Transcript AEM Analysis of Nanoparticles

Compositional
Mapping
Charles Lyman
Lehigh University,
Bethlehem, PA
Based on presentations developed for Lehigh University
semester courses and for the Lehigh Microscopy School
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X-ray Mapping is 50 Years Old
First x-ray dot map
»
Duncumb and Cosslett (1956)
3-D tomographic map
»
Kotula et al. (2006)
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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
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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
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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”
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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
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X-ray Dot Maps
Early X-ray Dot Maps

Advantages
»
»

Any x-ray detector
Rapid scanning provides survey
Disadvantages
»
»
»
»
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WDS dot maps
of Fe Ka in bulk
specimen
Dim recording dot
(100 sec frame)
Record CRT brightness is a variable
Single channel, single photograph
One element at a time
Time consuming
Qualitative only
Optimum recording dot
(100 sec frame)
SE image of flat-polished basalt
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Optimum recording dot
(300 sec frame)
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Digital X-ray Maps
Modern X-ray Maps

Advantages
»
»
»
»
»
»

EDS x-ray map of bulk specimen
Fe
Background
Si
Ca
K
Al
Up to 16 selected elements
Stored in computer
Photograph later
Dwell time per pixel
Background subtraction and
quantitation possible
Quantitative maps possible
Disadvantages
»
None
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
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Maximizing the Collected X-ray Counts

Maximize counts
»
Set pulse processor to a short
processing time t for high count
rate:
–
–
»
»
»

Use 50-60% dead time
More counts for same collection
(clock) time
Thin specimens rarely produce
high count rates
Silicon drift detector (EDS)
»

2,000 cps at 135 eV (long t)
10,000 cps at 160 eV (short t)
> 500,000 cps
Elemental detection
»
Collect > 8 counts/pixel to assure
element is present above
background
Low Fe
counts
0
Low
count
rate
High Fe
counts
1
5
Midcount
rate
11
8
High
count
rate
59
Bulk specimen of basalt
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WDS maps vs. EDS maps
Fe
Fe
Fe
Low Fe
phase
missed
WDS map (300 sec)
EDS map (900 sec)
Better peak-to-background
but WDS not currently used
for thin specimens
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X-ray Map Artifacts

Continuum image artifact
»
»
Fe map
Background map
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
Coat with 10 nm of Cr
Friel and Lyman, Microsc. Microanal. 12 (2006) 2-25
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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
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Maximum Map Magnification
W-gun STEM
FEG STEM
For ~1 nA probe current
Friel and Lyman, Microsc. Microanal. 12 (2006) 2-25
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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
•


M ≈ 400,000x
Over-sampling
•
•

L
RN
Most of
pixel not
sampled
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
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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
50 nm
S. Choi, M.S. Thesis, Lehigh University (2001)
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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
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Uses of Compositional Images

Location of elements and phases
» Where are individual elements?
» How does element concentration change (qualitatively)?
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Elemental associations
» How are elements combined?
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Particle and precipitate sizing
» classification by chemistry and size
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Quantitative analysis using stored maps
» combine pixels within a phase
» each pixel may have 10-100 counts
» significant counts when add > 500 pixels together
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STEM-EDS Elemental Maps from Au-Ag Nanoparticles
STEM-ADF image
Ag map (Ag La)
Au map (Au La)
20nm
Courtesy of M. Watanabe
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Profiles from Elemental Maps
STEM-ADF image
20nm
Courtesy of M. Watanabe
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STEM-XEDS Analysis of Au-Pd/TiO2 Particles for Peroxide Synthesis
ADF Image
Au Map
Pd Map
Ti Map
RGB Image
40 nm
40 nm
O Map
Red = Ti
Green = Pd
Blue = Au
Courtesy C. Kiely, published in Enache et al., Science 311 (2006) 362-365
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Color in X-ray Maps

Thermal color scale (look up table)
»
Red-orange-yellow-white
» Indicates intensity in quantitative maps
From Goldstein et al., Scanning Electron Microcopy
and X-ray Microanalysis, Springer, 2003

Primary color images
» red=Si; green=Al; blue=Mg
» yellow = red+green
(yellow shows location of Si+Al)
From Newbury et al., Advanced Scanning Electron
Microcopy and X-ray Microanalysis, Plenum, 1986
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High Resolution Quantitative Maps of Thin Specimens
Ni

Thin metal alloy with
precipitates

Quantitative map using
z-factor analysis
»
Al
Mo
Developed by M. Watanabe
Specimen: Ni base alloy
Williams et al., High Resolution X-ray Mapping in the
STEM, J. Electron Microsc 51 (suppl.) 2002, S113-S126
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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
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Spectrum Imaging: A Spectrum at Every Pixel

Collect a spectrum at each pixel
»

y
Collect ‘x-y-energy’ data cube
»
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Best way to analyze unknowns
256x196 pixels x1024 channels x32bit spectra
(for spectrum image of granite)
x
Use good EDS mapping practice
»
»
»
»
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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
Specimen: polished granite
Courtesy of D. Rohde
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Spectrum Image of Granite
Na, Ca, and Ti might not
show up in global spectrum
Specimen: polished granite
Courtesy of David Rohde
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Compositional Mapping in EELS


Sequential EELS mapping in STEM
EELS energy filters
From Williams and Carter, Transmission Electron Microscopy, Springer, 1996
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EELS Spectrum Image
Top row: elements known to be present in beryllium-copper
200 nm
Cu
Co
Be
O
Ti
V
Cr
Fe
Bottom row: elements not known to be present
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Hunt and Williams, Ultramicroscopy 38 (1991) 47-73
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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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