Table 6.16.
Table 6.16 LOD and LOQ values calculated for the calibration program
used for the base metal analysis of the RCCs
Wavelength (λ)
LOD (%) LOQ (%)
Cr 283.56 1.90 6.33
Fe 259.94 0.57 1.90
Mg 279.80 0.72 2.39
Al 396.15 1.21 4.04
Mn 259.37 0.009 0.032
Ti 336.12 0.210 0.700
V 311.07 0.014 0.046
Si 251.61 0.170 0.566
The major composition of the samples excluding Si was similar to the tailing
sample and constituted the elements Cr, Fe, Mg and Al, which were reported as
mass%. LOD and LOQ values are not critical for elements which report at such
high concentration level and hence, the regression statistics presented in Table
90
6.13 are more applicable for these elements. The samples also contained the
elements Mn, Ti, V and Si, at trace level concentrations close to the LOD of the
calibration program. The overall composition of the RCCs is presented in Figure
6.7. MnO, TiO2, V2O5 all reported above the LOQ of the method and were
accepted. SiO2 reported below the LOQ of 0.566 %.
6.7 AN ASSESSMENT OF THE CALIBRATION PROCEDURE USED
FOR THE PGE ANALYSIS OF THE RCCs
6.7.1 Optimisation of the SPECTRO MASS 2000 ICP-MS
Optimisation of the SPECTRO MASS 2000 ICP-MS was performed to obtain the
best analyte sensitivity and to maintain stability of the instrument and the sample
introduction system. The ICP-MS was optimised in accordance with the
SPECTRO operations manual for this instrument. A fresh solution containing 100
μg L -1 of Mg, U, Ce and Rh was prepared daily for optimisation. A “time scan”
was performed for the following isotopes: 24Mg, 36Ar, 70Ce+2, 103Rh, 140Ce, 156CeO, 230BKG (background) and 238U. These isotopes are sensitive to
instrumental changes and are used to optimise the torch alignment, sample argon
(nebulizer flow) and ion optics settings of the ICP-MS. The CeO/Ce ratio is a
plasma robustness criterion which has been widely adopted to monitor ICP-MS
performance. The CeO/Ce ratio is acceptable when less than 3%, which indicates
the efficiency with which the plasma can decompose the Ce-O bond. The
generator and ion optics optimisation data can be found in Section 2.1 Appendix
2. Successful optimisation of the ICP-MS was achieved and the calibration
process proceeded.
6.7.2 The calibration process and selection of isotopic lines
A Cross-flow nebulizer in conjunction with a Scott-type spray chamber was used
for the calibration process. Isotopic lines selected were sourced from literature
review, more specifically on analytical information obtained from applications in
the platinum industry which use ICP-MS. The isotopic lines selected for analysis
together with the potential interferences from ionic species are shown in Table
6.17.
91
Table 6.17 Selected isotopic lines and potential interferences which overlap
PGE signals [55-59]
Isotope Abundance %
Potential interference from ionic species
Polyatomic Isobaric Doubly Charged
99Ru 102Ru
12.70 31.60
103Rh 100.00 63Cu40Ar+, 86Sr17O+ 66Zn37Cl+, 68Zn38Cl+
206Pb2+
105Pd
106Pd
22.33
27.33
89Y16O1, 90Zr16O1
92Mo16O1, 66Zn40Ar+
106Cd+
115In 95.70 185Re 37.40 191Ir 193Ir
37.30 62.70
194Pt
195Pt
196Pt
32.90
33.80
25.30
178Hf16O+, 177Hf17O+
176Hf18O+,
179Hf16O1, 178Hf17O+ 177Hf18O+, 180Hf16O+
197Au 100.00
6.7.3 Assessment of the regression parameters using regression statistics
The statistical software used to generate the regression parameters for evaluation
was MS Office EXCEL 97. This software was used to assess the regressions for
linear range, dynamic range, sensitivity, linear correlation coefficient and
calibration uncertainty.
To obtain a general idea of the performance of the SPECTRO MASS 2000 ICP-
MS for measurement of the PGEs, a comparison of the regression data obtained
92
for each wavelength was made. A summary of the regression analysis of the
calibration is shown in Table 6.18.
Table 6.18 Summary of the regression parameters obtained for the different PGE
isotopic lines using the SPECTRO MASS 2000 ICP-MS
Isotopes
r2 a Sa B Sb Sy/x
102Ru 0.9999 122.02 63.11 255.68 1.24 99.94 103Rh 0.9998 602.99 328.86 725.17 6.45 520.77 105Pd 0.9990 167.20 130.49 139.73 2.56 206.24 106Pd 0.9996 147.82 100.29 166.77 1.97 158.82 191Ir 0.9997 196.89 94.08 181.20 1.85 148.98 193Ir 0.9997 296.13 163.54 305.18 3.21 258.97 194Pt 0.9970 279.35 173.47 112.17 3.40 274.76 195Pt 0.9997 58.13 73.69 121.56 1.44 113.93 196Pt 0.9970 136.15 111.42 83.61 2.19 176.44
197Au 0.9985 86.30 267.76 231.05 5.25 424.01
r2 = correlation coefficient, a = intercept, Sa = uncertainty in the intercept, b =
slope, Sb = uncertainty in the slope, Sy/x = random calibration uncertainty,
The regression data was assessed as follows:
• The correlation coefficient (r2) measures the linear relationship between
two variables i.e. concentration versus intensity. The statistical data
showed that r and r2 point to almost positive linearity for the isotopes 102Ru, 103Rh, 105Pd, 106Pd, 191Ir, 193Ir, 194Pt, 195Pt 196, Pt and 197Au. Thus, the
linear relationship may have been statistically significant, but did not
prove linearity or adequacy of the fit.
• An ANOVA manipulation was also performed on the regression data to
prove linearity and to test the dynamic range. This implied working in that
region of the calibration curve where the graph starts to plateau. The
93
statistical data showed that the F-values pointed to significant linearity,
since Fcalc > Fcrit for the isotopes 102Ru, 103Rh, 105Pd, 106Pd, 191Ir, 193Ir, 194Pt, 195Pt 196, Pt and 197Au.
• The sensitivity of an instrument is constant within the linear portion of the
calibration graph, but progressively decreases as the calibration line
approaches the horizontal. Thus, the method is analytically sensitive if
b ≠ 0. The analytical sensitivity of the method appeared to be satisfactory
for the isotopes 102Ru, 103Rh, 105Pd, 106Pd, 191Ir, 193Ir, 194Pt, 195Pt 196, Pt and 197Au.
• The calibration was also tested for good precision and whether the range
was acceptable. The precision refers to the measurement replicates per
calibration standard used. Since Sb < Sy/x, good precision was indicated for
the isotopes 102Ru, 103Rh, 105Pd, 106Pd, 191Ir, 193Ir, 194Pt, 195Pt 196, Pt and 197Au.
• When a calibration range is inadequate it is considered unacceptable and
means that extra calibration standards should be included between the
blank and first calibration standard. Since Sa > Sb, the calibration range
was acceptable for the isotopes 102Ru, 103Rh, 105Pd, 106Pd, 191Ir, 193Ir, 194Pt, 195Pt 196, Pt and 197Au.
The statistical analysis performed on the calibration data for the isotopes 102Ru, 103Rh, 105Pd, 106Pd, 191Ir, 193Ir, 194Pt, 195Pt 196, Pt and 197Au produced acceptable
results. The calibration data was accepted for all isotopes of interest and the PGE
analysis proceeded with confidence for the RCCs.
6.7.4 Limit of detection (LOD)
The LOD values are presented in Table 6.19 with concentrations converted to μg
kg -1 or ppb.
94
Table 6.19 LOD values calculated for the calibration program used for the PGEs
analysis of the RCCs.
Isotopic lines
LOD (μg L -1) LOD (μg kg -1)
102Ru 0.24 1.24 103Rh 0.12 0.60 105Pd 0.82 4.13 106Pd 0.84 4.19 191Ir 0.51 2.59 193Ir 0.66 3.30 194Pt 0.22 1.12 195Pt 0.56 2.79 196Pt 0.13 0.65
197Au 0.49 2.47
6.7.5 Assessment of the interference data and scans performed
The determination of precious metals at ultra trace levels in geological and
environmental matrices remains challenging even after the adoption of more
sophisticated instrumentation such as ICP-MS. Although ICP-MS technology has
been further improved following the introduction of the dynamic reaction cell
(DRC) and high-resolution (HR) ICP-MS technology, it can still only minimize
but not totally remove interferences from the matrix solution.
To complete an interference study it was critical to identify possible interferences
which may form part of the matrix. As above, the major components of the
residual chromitite crystals are the elements Cr, Fe, Mg and Al followed by trace
levels of Ti, Mn, V and Si. The matrix of the dissolved RCCs was removed during
the pre-concentration process prior to Te co-precipitation. Based on the RCCs’
sample composition, it was decided to perform scans to identify possible
interference using pure reference standard solutions each of 100 ug L-1 Cr, Fe, Se
and Te. For the scanning of the precious metals pure reference standard solutions
each of 100 ug L-1 Pt, Pd, Au, Rh, Ru and Ir were used. De-ionised water and a
95
procedural blank containing the matrix elements were also scanned together with
the pure standard solutions above. The resultant scans can be found in section 2.2
Appendix 2.
No spectral interference was identified for the PGEs isotopes of interest by the
matrix elements: Cr, Fe, Se and Te. It was evident that these elements were
following the background peak position of each PGE isotope, where intensities in
counts per second (cps) were around 10 2 and 10 3. It again emphasised how
important LOD is in assessing accuracy of analysis at trace levels.
According to Simpson [48] a major concern in ICP-MS analysis is severe spectral
interferences caused by the formation of refractory oxides (ZrO+, YO+, SrO+,
TaO+ and HfO+) and argides (ArZn+ and ArCu+) on all major isotopes of Pt, Pd
and Au [48]. The formation of refractory oxides like ZrO+, YO+, SrO+, TaO+ and
HfO+ was therefore considered. Reports suggest that Hf has been associated with
ZrO+ in autocatalyst substrates and interference by ZrO+ on Pd has been reported [48].
In the platinum industry it is known that when Na2O2 fusions are used during the
dissolution of samples, that Zr contains high concentrations of Hf, which
interferes with some isotopic lines as HfO+. Zr crucibles are used during Na2O2
fusions, which contain Hf. No interference was apparent from Hf, using the Te co-
precipitation process and scanning of the procedural blank did not indicate any
interference either. A scan was also performed containing 10 mg L-1 of pure Hf
standard solution, but no significant interference was apparent at the PGE
isotopes.
The formation of Argides is possible when Ni, Cu and Zr are present in solution.
Although no Cu and/or Ni was detected, it would not have been possible to
remove such interference with current SPECTRO MASS 2000 ICP-MS
technology. Some ICP-MS instruments have DRC technology, which use
ammonia gas instead of Argon to remove Argide interference.
It was found that Au gave erratic data during analysis, possibly due to memory
effects. In response, the flushing time between sample solutions was increased to
96
about 3 min which resolved the problem. The Au memory effect is illustrated in
Appendix 2, section 2.2, Figure 2H. The effect was clearly shown when the Au
solution was flushed, followed by a de-ionised blank after a flushing time of one
minute.
6.8 DETERMINATION OF THE BASE METAL COMPOSITION OF
THE RCCs.
6.8.1 Developing a method for the dissolution of the RCCs prior to analysis
The platinum industry is known for using pressure dissolution (PD) to dissolve
complex metals and it was decided that this technique should be investigated for
the dissolution of the RCCs. A portion of the sample was placed into a glass
ampoule, together with conc. HCl acid and saturated with Cl2 gas at about – 22 0C, using solid CO2. After sealing of the glass ampoules with a blow torch, they
were placed into stainless steel vessels. These vessels were placed into a furnace
and heated to 250 0C for about twenty four hours or until the sample was
dissolved [53]. This technique was successful for the dissolution of the RCCs, but
as a result of problems encountered, it was not used as the dissolution process for
the experiment and an alternate technique was investigated.
The hardness of the RCCs was between 5.5 and 6.5, which rendered the crystals
resistant to dissolution using normal acidic digestion. Although aqua regia is well
known for the digestion of PGEs, it is ineffective for digesting resistant matrix
phases such as chromite, which are not effectively wetted by aqua regia [71]. In the
chrome industry, acidic mixtures of 1:1 H3PO4:H2SO4 are used to digest
ferrochrome samples for the analysis of chromium. It was decided therefore to
employ a combination of these acids for the dissolution of RCCs using both HP
and MW digestion.
During the optimisation process however, total dissolution of the RCCs was not
obtained with small residual black particles visible inside the beaker. After
performing a particle size distribution analysis of the crystals, it was decided to
micronize the sample to about 95% < 5um, with a view to enhancing dissolution
and possibly releasing any enclosed PGEs minerals within the crystals. The HP
97
and MW digestion techniques were further optimised and after the milling
process, total dissolution was achieved and clear dark green solutions resulted.
The two methods developed are discussed in Chapter 5, sections 5.9.5 and 5.9.6.
The microwave digestion parameters for the Anton Paar GmB multiwave
microwave system are found in Appendix 2, section 2.3.
6.8.2 Base metal composition of the RCCs
A SPECTRO GENESIS ICP-OES was used for the determination of the base
metal elements Cr, Fe, Mg, Al, Mn, Ti, V and Si. The RCCs solutions were
prepared in quadruplicate over 2 days with the reference standard SARM 9
prepared in duplicate. The major and minor base metal concentrations of the
RCCs are shown in Figure 6.6 and Figure 6.7.
Figure 6.6 The major base metal composition of the RCCs as obtained using
HP and MW digestion techniques.
98
Figure 6.7 The minor base metal composition of the RCCs as obtained using HP
and MW digestion.
The HP and MW digestion results were compared using Significance testing
(t – Test). The t-test for independent sample means (equal and unequal variance)
was used and the null hypothesis defined as (H0): μ1 = μ2, i.e. there was no
significant difference between the means of the two methods for the elements Cr,
Fe, Mg, Al, Mn, Ti, V and Si, against the alternate hypothesis (H1): μ1 ≠ μ2, i.e.
there was a significant difference between the means of the two methods for the
elements Cr, Fe, Mg, Al, Mn, Ti, V and Si. The difference in standard deviations
was tested using the F-Test to determine whether to use the t-test for equal and
unequal variance. The HP and MW digestion comparison data are found in
Appendix 2, Section 2.4.
According to the results, there was no significant difference between HP and MW
digestions for the elements Fe, Mn and Ti at the 95 % two-tailed, confidence level
(CL). However, the results reported for HP and MW digestion were significantly
different for the elements Cr, Al, Mg and V at the 95 % two-tailed CL.
The biggest difference reported for the two digestion methods were for the
elements Al, with HP digestion reporting 1.07 % higher than MW digestion, Fe,
with HP digestion reporting 0.58 % higher than MW digestion and Mg, with HP
99
digestion reporting 0.37 % higher than MW digestion. Naturally it would be
expected that MW digestion should be more effective than HP digestion as it has
the advantage of introducing controlled factors such as temperature and pressure
to the digestion process. Surprisingly, higher values were reported for HP
digestion possibly as a result of the greater volumes of acid used which in turn
may have introduced additional impurities. Nevertheless, the precision of MW
digestion was very good when compared to HP digestion, which also suggested
that systematic errors had been introduced during sample preparation using HP
digestion. The precision data shall be discussed in section 6.8.4.
Chapter 3, Table 3.1, listed accessory minerals of the UG2 Reef and good
correlation existed between these minerals and the chemical analysis of the RCCs.
The oxides: Cr2O3, Fe2O3, MgO and Al2O3 represent both the major composition
of chromitite crystals and are reflected in the chemical analysis shown in table
6.7. The UG2 Reef also contains minerals such as ilmenite (FeTiO3), rutile (TiO2)
and ulv�spinel (Fe2TiO3). The chemical analysis for titanium as an oxide is
shown in Table 6.20.
6.8.3 Accuracy of the method
The reference material SARM 9 which was selected for accuracy testing was of
chromite origin and was representative of the RCC matrix. A comparison of the
base metal analysis of SARM 9 to the certified values (C.V.) of SARM 9 is shown
in Table 6.20.
Table 6.20 Comparing base metal results obtained for SARM 9 using HP and
MW digestion to certified values.
Base metals
Mean ± SD MW (%)
Mean ± SD HP (%)
C.V. %
Cr2O3 45.90 ± 0.16 45.41 ± 0.45 46.45 ± 0.040
Fe (Total) 18.79 ± 0.06 18.82 ± 0.19 19.41 ± 0.045
Al2O3 15.93 ± 0.14 15.87 ± 0.25 15.17 ± 0.135
MgO 11.09 ± 0.08 11.06 ± 0.08 10.85 ± 0.07
100
TiO2 0.57 ± 0.01 0.61 ± 0.01 0.56 ± 0.01
V2O5 0.34 ± 0.004 0.36 ± 0.01 0.32 ± 0.01
MnO 0.25 ± 0.01 0.27 ± 0.01 0.21 ± 0.01
SiO2 < 0.566 < 0.566 0.61 ± 0.01
Recoveries of the major composition elements: Cr2O3, Fe2O3, Al2O3 and MgO are
displayed in Table 6.21.
When assessing new methods in the platinum industry, recoveries between 98 and
102% are considered acceptable. The analysis of chrome with its impact upon the
smelting process and Fe because of its impact on other processing steps; are
considered more critical than the oxides of Al and Mg. Therefore, the results of
these critical elements should be accurate and precise. Cr and Mg recoveries were
between 98 and 102%, which was considered acceptable. Fe was under-recovered
while Al was over-recovered possibly due to contamination or systematic errors
introduced during sample preparation and matrix matching. The MW digestion
method was better for the dissolution of Cr than HP digestion with Fe slightly
under recovered by both MW and HP digestion.
Table 6.21 Recovery percentage calculated for the analysis of SARM 9 using
HP and MW dissolution
Methods Cr2O3
%
Fe
(% Total)
Al2O3
%
MgO
%
MW 99 97 105 102
HP 98 97 105 102
Factors which affect the digestion processes are: particle size, digestion time and
the type of acid mixture selected. Since the particle size of the RCCs had been
reduced to 95 % less than 5 μm this would suggest that digestion time and acid
mixture should be further optimised to improve Fe recoveries. A microwave
power setting of 500 W was sufficient to have resulted in sample loss. Overall, the
recoveries were satisfactory but could be improved by further optimisation.
101
6.8.4 Precision of the results
Repeatability data was obtained over a period of 2 days and statistical analysis
performed on the data. The precision of the results obtained for digestion of the
RCCs is compared and discussed below. Precision of the HP and MW digestion
methods were expressed as % RSD and are shown in Table 6.22 and Figure 6.6.
Table 6.22 The mean, standard deviation and % RSD values calculated for the
RCCs.
Fe % Total
Cr2O3 %
Al2O3 %
MgO %
MW HP MW HP MW HP MW HP Mean 20.63 20.72 41.01 41.59 16.04 17.13 8.39 8.76
SD 0.10 0.21 0.23 0.29 0.13 0.37 0.05 0.18 % RSD 0.49 1.01 0.56 0.70 0.82 2.16 0.63 2.10
For the reasons listed below, overall precision obtained by MW digestion was
superior to that achieved by HP digestion for the elements Cr, Fe, Al, Mg, Mn, Ti
and V. The %RSD values obtained by MW digestion for the major components
were all less than 1% as shown in Figure 6.8. MW digestion was performed under
controlled conditions, with temperature and pressure monitored by sensors. MW
digestion was also closed thereby preventing volatile components from
evaporating. HP digestion was not controlled and the digestion times varied. This
procedure was prone to systematic errors and this was reflected by the higher
%RSD results obtained during digestion.
102
Figure 6.8 Illustrating the difference in the %RSD values obtained between HP
and MW digestion methods
6.9 DETERMINATION OF THE PGE COMPOSITION OF THE RCCs.
6.9.1 Composition of the PGE concentration
Te co-precipitation methods developed for pre-concentration of the precious
metals as tellurites, have been discussed in Chapter 5, sections 5.9.7 and 5.9.8.
This method is quantitative for the elements Pt, Pd, Rh and Au but only semi-
quantitative for Ru and Ir.
All chemicals used during the dissolution of the tellurium precipitate were of ultra
pure grade to minimize interference during ICP-MS analysis. Calibration
standards were prepared freshly on a daily basis to prevent contamination and also
to stabilize Au solution in 2 M HCl, (Au becomes instable at less than 2 mg L-1).
It is known that the reason for instability at the part-per-billion (ppb) level is due
to adsorption onto the container walls. [76]
Results obtained for precious metal analysis using MW digestion are shown in
Table 6.23. Accordingly, the RCCs were found to contain a predominance of Pt
and to a lesser extent Pd and Ru. As indicated in Figure 6.5, only trace
compositions of Au and Ir are present in the UG2 Tailings sample, 10 ug kg-1 and
103
70 ug kg-1 respectively. It was unsurprising therefore that the elements Au and Ir
were not detected in the residual chromitite crystals (RCCs). This may also
suggest that any residual PGM containing minerals of Ir and Au may be found, if
present, in the siliceous material of tailings and not in the chromitite crystals.
The precision obtained for the isotopes 195Pt and 105Pd were less than 10 %RSD,
compared to the isotopes of 102Ru and 106Pd which were greater than 30 %RSD. It
would be expected that the precision obtained for Ru would be poorer due to
semi/quantitative recovery by the Te co-precipitation process and because Ru is
also known for its volatility. The lower precision for the isotope of 106Pd may be
as a result of greater interference, which may have contributed to the higher
measurement uncertainty when compared to the isotope 105Pd.
Table 6.23 The precious metal analysis obtained for the RCCs using MW
digestion
Isotopes
concentration
μg kg-1 SD
μg kg-1
RSD
%
102Ru 4.84 0.89 33.98 103Rh < 0.6 - - 105Pd 9.78 0.79 8.06 106Pd 7.99 2.44 30.54 191Ir n.d. n.d. n.d. 193Ir n.d. n.d. n.d. 194Pt 22.62 2.89 12.78 195Pt 27.25 2.05 7.53 196Pt 27.80 3.87 13.93
197Au n.d. n.d. n.d. n.d. - Not detected
Results obtained for the precious metal analysis using HP digestion are presented
in table 6.24. As per MW digestion, the elements Au and Ir were not detected in
the RCCs, whilst traces of Pt, Pd, Rh and Ru were found. Results reported for Rh
and Ru were slightly higher than for MW digestion. The difference in results and
precision between MW and HP digestion was probably due to random and
104
systematic errors introduced by HP digestion method and interference was not
improbable.
Table 6.24 The precious metal analysis obtained for the RCCs using HP
digestion
Isotopes
concentration
μg kg -1
SD
μg kg -1
RSD
%
102Ru 13.07 1.41 10.78 103Rh 10.30 2.56 24.82 105Pd 15.61 5.95 38.08 106Pd 8.59 3.12 36.29 191Ir n.d. n.d. n.d. 193Ir n.d. n.d. n.d. 194Pt 16.48 2.30 13.94 195Pt 16.28 2.23 13.72 196Pt 17.71 1.80 10.19
197Au n.d. n.d. n.d.
n.d. - Not detected
6.9.2 Recovery testing
The greatest concern about accuracy in trace analysis is the means of its
assessment. In reality, for the majority of work at trace levels appropriate CRMs
are not available. An alternate approach would be to verify a trace result from one
technique by comparing it to a trace result from another technique. Due to the
lack of appropriate CRMs, it was decided to use recovery testing to prove
accuracy of this technique.
The objective of the recovery testing was to determine the applicability of the
tellurium co-precipitation method for the recovery of the precious metals in an
acidic solution, which would be referred to as matrix 1. The results obtained from
the recovery testing of matrix 1 are found in Table 6.25. It was also necessary to
assess whether the presence of base metals affected the recovery of the precious
105
metals under the test conditions chosen for the method and would be referred to as
matrix 2. The procedure followed for the recovery testing is explained in Chapter
5, section 5.5.1.
Table 6.25 The percentage recovery data obtained for matrix 1
Matrix 1 Spiked
μg L-1 Obtained ± SD
μg L-1 Recovery
% 102Ru 250
750 219 ± 42 736 ± 24
87 98
103Rh 250 750
245 ± 15 750 ± 12
98 98
105Pd 250 750
229 ± 30 761 ± 63
101 92
106Pd 250 750
245 ± 23 749 ± 24
101 98
191Ir 250 750
252 ± 19 767 ± 132
100 101
193Ir 250 750
256 ± 11 717 ± 84
102 102
194Pt 250 750
242 ± 21 736 ± 61
96 97
195Pt 250 750
243 ± 26 739 ± 14
98 97
196Pt 250 750
251 ± 23 746 ± 60
99 100
197Au 250 750
231 ± 25 719 ± 25
98 92
For analysis, the final concentrations of 250 μg L-1 and 750 μg L-1 PGEs were
diluted ten times to fit on the calibration range at concentrations of 25 μg L -1 and
75 μg L -1 PGEs. Each dilution was prepared in triplicate. A satisfactory recovery
of more than 96% of microgram quantities of platinum, palladium, rhodium and
gold was obtained by this method in the absence of base metals. As before with
the knowledge that Ru is not quantitatively recovered using the Te co-
precipitation process it is not surprising that Ru slightly under recovered with 87%
at concentration levels of 250 ug L-1. No information in the literature is found to
indicate to what extent Ru is under recovered using Te co-precipitation.
According to Palmer et al. [40] the recovery of the element Ir is apparently higher
106
than that of Ru using Te co-precipitation. Ir showed recoveries of up to 102%,
which may have been due to interference from the solution matrix.
Table 6.26 The percentage recovery data obtained for matrix 2
Matrix 2 Spiked
ug ml -1 Obtained ± SD
ug ml -1 Recovery
% 102Ru 250
750 176 ± 59 681 ± 116
70 91
103Rh 250 750
227 ± 18 749 ± 25
91 100
105Pd 250 750
222 ± 18 679 ± 64
89 91
106Pd 250 750
233 ± 21 716 ± 62
93 95
191Ir 250 750
234 ± 12 715 ± 90
93 95
193Ir 250 750
258 ± 10 678 ± 61
103 90
194Pt 250 750
230 ± 23 661 ± 60
92 88
195Pt 250 750
237 ± 33 723 ± 42
95 96
196Pt 250 750
239 ± 32 729 ± 32
96 97
197Au 250 750
230 ± 18 712 ± 28
92 95
Investigations performed by Palmer et al. [40] showed recoveries of more than 96%
for microgram quantities of platinum, palladium, rhodium and gold in the
presence of base metals. The base metal concentrations added during their
investigations were: Ca at 1500 mg l-1, Fe at 1000 mg l-1, Mg at 375 mg l-1, Ni at
50 mg l-1 and Al at 500 mg l -1. The results obtained from the recovery testing of
matrix 2 are found in Table 6.26.
Matrix 2 represents the composition of SARM 9, where the major elements are
Cr, Fe, Mg and Al. Recoveries although still above 90% were lower at
concentration levels of 250 μg L -1 for Pt, Pd, Rh and Au. The recoveries were at
or above 95% at concentration levels of 750 μg L -1 for Pt, Pd, Rh and Au. The
recoveries obtained for the element Ru varied between 70 to 91% and for Ir
107
between 90 to 103%. These recoveries were obtained in the base metal presence
of Fe at app. 2300 mg L-1, Cr at app. 4000 mg L -1, Mg at 600 mg L-1 and Al at
app. 1000 mg L-1.
The precision of the overall recovery test was less than 10 %RSD for the elements
Pt, Pd, Rh and Au with Ru and Ir at approximately 20 %RSD.
Although the TeCl4 concentration was increased during Te co-precipitation to
compensate for the higher Fe and Cr in solution; the recoveries of trace amounts
of Pt, Pd, Rh and Au were still adversely affected.
The significance of this effect on ultra trace PGEs concentration was not
determined.
6.9.3 GFAAS was used for the verification of the trace amounts of PGEs in
the RCCs
It was decided to use GFAAS as an alternate technique to verify the trace PGEs
concentrations obtained by ICP-MS. According to Gupta [49], Te only interferes
with Au with no interference reported for the elements: Pt, Pd, Rh, Ru and Ir
when using Te co-precipitation as collection technique by GFAAS. This is due to
the high pyrolysis temperature used during analysis by GFAAS for these
elements. Only the elements Pt and Pd were verified using GFAAS and the
instrumental parameters can be found in Appendix 3, section 3.1.
Despite both ICP-MS and GFAAS, theoretically being capable of ultra trace level
detection, the limit of detection for the method is generally dictated by the
chemical preparation. Procedural blanks were examined by using exactly the same
method but without sample being included because they reflect reagent
contaminant for sample preparation. The LOD was assessed from these analyses.
Only four procedural blanks were prepared and assessed. The LOD values for Pt
and Pd were converted to μg kg-1 or ppb and are shown in Table 6.27.
108
Table 6.27 The LOD values expressed for Pt and Pd using GFAAS
Wavelength (nm) LOD (μg L-1) LOD (μg kg-1)
Pt 265.9 6.24 31.25
Pd 224.8 9.92 49.60
The LOD values obtained for the method using the PG – 990 GFAAS instrument
were much higher that the LOD values obtained by the SPECTRO MASS 2000
ICP-MS instrument for the same sample type. Chapter 4, section 4.4, refers to the
detection capabilities for the major spectroscopic techniques and from that it is
evident that the ICP-MS is capable of producing superior detection limits
compared to the GFAAS instrument. Although the samples were analysed for Pt
and Pd by GFAAS, the results produced were below the LOD of the method and
the PGE results obtained by ICP-MS could not be verified with confidence.
6.9.4 NiS-FA by ICP-MS used for the verification of trace amounts of PGEs
in the RCCs
Determination of precious metals at ultra trace levels in geological and mining
matrices remains difficult even after the arrival of more sophisticated
instrumentation like ICP-MS. The greatest challenge is to develop a method
which shall remove the complex matrix of the material while simultaneously pre-
concentrating the precious metal present at trace level such that, these elements
may be defineable using sophisticated instrumentation. As discussed in Chapter 3,
Pb-FA and NiS-FA collection techniques combined with other analytical
techniques are very effective for the determination of precious metal
concentration at mg kg-1 (ppm) levels. Only recently have mining industries
started developing and improving their analytical techniques to analyse at ultra
trace levels such as μg kg-1 (ppb).
One such technique suggested within the mining industry is the use of NiS-FA in
conjunction with ICP-MS for trace analysis. It was therefore decided to analyse a
portion of the RCCs together with two reference standards: GBW0792 (chromite
matrix) and GBW07293 (platinum ore) at ultra trace level, using NiS-FA by ICP-
109
MS as an alternate technique to verify the PGEs results obtained by Te co-
precipitation. The reference standard SARM 76 was included as quality control to
measure PGEs at trace level concentration.
Although the in-house reference standard of SARM 76 compared well with its
certified values at PGEs trace concentration level, the results produced for the two
reference materials were inaccurate at the ultra trace concentration level. At such
ultra trace concentration levels many factors may have contributed to such
inaccuracy, not least that, the NiS flux may have been inappropriate for the
sample matrix. There may also have been process contamination or that possibly
an inappropriate calibration range was used. In industrial practice measurement
uncertainty at ultra-trace concentration level also remains unacceptably high.
Although the absence of a suitable CRM and the ineffective nature of ICP-MS
and GFAAS and FA NiS/ICP-MS for the determination of what turned out to be
ultra trace levels of PGEs in the RCCs meant that the analysis by Te co-
precipitation/ICP-MS could not be verified quantitatively, undoubtedly PGE’s
were detected. In the absence of such verification it was decided that mineralogy
studies like SEM/EDS and EPMA should be employed as alternate techniques to
confirm the presence of PGEs in the RCCs.
6.10 MINERALOGICAL STUDIES PERFORMED ON THE RCCs
6.10.1 Morphology study of the RCCs
Results obtained by mineralogy studies are found in Figure 6.9.
a) S1 X 160 b) S2 X 250
110
c) S3 X 180 d) S4 X 150
e) S5 X 190 f) S6 X 95
g) S7 X 140
h) S8 X 250
111
Figure 6.9 a – h Scanning electron micrographs of residual chromitite crystals
(RCCs), at different magnifications.
Four polished thin sections of the RCCs and two polished sections of chromite
from UG2 ore were studied by optical microscopy and then by SEM/EDS using
JEOL JSM-840. The morphology study was performed on different chromite
crystals to identify the different crystal shapes. The literature describes chromitite
crystals as commonly massive, granular to compact, which can be seen in Figure
6.11.
Figure 6.10 Chromitite crystals exposed from a UG2 ore sample
Crystal growth depends on conditions, which include external influences such as
temperature, pressure nature of solution, direction of flow of the solution and
availability of open space for free growth. The angular relationship, size and
shape of faces on a crystal are aspects of crystal morphology [61]. Chapter 3,
section 3.3.4, discussed the crystal structure of chromium in more detail.
The SEM photographs as displayed in Figure 6.10 (a-d), and d, are residual
chromitite crystals extracted from a UG2 Tailings sample taken at different
magnifications. The crystals vary in shape considerably from elongated needles to
polygonal. Even a perfect hexagon was evident. The reason for this has already
been discussed under the particle size distribution analysis and, is that, during
mineral processing the bulk sample is milled to achieve 70% < 75 μm, which
assists in the release or liberation of PGEs minerals during the Concentrator
112
process. Thus some, but not all, the chromitite crystals get broken down into
smaller particle sizes. What is also interesting about the shape of these RCCs, are
the fact that they still have sharp edges, reflecting the hardness of these crystals
and are therefore rarely attacked during fusion with basic fluxes.
The SEM photographs as displayed in Figure 6.10 (e-h) and h are residual
chromitite crystals extracted from a UG2 ore sample which was crushed and
sieved to obtain unbroken crystals. These crystals were more circular and of
varying size. The photograph in Figure 6.10 h) shows the boundary of 2
chromitite crystals which are still attached to each other.
6.10.2 SEM/EDS studies performed for the identification of minerals in the
RCCs
a)
b)
Laurite
Chromite, oblong shaped crystal
Laurite Chromite, tabular shaped crystal
113
c)
Chromite, hexagon shaped crystal Laurite
d)
e)
Laurite
Pt,RuAsS mineral Laurite
Chromite crystal
114
f)
Chromite crystal PtNiFeCu impurity
Figure 6.11 a – f) Scanning electron micrographs showing the textures and
mineral assemblages of inclusions in the RCCs.
MINTEK were commissioned to perform a mineralogy study to identify whether
the RCCs contained PGEs minerals. The instrument used was a QEMSCAN E230
system consisting of a Zeiss EVO 50 SEM and Bruker EDS system. The
magnification used to locate the PGEs grains was 135 X, which provided a
detection limit of 0.7 μ (i.e. SEM image pixel size is 0.7 x 0.7 microns).
Ten polished thin sections were prepared from the RCCs extracted from the UG2
Tailings sample. In total 16 minerals were identified, some of which are displayed
in figure 6.11 a – f). Figure 6.12 (a-d), were identified as the mineral Laurite
(Ru(Os,Ir)S). In total 14 Laurite minerals were identified. Figure 6.11 e) shows
two minerals lying on top of each other i.e. Laurite and Pt,RuAsS. It is clear that
these particles were all locked or enclosed within the chromitite crystals and were
therefore not liberated. The minerals identified were all present in chromitite
crystals which were still unbroken. The last liberated particle identified in Figure
6.11 f) is that of PtNiFeCu which apparently is a base metal sulphide which is
more normally associated with Impala Converter Matte samples and thus was
obviously present due to contamination.
The particle sizes of each of these minerals were also measured. The Laurite
minerals varied between 2.71 to 4.83 μm while the (Pt,RuAsS) mineral was app.
4.23 μm in size. The impurity particle was measured to be app. 6.90 μm in size.
115
These particles were easily identifiable at a magnification of 135 X which
provided a detection limit of 0.7 μm. Detection limits increase with higher
magnification.
6.10.3 Electron probe micro analyser (EMPA) studies performed on the
RCCs for the identification of minerals as solid solution
A total of 20 polished sections were prepared and subjected to a particle search in
the Zeiss EVO MA15 Scanning Electron Microscope using the SmartPI software
to locate laurite minerals and base metal sulphides (BMS) particles. After location
and recording of these particles, it was introduced to the EPMA for relocation and
analysis. A camera SX50 microprobe, using wavelength dispersive spectroscopy
(WDS), was calibrated for counting the S Kα peak, Ru Lα peak, Os Mα peak and
Ir Mβ with the appropriate crystals. An accelerating voltage of 20 kV, a beam
current of 30 nA, with an electron beam diameter of app. 1 μm, was used.
Counting times of 30 seconds on the peak and 15 seconds on each of two
background positions, either side of the measured peak, were used. The Ir Mβ
peak was measured as there is an overlap of the Ir Mβ peak with the Os Mβ peak.
The detection limits at 95% confidence level are: Ru at 0.096%, Os at 0.066%, Ir
at 0.095% and S at 0.067%.
Nickel sulphide (NiS) and pure element standards were used to calibrate for S,
Ru, Os and Ir in solid solution.
Base metal sulphide (BMS) solid solution analysis
Chapter 3, section 3.5.2, discusses the occurrence of PGEs as solid solution in
BMS minerals, arsenides and sulfursenides, which are commonly found in
platinum ore. Although the UG2 Reef is known for its high chrome content and
lower base metal content compared to the Merensky Reef, it was decided to
proceed with the search for BMS minerals, such as pentlandite, for analysis of
possible PGEs as solid solution.
For BMS analysis by EPMA, the mineral particles need to be flat and of a suitable
size. The BMS minerals found in the RCCs were small, fractured and located at
116
the edge of the chromitite grains, presenting uneven surfaces for analysis.
Nevertheless, the largest problem was the very few BMS mineral particles found
in the chromitite sample, rendering any data obtained statistically invalid. Thus,
the BMS mineral particles could therefore not be analysed with reliable
confidence.
Laurite solid solution analysis
The analyses of Laurite found in the RCCs is presented in Table 6.27. From the
results it can be seen that the Laurite inclusions were ru rich, associated with
Osmium and to a lesser extent Iridium. By weight, Ruthenium constituted
approximately 50%, followed by Os at approx. 6% and Ir approx. 2% of the
sulphide mineral. The Laurite inclusions, were, as indicated above, polygonal with
particle sizes between 2 and 4 μm. The quantitative analysis of the Laurite grains
was adversely affected by the small the particle size < 3 μm, which contributed to
the low analysis totals. The high Ir total for grain no. 17, was due to an
interference with an Ir line from a small attachment of Pt-bearing phase. The
presence of S is in accordance with the sulphide mineral Laurite (Ru(Os,Ir)S).
Table 6.28 Electron microprobe analysis of laurite in a chromite sample
Grain Ru
Wt%
Os
Wt%
Ir
Wt%
S
Wt%
Total
Wt%
1 53.23 6.49 2.19 33.69 95.59 2 40.79 5.85 0.68 23.30 70.63 3 54.83 4.20 1.54 33.20 93.77 4 53.18 4.65 2.57 33.48 93.88 5 52.02 6.21 2.46 32.87 93.56 6 53.18 6.46 2.12 33.67 95.42 7 54.39 4.60 2.19 32.91 94.08 8 51.53 5.15 3.29 33.21 93.17 9 51.62 6.45 1.91 31.03 91.01 10 52.02 6.17 2.41 32.95 93.54 11 53.25 6.67 2.21 32.96 95.09 12 53.31 4.60 2.54 33.26 93.72 13 52.83 6.53 2.24 32.41 94.01 14 54.34 4.66 2.29 33.68 94.97
117
118
15 52.85 4.90 3.30 33.48 94.53 16 55.56 4.15 1.53 33.99 95.23 17 43.66 3.44 16.61 32.70 96.41 18 52.64 5.03 3.27 33.52 94.46 19 54.14 4.62 2.20 33.58 94.54 20 51.96 5.99 1.50 30.78 90.22 21 51.76 4.00 2.39 29.17 87.32
The SEM/EDS results obtained were successful for confirming the presence of
PGMs as mineral inclusions present within the RCCs. The EPMA results obtained
were largely successful in quantifying the Laurite minerals, where as indicated in
Section 3 the ability of Osmium and Iridium to interchange to varying degrees
with Ruthenium confirms that the precious metals in Laurite were present as solid
solution.
The mineralogy study was therefore successful in achieving the confirmation of
the presence of PGEs in the RCCs as determined using Te co-precipitation
methods.