Advancing Feature Analysis and Spectrum Imaging in Scanning Electron Microscopy
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1 Advancing Feature Analysis and Spectrum Imaging in Scanning Electron Microscopy Automated EDS analysis for geoscience, mineralogy and mining. Bruker Nano GmbH, Berlin Webinar, March26 th, 2014 Innovation with Integrity
2 Presenters Dr. Tanja Mohr-Westheide Postdoc/Research Assistant, Museum für Naturkunde, Berlin, Germany Dr. Tobias Salge Senior Application Scientist EDS Bruker Nano GmbH, Berlin, Germany 2
3 Overview Methods for mineral applications Automated feature analysis using computer-controlled SEM Mineral detection by morphological and chemical classification Advanced EDS analysis by spectrum imaging Modal analysis Low voltage EDS analysis (<7 kv) Enhancement of spatial resolution for element analysis Applications Industrialized minerals (Fe-oxides) Early exploration for mineral assets (REE, As, Te, S) Academic research (PGE) 3
4 State-of-the-art XFlash SDD Specifiations of 6th generation FWHM of 121 ev (Mn-Kα) up to 100 kcps High pulse throughput up to 600 kcps Multi detector and multi segment option Improved standardless quantification for light element / low energy analysis Combination of true standardless and standard-based quantification SEM, STEM, EPMA, MLA, QEMSCAN 4
5 Spatial resolution of X-rays analysis Electron transparent and bulk sample 1µm 1µm Si bulk sample 150 nm thin FIB lamella Semiconductor bulk sample 30 kv 1µm 100 nm 30 kv 4 kv 100 nm Low lateral resolution Salge (2012) 1µm 1µm 5
6 Introduction Particle analysis Particle sample (BSE Image) Image binarization Automatic detection of particles and image analysis particle morphology (area, length, width, aspect ratio, diameter, ) Automated collection of EDS spectra (each particle) quantification of EDS spectra Classification of particles based on pre-defined chemical groups Review, data analysis and reporting 6
7 Feature software for particle analysis Fully integrated into ESPRIT software Automated feature analysis using computer-controlled SEM (including Job- and StageControl to cover larger sample areas) Two steps: A) Sizing: Particle detection by image analysis particle morphology A B B) Chemistry: EDS spectra & chemical classification 7
8 Feature software Method setup A) Particle detection: Image filters 8
9 Feature software Method setup A) Particle detection: Binarization 9
10 Feature software Method setup A) Particle detection: Morphological filters 10
11 Feature software Method setup A) Particle detection: Analysis 11
12 Feature software Method setup A) Particle detection: Property filters 12
13 Feature software Method setup A) Particle detection: Display 13
14 Feature software Result A) Particle detection Summary for particle detection (Sizing) Automatic detection of multiple phases Improved particle segmentation/ separation with morphology and property filtering Setup can be stored as method file Link between particle image and list Any image can be loaded and analyzed here 14
15 Feature software Method setup B) Chemical classification Set up EDS spectrum acquisition (measuring time) Option to scan full particle (also with guard band to omit edge/ particle boundary effects Set up quantification method Set up and define chemical classes with multiple chemical concentrations, comparisons and operations 15
16 Feature software Result B) Chemical classification Link between EDS spectrum, particle image and list: 16
17 Feature Software Review function Results can be sorted according to classes Search for and drive to specific particle or field (with StageControl) Build panorama image Re-classification and/or re-quantification without re-acquisition 17
18 Feature Software Data analysis with histograms and charts Available diagrams for data analysis and reporting: histogram binary charts ternary charts Any particle property (morphological parameter) or element (wt%, atom%, ) can be plotted Link between data point in diagrams, particle list and spectrum to find specific particles of interest 18
19 Feature software JobControl for analyzing multiple frames 19
20 Mosaic of particle analysis result overlain with BSE micrograph 3 mm 20
21 Overview Applications Industrial minerals Magnetite and hematite in iron ore pellets Early exploration for mineral assets High-demand elements (REE) in laterite Sulfides, arsenides and tellurides from the Sudbury Igneous Complex Academic research Identifying traces of mega-impacts in Earth s ancient history (PGE) 21
22 Automated feature analysis Measurement conditions Parameter Conditions Remarks BSE threshold Multiple/ single All / selected particles Pixel resolution µm range Image acquisition dwell time 2-16 µs HV 15-25kV 3 times higher than smallest feature of interest Depending on BSE detector performance Spatial resolution in µm range Shaping time/ Dead time 130 kcps/ 30 % ~90 kcps output count rate Spectrum acquisition time s Sufficient impulse statitistics for chemical classification Depending on overlapping peaks, relevant element concentration 22
23 Altered carbonatite Classification of monazite and pyrochlore Composite of 64 BSE images Salge et al. (2013a) Bariopyrochlore Ba 0.3 Sr 0.2 Ca 0.1 Nb 1.8 Ti 0.2 O 5.6 (H 2 O) 0.8 Plumbopyrochlore Pb 0.8 Y 0.2 U 0.1 Ca 0.1 Nb 1.4 Si 0.2 Fe Ta 0.1 O 6.2 (OH) 0.5 Zirconolite Ca 0.8 Ce 0.2 ZrTi 1.5 Fe Nb 0.1 Al 0.1 O 7 Hollandite Ba 0.8 Pb 0.2 Na 0.1 Mn Fe Mn Al 0.2 Si 0.1 O 16 23
24 Pyrochlore Deconvolution of overlapping peaks cps/ev Ta Sr Zr Nb Pb cps/ev U~0.4 mass% Th U Ca HV: Time: 20 kv 3 s SDD: 30 mm 2 Max. throughput: 130 kcps FWHM Mn-Kα: 136 ev Input count rate: kcps Dead Time: % kev kev Salge et al. (2013a) 24
25 Salge et al. (2013a) Monazite La-Monazite Nd-Monazite
26 Salge et al. (2013a) Monazite La-Monazite Nd-Monazite Nd (wt.%) Class Count Monazite Nd>8 mass% 123 Monazite La>18 mass% 551 Monazite 669 Baryte 32 Hollandite 22 Plumbopyrochlore 15 Bariopyrochlore 20 Zirconolite 2 Unclassified 43 All 1477 Nd , ,1 9.9,9 8.78,7 7.47,4 6.26,2 4.94,9 3.73,7 2.52,5 1.21,2 0.0 La versus Nd La versus Nd La versus Nd 0,0 0, ,3 4, , ,0 11,3 La La (wt.%) 13,5 15,8 18,0 20,3 22,
27 Salge et al. (2013a) h Monazite La-Monazite Nd-Monazite
28 Salge et al. (2013a) h Monazite La-Monazite Nd-Monazite
29 Iron oxides Fast quantification using a reference Hematite Fe 2 O 3 and Magnetite Fe 3 O 4 Standard-based quantification is required to obtain highest accuracy. Hematite was used for reference. HV: Current: Time reference/sample: 15 kv na 120/30 ms SDD: 4 x 10 mm 2 Max. throughput: 4 x 275 kcps FWHM Mn-Kα: 152 ev Haematite Fe 2 O 3 Expected Mean s N=10 (at.-%) (at.-%) (±at.-%) O Fe Magnetite Fe 3 O 4 N=10 Expected Mean s (at.-%) (at.-%) (±at.-%) O Fe Input count rate: 925 kcps Dead Time: ~30 % Salge et al. (2013a) Ritchie et al. (2012) 29
30 Classification of iron oxides Feature using hybride quantification One analyzed field of iron ore pellet Magnetite Hematite Ti-Hematite Ti-Magnetite HV: 15 kv Max. throughput: 4 x 130 kcps Input count rate: 470 kcps Time: 500 ms FWHM Mn-Kα: 130 ev Dead Time: ~30 % Salge et al. (2013a) 30
31 Quantification with hybrid method Standardless with reference for Fe and O Class Count Area fraction (%) Ti-Magnetite Magnetite Ti-Hematite Hematite Quartz Olivine Na-feldspar Alumosilicate Calcium pyroxene Apatite Calcium carbonate Unclassified All Salge et al. (2013a) Magnetite / Hematite =
32 Arsenides, tellurides, sulfides Multiple BSE thresholds Size 1.3 x 0.9 cm Fields 90 Time 292 min Count 6351 Measurement conditions Pixel size: µm HV: 25 kv Input count rate: kcps Acquisition time: s chalcopyrite cobalt nickel arsenide iron sulfide pentlandite 3 mm Salge et al. (2013b)
33 Arsenides, Tellurides Bright BSE threshold Size 3.3 x 1.8 cm Fields 875 Time 120 min Count 105 Measurement conditions Pixel size: µm HV: 25 kv Input count rate: kcps Acquisition time: s 5 mm Salge et al. (2013b) 33
34 Spectrum Imaging HyperMap 34
35 Low voltage analysis (7 kv) Sulfides, Arsenides and Tellurides cps/ev Te O Fe Co Ni Cu As kev XFlash 6 10, 7 kv, 22 na, ~97 kcps, 20 min, 640x360 pixels, 45 nm pixel size Online peak deconvolution in the low energy range using an enhanced atomic library Salge et al. (2013b) 35
36 Low voltage analysis (7 kv) Sulfides, Arsenides and Tellurides cps/ev Te O Fe Co Ni Cu As kev XFlash 6 10, 7 kv, 22 na, ~97 kcps, 20 min, 640x360 pixels, 45 nm pixel size Online peak deconvolution in the low energy range using an enhanced atomic library Salge et al. (2013b) 36
37 Low voltage analysis (7 kv) Sulfides, Arsenides and Tellurides Salge et al. (2013b) 37
38 Low voltage analysis (7 kv) Sulfides, Arsenides and Tellurides Salge et al. (2013b) 38
39 Low voltage analysis (7 kv) Sulfides, Arsenides and Tellurides Salge et al. (2013b) 39
40 Low voltage analysis (7 kv) Sulfides, Arsenides and Tellurides Salge et al. (2013b) 40
41 Low voltage analysis (7 kv) Sulfides, Arsenides and Tellurides Pn altered Pn Cob>Gers Gers~Cob Gers>Cob Sper Als1 Als2 K-Fsp Na-Fsp Chemical phase map detects similarly composed areas with the help of mathematical methods Salge et al. (2013b) 41
42 Summary Automated feature and Spectrum Imaging Improvements in detector and pulse processor technology, software developments and reference database extension enhance EDS analysis Automated feature analysis and advanced analysis options by hyperspectral imaging provide new insights for applied and process mineralogy as well for academic research These are based mostly on the truly quantitative character of the results and the possibility to collect high-quality data in seconds without losing spatial resolution Analyzing only features of interests by selecting grey scale thresholds in the BSE micrograph significantly reduces measurement and evaluation time These analysis options will stimulate new approaches for investigations of nano particles (Rades et al. 2014), atmospheric particulates and applications in other fields 42
43 References N. W.M. Ritchie, D. E. Newbury, J. M. Davis (2012) EDS Measurements of X-Ray Intensity at WDS Precision and Accuracy Using a Silicon Drift Detector, Microscopy and Microanalysis, 18, T. Salge, (2012) EDS Analysis with Silicon Drift Detectors at High Spatial Resolution - Advances in Low Energy X-ray Analysis, G.I.T. Imaging & Microscopy, T. Salge, R. Neumann, C. Andersson, M. Patzschke (2013a) Advanced mineral classification using feature analysis and spectrum imaging with EDS, Proceedings of the 23rd International Mining Congress and Exhibition of Turkey, UCTEA Chamber of Mining Engineers of Turkey, T. Salge, M. Patzschke, B. Hansen, L. Hecht (2013b) Classification of Sulfides, Arsenides and Tellurides from the Sudbury Igneous Complex (SIC) using Feature Analysis and Spectrum Imaging with Advanced EDS. Large Meteorite Impacts and Planetary Evolution V (LMI V) USRA, Sudbury, Canada. S. Rades, T. Salge, R. Schmidt and Vasile-Dan Hodoroaba (2014) Need for Large- Area EDS Detectors for Imaging Nanoparticles in a SEM Operating in Transmission Mode, submitted to Microscopy & Microanalysis 2014.
44 Museum für Naturkunde Berlin T. Mohr-Westheide 1, J. Fritz 1, W.U. Reimold 1,2, R. Tagle 3, T. Salge 3 1 Museum für Naturkunde Berlin (Evolution und Geoprozesse) 2 Humboldt University of Berlin 3 Bruker Nano GmbH, Berlin Invalidenstraße Berlin tanja.mohr-westheide@mfn-berlin.de
45 Why are impact studies important? Fundamental process for planetary evolution Surface geological process Energy transfer for the early Earth Evolution of life Danger to life on Earth Economic importance of impact structures - 2 -
46 Purpose of ICDP Drilling at Barberton, South Africa Collisions and impact processes have been important throughout the history of the solar system. The Barberton Greenstone Belt in South Africa is one of the best-preserved successions of mid-archean ( Ga) supracrustal rocks in the world. Identifying traces of mega-impacts in Earth s ancient history. Investigation of spherule layers (including impact debris) provides information about the nature and magnitude of meteorite impacts on the early Earth
47 Location of spherule layer and impact structures Sudbury Vredefort Sudbury Vredefort ~ km 1850 Ma ~ km 2020 Ma (W.U. Reimold & C. Koeberl (2014), J. Afr. Earth Sci.) - 4 -
48 Location of spherule layer and impact structures Ga Ga 1.85 Ga Sudbury Ga Ga Vredefort Sudbury Vredefort ~ km 1850 Ma ~ km 2020 Ma (W.U. Reimold & C. Koeberl (2014), J. Afr. Earth Sci.) - 5 -
49 Location of spherule layer and impact structures Ga (W.U. Reimold & C. Koeberl (2014), J. Afr. Earth Sci.) - 6 -
50 What are spherule layers? Sand-sized, mostly spherical particles, which are thought to have formed by the condensation within impact vapor plumes generated by large impact events. or they can be interpreted as ejecta that were molten during atmospheric re-entry. Spherule layer BARB 5 ( m) 2 cm - 7 -
51 Evidence for impact origin presence of shocked minerals (1 grain in Australia) elevated Ir contents Cr isotope anomalies 1 cm BARB 5 ( m) - 8 -
52 Problematics of genetics Primary vs. secondary signatures: primary characteristics related to the impact event and secondary characteristics due to (re)deposition, diagenesis, tectonic overprint, and metamorphism Primary signatures preserved in the spherule layers may provide insights regarding the impact event(s), plume processes, and the projectiles involved. Locally extremely too high Ir - up to four times the Ir concentrations in chondrites. Why? What are the carrier phases? undeformed spherules sheared spherules How many SL are there really? For example in core CT 3 (Northern BGB) 17 intersections have been observed. 1 cm - 9 -
53 Drill core BARB5 BOX m m m m
54 Drill core BARB5 BOX m m m m
55 BARB5_ Lithology m Spherules occur densely packed in four layers each about 4 cm thick Spherules on top of layer 1 are extensively deformed (sheared) in contrast to the generally un- or at least barely deformed spherules in layers m
56 BARB5_ Lithology m Spherules occur densely packed in four layers each about 4 cm thick Spherules on top of layer 1 are extensively deformed (sheared) in contrast to the generally un- or at least barely deformed spherules in layers m
57 BARB5_ Lithology m Spherules occur densely packed in four layers each about 4 cm thick Spherules on top of layer 1 are extensively deformed (sheared) in contrast to the generally un- or at least barely deformed spherules in layers m
58 BARB5_ Lithology m Spherules occur densely packed in four layers each about 4 cm thick Spherules on top of layer 1 are extensively deformed (sheared) in contrast to the generally un- or at least barely deformed spherules in layers m
59 BARB5_ Lithology m Spherules occur densely packed in four layers each about 4 cm thick Spherules on top of layer 1 are extensively deformed (sheared) in contrast to the generally un- or at least barely deformed spherules in layers 2-4. The original mineralogical and chemical compositions of the spherules have been almost completely changed by alteration Spherule beds are comprehensively altered to assemblages of quartz, chlorite, other phyllosilicates, K-feldspar, Mg-siderite, barite, and calcite. Sulfide mineralization increasing from layer 1 to layer 4 both within spherules and ground mass m
60 Bruker M4 TORNADO µ-xrf results 50 kv, 50 µm steps, 50 ms dwell time, 128 min Cr Ni Fe 2cm m m
61 Bruker M4 TORNADO µ-xrf results 50 kv, 50 µm steps, 50 ms dwell time, 128 min High Fe content in shale bed Cr Ni Fe 2cm m m
62 Bruker M4 TORNADO µ-xrf results 50 kv, 50 µm steps, 50 ms dwell time, 128 min Cr highly enriched on top of layer 1 Cr Ni Fe 2cm m m
63 Bruker M4 TORNADO µ-xrf results 50 kv, 50 µm steps, 50 ms dwell time, 128 min Highest Ni concentration Cr Ni Fe 2cm m m
64 Bruker M4 Tornado µ-xrf results 50 kv, 50 µm steps, 50 ms dwell time, 128 min Highest Ni concentration Cr Ni Fe 2cm m m
65 Bruker M4 TORNADO µ-xrf results 50 kv, 50 µm steps, 50 ms dwell time, 128 min The lowest Cr and Ni content in bottom layer 1 Cr Ni Fe 2cm m m
66 Bruker M4 Tornado µ-xrf results 50 kv, 50 µm steps, 50 ms dwell time, 128 min High Cr and Ni contents in spherule layer 2-4 Cr Ni Fe 2cm m m
67 Bruker M4 TORNADO µ-xrf results 50 kv, 50 µm steps, 50 ms dwell time, 128 min No spinel! Occurrence of Ni-Cr Spinel Cr Ni Fe 2cm m m
68 BARB5 nickel-rich chromium-spinel Ni-Cr-spinel within a spherule Groundmass hosted Ni-Cr-spinel Spherule Spherule 100 μm 100 μm
69 Trace element analyses by INAA Mohr-Westheide et al. (submitted to IMA 2014), data courtesy of Koeberl, Mader, Schulz, NHM Vienna, University of Vienna) Top Cr m cm m
70 Trace element analyses by INAA Mohr-Westheide et al. (submitted to IMA 2014), data courtesy of Koeberl, Mader, Schulz, NHM Vienna, University of Vienna) Top Cr m cm m
71 Observations and Questions INA analyses documented distinctly elevated Ir concentrations. Highest amounts of Ir found in spherule layer 3, with overall good correlation of chromium. Are Ni-Cr spinels associated with PGE phases? Is Ni-Cr spinel a carrier of the extraterrestrial signature?
72 BSE mosaic (100nm pixel resolution, 6103x4065 pixels)
73 BSE mosaic (100nm pixel resolution, 6103x4065 pixels)
74 Low voltage EDS analysis (6 kv) Enhancement of spatial resolution for element analysis Low energy spectrum region of analyzed PGE phases showing significant peak overlaps Depths distribution of emitted X-rays for PtAsS at 6 kv
75 Low voltage EDS analysis Enhancement of spatial resolution for element analysis Deconvolution result of grain P46 cps/ev Background free C O S Fe Co Ni As Ru Rh Os Pt Ir Sum 3 Os Ir Pt S Ru Rh kev Extended atomic databases improve the identification and quantification of low energy X-ray lines
76 Measurement Conditions for Automated Feature Analysis using FE-SEM with XFlash 6 10 SDD Analysis Chromite PGE BSE threshold Intermediate to bright bright Pixel resolution ~2 µm ~100 nm Accepted particles 6 µm radius 250 nm radius Scan Full particle (2 µm scan guard band) Particle center HV 20 kv 6 kv Maximum pulse throughput 130 kcps 60 kcps FWHM Mn-Kα 125 ev at 300 kcps 123 ev at 150 kcps Input count rate/ Dead time ~90 kcps/ 24 % ~70 kcps/ 35 % Spectrum acquisition time 0.5 s 3 s Fields 288 (400x266 pixels) 170 (3600x2397 pixels) BSE acquisition time per field 0.9 s (8 µs dwell time) 17 s (2 µs dwell time) Analysed area 495,613 µm 2 89,746 µm 2 Count Total time 60 min 90 min
77 Chromite Results Classified Minerals
78 Chromite Results Average Diameter (µm, exclusion of border particles) 17 Average Diameter Average Diameter
79 Chromite Results Distribution of Chromite Clusters Cr-Ni spinels are present in the complete analyzed area Upper area was chosen for analysis of PGE-phases
80 PGE Results Classified Minerals
81 PGE Results Average Diameter (µm) of all analyzed grains 17 PGE sulpharsenides with an average diameter of µm were detected
82 PGE bearing sulpharsenides phases associated with Ni-chromite Ni-chromite Layer Y X Y (µm) cm Ni-Chromite X (µm)
83 PGE bearing sulpharsenides phases associated with Ni-chromite PGE-arsenide vs. Ni-chromite Layer Y X Y (µm) cm X (µm) Ni-Chromite PGE-arsenide Pd
84 PGE bearing sulpharsenides phases associated with Ni-chromite PGE-arsenide vs. Ni-chromite Layer Y X Y (µm) cm X (µm) Ni-Chromite PGE-arsenide Pd
85 Net intensity maps of zoned PGE-sulparsenide 2x2 spectrum binning => 30 nm pixel resolution Composite map with line scan Map table of selected elements XFlash, 6ǀ10, 6 kv, 52 min, 8 kcps
86 Summary The presence of four closely spaced but well separated spherule beds is suggestive of aquatic deposition after a single impact event, with multiphase currents affecting sedimentation. Strong hydrothermal overprint is indicated for all lithologies in the studied section. Primary characteristics include spherule size and shapes, and presence of Ni-rich chromite (projectile related), which is absent in layer 1. Sulfide mineralization, (incl. pyrite, gersdorffite) is of secondary origin and related to chemical alteration and metamorphism. High Zn concentrations along cataclased spinel grains relate to late overprint
87 Summary High abundances of the siderophile elements (Ni, Co, Ir, Os, Cr, and Au) reflect extraterrestrial components. Abundances are on the same level, or even strongly exceeding, the contents of these elements in chondritic meteorites. Our microchemical analytical efforts are directed at identifying the loci and carrier phases of the ETC. LA-ICPMS has revealed that PGE are also present in chromium-rich areas of the matrix (I. McDonald, submitted to IMA 2014). High resolution SEM-EDS studies (feature analysis) identified Ni-chromite clusters as neighbourhoods of PGE enrichments. PGE-sulpharsenides (Ø = μm) can be classified in a short time by automated feature analysis using an accelerating voltage of 6 kv at 100 nm BSE pixel resolution
88 Papers submitted to 21 st General Meeting of the International Mineralogical Association, Gauteng, South Africa ICDP Drill Core BARB5: First Petrographic Results of the Archean Impact Spherule Layer Consortium. Mohr-Westheide, T., Fritz, J., Reimold, W.U., Schmitt, R.T., Hofmann, A., Koeberl, C., McDonald, I., Luais, B., Tagle, R., Salge, T., Schulz, T., Mader, D., and Hoehnel, D. Archean Spherule Layers in the Barberton Mountain Land: A Consortium Study on Earth s Early Impact Record. Fritz, J., Mohr-Westheide, T., Reimold, W.U., Schmitt, R.T., Hofmann, A., Koeberl, C., McDonald, I., Luais, B., Tagle, R., Schulz, T., Mader, D., and Hoehnel, D. Mapping the distribution of projectile material in Archaean impact spherule layers using LA-ICP-MS. McDonald I., Simonson B.M., Fritz J., Mohr-Westheide T., Reimold W.U. and Koeberl C. Advanced EDS and µxrf Analysis of Earth and Planetary Materials using Spectrum Imaging, Computer-Controlled SEM and an Annular SDD. Salge, T., Tagle, R., Hecht, L., Mohr-Westheide, T., Reimold, W.U., Ferrière, L., Ball, A.D., Kearsley, A.T., Smith, Jones, C.G., Patzschke, M
89 Thank you for your attention
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