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Advanced Techniques in EPMA Seminar August 7, 2010 University of Oregon Eugene, Oregon

A brief introduction to the FEI Mineral Liberation Analyzer ™ : the technique & results. Michael Shaffer INCO Innovation Centre Memorial University St. John’s, Newfoundland mshaffer@mun.ca. Advanced Techniques in EPMA Seminar August 7, 2010 University of Oregon Eugene, Oregon.

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Advanced Techniques in EPMA Seminar August 7, 2010 University of Oregon Eugene, Oregon

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  1. A brief introduction to the FEI Mineral Liberation Analyzer™: the technique & results Michael ShafferINCO Innovation CentreMemorial UniversitySt. John’s, Newfoundland mshaffer@mun.ca Advanced Techniques in EPMA Seminar August 7, 2010 University of Oregon Eugene, Oregon

  2. MLA:points of interest • Particle analysis • Rocks crushed, sized and representative • Most accurate • E.G, iron ore from Labrador • “Large particle” analysis • e.g., 25x45mm section • Questionably representative • Large grain sizes • textures • E.G, Himalayan garnet shist

  3. BEI: Fe-rich minerals

  4. Fe-rich minerals of interest& spectral ambiguity • Hematite & magnetite [Fe2O3 versus Fe3O4] • Generally not distinguishable with x-ray spectra • Associations important to client • Titano-magnetite • Distinguishable with x-ray spectra • BSE similar to Hm • Titanium important to client • Goethite or limonite [FeO(OH)•(H2O)n] • Generally with minor Al, Si, Mg, and usually distinguishable with x-ray spectra • BSE darker than Hm (BSE classification would be helpful) • Siderite [FeCO3] • Generally with Ca, Mg, Mn, and usually distinguishable with x-ray spectra • BSE darker than Hm (BSE classification would be helpful)

  5. Mineral modes Mineral Wt% Hematite 4.57 Magnetite 38.54 Ti_magnetite 0.09 Goethite 0.17 Limonite 0.08 Ilmenitend Rutile nd Corundum nd Quartz 35.55 Aluminosilicate nd Misc_silicates 0.11 Siderite 0.06 Siderit-Mn 0.11 Rhodochrosite nd Rhodo-FeMg 0.01 Rhodo-MgFe 0.00 Siderit-MgMn 7.37 Siderit-Mg 0.96 Ankerite 0.06 Calcit-MgMnnd Dolomit-FeMn 11.48 Magnesit-FeMn 0.22 Dolomite 0.15 Calcite 0.08 Unknown 0.02 Mineral Wt% Pyrolusite 0.00 Bixbyite_lo-Mnnd Bixbyite_hi-Mnnd Other_oxides 0.00 Olivine 0.00 Garnet 0.00 Cpx 0.01 Opx 0.02 Amphibole 0.00 Biotite 0.03 Feldspar 0.03 Muscovite 0.04 Serpentine nd Chlorite 0.14 Mn-rich_claynd Calcit-REE nd Pyrite 0.00 Pyrrhotite nd Chalcopyrite nd Sphalerite nd Misc_sulfidesnd Apatite 0.08 Miscellaneous 0.00 Misc_metals 0.01 Total 100.0 Mineral Wt% Magnetite 38.54 Hematite 4.57 Hm_or_Mt 0.00 Goethite 0.17 Limonite 0.08 Other_oxides 0.09 Quartz 35.55 Misc_silicates 0.38 Carbonates 20.50 Sulfides 0.00 Misc 0.09 Unknown 0.02 Total 100.0

  6. The particle table 4k to 20k particles

  7. Properties of particles Density Wt% Area% Area (microns) Area (pixels) Perimeter Max Span Length (MBR) Breadth (MBR) Hull Area Hull Perimeter EE Minor Axis Hull EE Minor Axis EE Major Axis (P&A) EE Minor Axis (P&A) EE Perimeter EC Diameter Angularity Enclosed Length Delta Form Factor All minerals (Wt%) e.g., Hematite (Wt%) Magnetite (Wt%) Goethite (Wt%) Limonite (Wt%) Quartz (Wt%) … Misc (Wt%) Unknown (Wt%) All elements (Wt%) e.g., Al (Wt%) Ca (Wt%) Cr (Wt%) Cu (Wt%) F (Wt%) Fe (Wt%) H (Wt%) K (Wt%) La (Wt%) Mg (Wt%) Mn (Wt%) Na (Wt%) Ni (Wt%) P (Wt%) S (Wt%) Si (Wt%) Ti (Wt%) … Zn (Wt%) Free Boundary, all minerals e.g., Hematite (%) Magnetite (%) Goethite (%) Limonite (%) Quartz (%) … Misc (%) Unknown (%)

  8. datamining the particle table

  9. Large sections

  10. Spectral discrimination ~ garnet

  11. grain boundaries resolved with BEI

  12. grain boundaries not resolved with BEI

  13. Grain associations

  14. The grain table More than 52,000 grains

  15. Properties of grains Density Center X Center Y Wt% Area% Area (microns) Area (pixels) Perimeter Max Span Max Span Angle Wt% (Particle) Area% (Particle) Wt% (Mineral) Area% (Mineral) Particle Max Span Particle Perimeter Length (MBR) Breadth (MBR) Angle Length (MBR) Hull Area Hull Perimeter EE Minor Axis Hull EE Minor Axis Hull EE Perimeter EE Major Axis (P&A) EE Minor Axis (P&A) EC Diameter Aspect Ratio Angularity Enclosed Length Delta Form Factor Boundaries with other minerals e.g., Quartz (%) Orthoclase (%) Garnet (%) Biotite (%) … free surface (%)

  16. datamining the grain table:mineral textures

  17. Applications at MUN • Mineral modes & associations • Mineral locking & liberation • Mineral searching (e.g., zircon, baddeleyite, monazite) • Includes x-y coordinate export • Precious mineral searching (e.g., Au, PGM) • Includes associations with host minerals • Provenance determinations • Sourcing continental river & till sediments (mineral prospecting) • Sourcing offshore sediments with onshore (oil & gas) • Lateral correlation of offshore sediments (oil & gas) • Some thought toward … • Accurate determination of trace minerals (e.g., apatite, corundum) • Invisible gold with a FEG MLA • Long-count EDX • Auxillary inputs …, e.g., WDX, μXRF

  18. Acknowledgements The MUN MLA team: David Grant Alan Maximchuk Dylan Goudie & thank you for your interest!

  19. A typical frame, BSE relative to Ni metal

  20. Is it possible with XBSE & MLA spectra? Difference is only 24 counts (2σ ~ 34) 15 counts (2σ ~ 58) 28 wt% O versus 30% Sensitive to absorption 72 wt% Fe versus 70% Sensitive to charging

  21. The spectral-classification result Red implies mineral grain is eitherhematite or magnetite

  22. BSE classification Hm Qtz “reliable” histogram Cumulative or “full” histogram Mt Other silicates, carbonates and hydroxides

  23. BSE-classification results – good & bad Magnetite Hematite “Darks”

  24. MLA BSE mode results – good & badthe smallest size fraction: -200 mesh

  25. Before “Merge Overlay” Processed via gray level segmentation Mode BSE data acquisition Classified data, modes, … Merge Overlay OR Processed via Spectral matching Mode XBSE data acquisition Classified data, modes, …

  26. MLA “merge overlay” tool

  27. Results from Merge Overlay • Spectrally classified “Hm-or-Mt” becomes: • Hematite, or • Magnetite, or • “Fe-ox_no-ID” • Which can generally be justified and grouped with limonite or goethite (… although pure siderite is also a possibility) • Smaller size fractions evaluated independently • Hm:Mt modal ratio might be assumed from larger SFs or their trends

  28. Reproducibility: mineral modes same samples – 6 months between Samples A, B, C & D

  29. Reproducibility: mineral modes same samples – 6 months between Samples A, B, C & D

  30. Reproducibility: mineral associations same samples – 6 months between Samples A, B, C & D

  31. Reproducibility: mineral associations same samples – 6 months between Samples A, B, C & D

  32. Results comparison:MLA v. Rietveld XRD

  33. Results comparison:MLA v. Rietveld XRD Average absolute errors

  34. Sources of data processing error

  35. Sources of instrumental error:electron beam illumination 195 = Hm 198 = Mt 192 = Hm 195 = Mt

  36. Sources of instrumental error:varying e-beam current 3rd frame 143rd frame 195 = Hm 198 = Mt 2 hours Later … 192 = Hm 195 = Mt

  37. Remedying BSE problems • Non-uniform illumination • No remedy if the SEM manufacturer did not anticipate applications in quantitative BSE • Except to use high magnification • Difficult to remedy if the SEM manufacturer did not provide alignment tools for uniformity • FEI Quanta SEMs: • Centering the illumination provided by e-gun tilt • Tetrode & gun alignment should be accurate • Illumination gradients worse for large spot sizes

  38. Remedying BEI problems • Varying beam current • Very common depending on age of filament … • Stability generally monotonic, i.e., not erratic • … allows for breaking the BSE JKF file into 2 to 4 files, thereby creating more reliable histograms that represent time periods during analysis. • Note also that this method is quite dependent on a significant amount of Hm-Mt in the sample, which builds a more accurate reliable histogram

  39. Anticipating problems we haven’t yet encountered, and possible improvements • MUN IIC has not yet applied this method to mineral assemblages other than the minerals discussed here • I.E., a severe complication would arise for significant amounts of titano-magnetite, thereby blurring the distinction of Hm in the reliable histogram • A very helpful improvement, which would allow the same tools to be applied to other applications, would be for the spectra-classified result to mask the minerals of interest to be classified with BSE

  40. MLA Mode BSE conclusions • Hm – Mt BSE discrimination works … • And Hm-Mt associations are possible • … but not specifically with other minerals • and, by itself, cannot discriminate most other minerals because of average atomic number (i.e., BSE ambiguity) • However, it presents a suitable solution for augmenting spectral classification (mode XBSE) • How to augment with spectral classification? …

  41. Summary • Hm–Mt BEI discrimination is possible … • Hm-Mt associations are possible, and with all minerals • Mineral modes and associations can be reproduced with acceptable accuracy • A comparison with quantitative XRD is within errors associated with the difficulty associated with representative down-sampling (XRD sampling independent of MLA sampling) • However, a well-aligned and stable SEM is necessary … • Electron beam illumination must be uniform over 1 – 2mm • Beam current must be stable over the 2 – 3hr analytical time (although data processing can accommodate a monotonic variation) • This technique is more generally applicable, even to more complex mineral assemblages when chemistry (x-ray spectra) aids in masking the minerals of interest

  42. Consider an independent approach …

  43. Exported BEI frames into 3rd-party software

  44. The masked & cleaned frames

  45. A clean histogram allows for automatic thresholding

  46. Independent software resultsfortunate & unfortunate

  47. Independent BEI conclusions • Hm – Mt discrimination works … • Associations Hm-Mt are not possible • Minerals of similar atomic number, identified by XBSE, do not affect calculated Hm:Mt • However, results can be biased if: • one mineral does not polish as well, or if • one mineral’s grain size is typically smaller • Not the best solution, but should be in the analyst’s toolbox

  48. The results for the client • Primary modes and associations come from mode XBSE. • Whereas we had been providing Hm:Mt via the independent method … • Because titano-magnetite and pyrite are minimal and correctable, we do not augment XBSE with additional BSE results. • The good news is that Hm-Mt associations are provided but the bad news is that Hm-Mt-Qtz associations are not. • What is needed …

  49. Results comparison:MLA v. Rietveld XRD Sample 1 SFs +100 & +200 sampling error

  50. Results comparison:MLA v. Rietveld XRD Sample 2 SFs +100 & +200

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