CHAPTER 6: RESULTS AND DISCUSSION

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 %.


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


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


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.


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.


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,



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.


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


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


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.


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 %.


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


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,



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.


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


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


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.


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.


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


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.

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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.

CHAPTER 6: RESULTS AND DISCUSSION

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