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Compositional Mapping

Compositional Mapping. Charles Lyman Lehigh University, Bethlehem, PA. Based on presentations developed for Lehigh University semester courses and for the Lehigh Microscopy School. X-ray Mapping is 50 Years Old. First x-ray dot map Duncumb and Cosslett (1956) 3-D tomographic map

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Compositional Mapping

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  1. Compositional Mapping Charles Lyman Lehigh University, Bethlehem, PA Based on presentations developed for Lehigh University semester courses and for the Lehigh Microscopy School

  2. X-ray Mapping is 50 Years Old First x-ray dot map • Duncumb and Cosslett (1956) 3-D tomographic map • Kotula et al. (2006)

  3. Types of Compositional Images in TEM/STEM • Dark-field images • Phase-specific DF images (any TEM) • Centered dark-field (tilted beam) • Displaced aperture dark-field • High-angle annular dark-field (HAADF) STEM images • X-ray elemental images (x-ray maps) • Specimen thickness: 10 nm to 500 nm • Need counts, counts, counts • Make large: probe current, thickness, counting rate, time • Auger elemental images • Images of elements on the surfaces • Special UHV instrument required • EELS elemental images • Specimen thickness: < 30 nm

  4. X-ray Mapping Compared with Other Mapping Methods Mapping detection limits assumed to be about 0.1 x point detection limit Friel and Lyman, Microsc. Microanal. 12 (2006) 2-25

  5. X-ray Mapping Important Questions • Where are specific elements located? • What elements are associated with each other? • Have I missed any elements? Types of X-ray Mapping • Qualitative • Which elements are present? • Quantitative • How much of each element is present? • Spectrum imaging • Entire spectrum is collected at each pixel • In the future: “Every image an analysis, every analysis an image”

  6. X-ray Map Acquisition • Dot Maps (since 1956) • density of x-ray dots photographed as beam scans (1 scan per element) • no intensity information • Digital Images (starting about 1980) • gray levels give intensity • many element maps collected in 1 scan • can be made quantitative • Spectrum Images (since 1989) • store a spectrum at each pixel • no pre-set elements • “mine the data” off-line Friel and Lyman, Microsc. Microanal. 12 (2006) 2-25

  7. X-ray Dot Maps WDS dot maps of Fe Ka in bulk specimen Early X-ray Dot Maps • Advantages • Any x-ray detector • Rapid scanning provides survey • Disadvantages • Record CRT brightness is a variable • Single channel, single photograph • One element at a time • Time consuming • Qualitative only Dim recordingdot (100 sec frame) Optimum recording dot (100 sec frame) Optimum recording dot (300 sec frame) SE image of flat-polished basalt

  8. Digital X-ray Maps EDS x-ray map of bulk specimen Fe Si Modern X-ray Maps • Advantages • Up to 16 selected elements • Stored in computer • Photograph later • Dwell time per pixel • Background subtraction and quantitation possible • Quantitative maps possible • Disadvantages • None Background K Ca Al Collection parameters: 128x128 pixels 55 ms dwell time per pixel 20% dead time Total frame time = 15 min (900 sec) SE image of flat-polished basalt

  9. Maximizing the Collected X-ray Counts Low Fe counts 0 Low count rate High Fe counts • Maximize counts • Set pulse processor to a short processing time t for high count rate: • 2,000 cps at 135 eV (long t) • 10,000 cps at 160 eV (short t) • Use 50-60% dead time • More counts for same collection (clock) time • Thin specimens rarely produce high count rates • Silicon drift detector (EDS) • > 500,000 cps • Elemental detection • Collect > 8 counts/pixel to assure element is present above background 1 5 Mid- count rate 11 8 High count rate 59 Bulk specimen of basalt

  10. Fe Fe Fe WDS maps vs. EDS maps Low Fe phase missed WDS map (300 sec) EDS map (900 sec) Better peak-to-background but WDS not currently used for thin specimens

  11. Coat with 10 nm of Cr X-ray Map Artifacts Fe map Background map • Continuum image artifact • Collect a map for every element known in specimen • Map a non-existant element • null-element or continuum background map • Mobile species • Certain elements (e.g. Na, S) move under the beam • Lock element in place with 10 nm of sputtered Cr Friel and Lyman, Microsc. Microanal. 12 (2006) 2-25

  12. Small Thin-Specimen Excitation Volume • Most serious problem for thin specimen map • Too few counts per pixel • Drift of specimen during long map 1 nA in 20-50 nm 1 nA in 1-2 nm From Williams and Carter, Transmission Electron Microscopy, Springer, 1996

  13. Maximum Map Magnification W-gun STEM FEG STEM For ~1 nA probe current Friel and Lyman, Microsc. Microanal. 12 (2006) 2-25

  14. Oversampling & Undersampling • Field-emission STEM • Beam size ~ 2 nm (~ 1nA) • R = x-ray spatial resolution including beam size and beam spreading • Let R = 2 nm = 1 pixel N = 128 pixels in a line L = 10 cm screen width • M ≈ 400,000x • Over-sampling • M > 400,000x • M to 1,000,000x is OK • Under-sampling • M < 400,000x • M << 400,000x (survey) • Do not use this M to obtain a quality map Most of pixel not sampled

  15. 50 nm Field-Emission STEM X-ray Maps Map setup: probe size 2nm, probe current 0.5 nA, 128x128, 100 ms/pixel Original magnification = 500,000x Pt-Rh catalyst sulfided with SO2 ADF Image Pt map S map Background map S. Choi, M.S. Thesis, Lehigh University (2001)

  16. W-Gun Thin Specimen X-ray Maps • Map setup • 128x128 pixels • 2.6 sec/pixel • 12 hours • Original M ~ 10,000x Freeze-dried section of rat parotid gland Images from Wong et al. quoted in Friel and Lyman, Microsc. Microanal. 12 (2006) 2-25

  17. Uses of Compositional Images • Location of elements and phases • Where are individual elements? • How does element concentration change (qualitatively)? • Elemental associations • How are elements combined? • Particle and precipitate sizing • classification by chemistry and size • Quantitative analysis using stored maps • combine pixels within a phase • each pixel may have 10-100 counts • significant counts when add > 500 pixels together

  18. STEM-EDS Elemental Maps from Au-Ag Nanoparticles Ag map (Ag La) Au map (Au La) STEM-ADF image 20nm Courtesy of M. Watanabe

  19. Profiles from Elemental Maps STEM-ADF image 20nm Courtesy of M. Watanabe

  20. STEM-XEDS Analysis of Au-Pd/TiO2 Particles for Peroxide Synthesis ADF Image Au Map Pd Map 40 nm 40 nm O Map Ti Map RGB Image Red = Ti Green = Pd Blue = Au Courtesy C. Kiely, published in Enache et al., Science 311 (2006) 362-365

  21. Color in X-ray Maps • Thermal color scale (look up table) • Red-orange-yellow-white • Indicates intensity in quantitative maps • Primary color images • red=Si; green=Al; blue=Mg • yellow = red+green (yellow shows location of Si+Al) From Goldstein et al., Scanning Electron Microcopy and X-ray Microanalysis, Springer, 2003 From Newbury et al., Advanced Scanning Electron Microcopy and X-ray Microanalysis, Plenum, 1986

  22. High Resolution Quantitative Maps of Thin Specimens Ni • Thin metal alloy with precipitates • Quantitative map using z-factor analysis • Developed by M. Watanabe Al Mo Specimen: Ni base alloy Williams et al., High Resolution X-ray Mapping in the STEM, J. Electron Microsc 51 (suppl.) 2002, S113-S126

  23. Recent Ways to Find Element Associations • Spectrum-Imaging • Available from most EDS companies • Available for EELS • Multivariate Statistical Analysis • Next lecture • LISPIX • Powerful image processing program by D. Bright (NIST) • Color overlays, scatter diagrams, mining spectrum-image data cubes • On the Lehigh CD

  24. Spectrum Imaging: A Spectrum at Every Pixel • Collect a spectrum at each pixel • Best way to analyze unknowns • Collect ‘x-y-energy’ data cube • 256x196 pixels x1024 channels x32bit spectra (for spectrum image of granite) • Use good EDS mapping practice • Specimen: bulk, flat polished • Vo = 15 kV • Ip = 2.9 nA • M = 600x • Dwell time = 0.13 µs per pixel • Data rate = 10,000 cts/sec • DT = 40% dead time • Acquisition time = 10 minutes y energy x Specimen: polished granite Courtesy of D. Rohde

  25. Spectrum Image of Granite Na, Ca, and Ti might not show up in global spectrum Specimen: polished granite Courtesy of David Rohde

  26. Compositional Mapping in EELS • Sequential EELS mapping in STEM • EELS energy filters From Williams and Carter, Transmission Electron Microscopy, Springer, 1996

  27. 200 nm EELS Spectrum Image Top row: elements known to be present in beryllium-copper O Be Cu Co Ti V Cr Fe Bottom row: elements not known to be present Hunt and Williams, Ultramicroscopy 38 (1991) 47-73

  28. Summary • X-ray Mapping • Thickness not critical • Match pixel size to x-ray excitation volume • Collect as many counts as possible • Always map for an element that is not present (background map) • EELS Mapping • Higher spatial resolution than x-ray mapping (since beam spreading is not an issue) • Specimen must be very thin

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