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An MKS PAMP GROUP Company
The Eighth LBMA Assaying & Refining Conference, Royal Garden Hotel, Kensington, London, 17-20 March 2019
ANALYSIS OF GOLD 995‰ VIA DIFFERENT METHODSpresented by Daniela Manara and Barbara Badiello
PAMP
Selecting a method: the key factors
2
The selection of an analytical method is based on several key factors
Equipment
Sample preparation
Certified reference material
Skills
Costs
Uncertainty
Analysis of Gold 995 ‰ via different methods – The Eighth LBMA A&R Conference, London, 17-20 March 2019
PAMP
Our study is based on an inductive approach
The methodology: a study based on real data available
3
DEDUCTION
CONFIRMATION
OBSERVATION
COMPARISON
INDUCTION
COMPARISON
PATTERN
OBSERVATION
Analysis of Gold 995 ‰ via different methods – The Eighth LBMA A&R Conference, London, 17-20 March 2019
PAMP
Steps and objectives
4
Overview1
Comparison2
Evaluation3
Focus on instrumental conditions
No theory on spectroscopy
Focus on statistical conditions
No introduction on statistics
Interpretation of the results
Analysis of Gold 995 ‰ via different methods – The Eighth LBMA A&R Conference, London, 17-20 March 2019
PAMP
The range of methods available: main PROs and CONs
5
METHOD ADVANTAGES DISADVANTAGES
SPARK - OES• Time• Morphology• Uncertainty
• Indirect analysis• Certified reference material• Line range
ICP OES• Certified reference material• Line range
• Indirect analysis• Preparation• Time
WD XRF• Line range• Non-destructive• Uncertainty
• Certified reference material• Morphology• Indirect analysis
FIRE ASSAY• Direct analysis • Time
• Skills
Analysis of Gold 995 ‰ via different methods – The Eighth LBMA A&R Conference, London, 17-20 March 2019
PAMP
The methods available at PAMP
6
Fire assay
Nabertherm
ISO17025 accredited
SPARK OES
Ametek Labm / Labs
ISO17025 accredited
ICP OES
Agilent Varian 720 ES
Interlaboratory tested
WD XRF
Thermo ARL Advant’XP
Interlaboratory tested
Analysis of Gold 995 ‰ via different methods – The Eighth LBMA A&R Conference, London, 17-20 March 2019
PAMP
The dataset
7 Analysis of Gold 995 ‰ via different methods – The Eighth LBMA A&R Conference, London, 17-20 March 2019
PAMP
Results analysis
8
Check of normal distribution?
Elimination of outliers?
Analysis of variance (ANOVA)?
Principal component analysis (PCA)?
Analysis of Gold 995 ‰ via different methods – The Eighth LBMA A&R Conference, London, 17-20 March 2019
PAMP
All data in the dataset confirm a normal distribution
Results analysis
9
Check of normal distribution
Elimination of outliers?
Analysis of variance (ANOVA)?
Principal component analysis (PCA)?
Analysis of Gold 995 ‰ via different methods – The Eighth LBMA A&R Conference, London, 17-20 March 2019
PAMP
3,7% outliers removed from the dataset
All data in the dataset confirm a normal distribution
Results analysis
10
Check of normal distribution
Elimination of outliers
Analysis of variance (ANOVA)?
Principal component analysis (PCA)?
1700.0
1800.0
1900.0
2000.0
2100.0
Ag
2700.0
2750.0
2800.0
2850.0
2900.0
2950.0
3500.0
3600.0
3700.0
3800.0
SPARK - LABS WD XRF ICPSPARK LABM
Discrepancy
Discrepancy
No discrepancy
Analysis of Gold 995 ‰ via different methods – The Eighth LBMA A&R Conference, London, 17-20 March 2019
PAMP
There is no significant difference between groups
3,7% outliers removed from the dataset
All data in the dataset confirm a normal distribution
Results analysis
11
Check of normal distribution
Elimination of outliers
Analysis of variance (ANOVA)
Principal component analysis (PCA)?
Au
Ag
Cu
Test for equal means
Sum of sqrs dfMean square F
p (same)
Betweengroups 0.0549767 3 0.0183256 0.02425 0.9949
Withingroups 87.6689 116 0.755767
Permutation p (n=99999)
Total 87.7239 119 9.95E-01
Kruskal-Wallis test for equal medians
H (chi2): 0.2459
Hc (tie corrected): 0.246
p (same): 0.9699
There is no significant difference between sample medians
Test for equal means
Sum of sqrs dfMeansquare F
p (same)
Betweengroups 96628.6 3 32209.5 0.06156
9.80E-01
Withingroups 5.34E+07 102 523228
Permutation p (n=99999)
Total 5.35E+07 105 0.9801
Kruskal-Wallis test for equal medians
H (chi2): 0.3741
Hc (tie corrected): 0.3741
p (same): 0.9455
There is no significant difference between sample medians
Test for equal means
Sum of sqrs dfMean square F
p (same)
Betweengroups 21137.3 3 7045.77 1.292 1.281
Withingroups 589087 108 5454.51
Permutation p (n=99999)
Total 610224 111 0.2773
Kruskal-Wallis test for equal medians
H (chi2): 5.394
Hc (tie corrected): 5.395
p (same): 0.9451
There is no significant difference between sample medians
Analysis of Gold 995 ‰ via different methods – The Eighth LBMA A&R Conference, London, 17-20 March 2019
The dataset can be used for furtheranalysis adding new variables
PAMP
Results analysis – Principal Component Analysis (PCA) /1
12
Three new variables are introduced
Frequency of use for each method1
Skills needed (training investment needed)2
Time needed for the analysis3
Analysis of Gold 995 ‰ via different methods – The Eighth LBMA A&R Conference, London, 17-20 March 2019
PAMP
Results analysis – Principal Component Analysis (PCA) /2
13
PC Eigenvalue % variance
1 489.201 99.429
2 2.03626 0.41386
3 0.699681 0.14221
4 0.0715112 0.014534
PC 1 PC 2 PC 3 PC 4
Au 0/00 -0.010 0.992 1.000 0.001
Time 1.000 -0.001 0.000 0.000
Use frequency -0.682 0.113 -0.004 0.722
Skill 0.995 0.037 0.000 0.062
The method choice is directly influencedby the duration of the analysis (mainly)
and by the skills required
The frequency of use is indirectly
proportional to Time and Skills required
Fineness is not influencedby method selection
The most used method is the less time-intensive The less time-intensive method is the one requiring less
training time The results delivered by each method are equivalent
PCA interpretation
Analysis of Gold 995 ‰ via different methods – The Eighth LBMA A&R Conference, London, 17-20 March 2019
PAMP
Conclusions
14 Analysis of Gold 995 ‰ via different methods – The Eighth LBMA A&R Conference, London, 17-20 March 2019
In addition to fire assay, spectrometry offers a wide range of technical options in analysing high grade gold
Precision was not compared in this study, as only average values are consideredAdding this parameter in the dataset could lead an interesting additional analysis
The cost for each analysis could also be an interesting variable to compare and correlate with others
Our goal, with the results of this work, is to provide the «spark» towards further study on the impact and opportunity of merely organisational&managerial parameters on analytical methods selection