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Update on Energy Dispersive X-ray Spectrometrywith the Silicon Drift Detector (SDD) and
Microstructural Characterization with NIST Lispix
D.E. Newbury*, D.S. Bright*, J.H. Scott*,N. Ritchie*, J.R. Michael**, and P.G. Kotula**
*National Institute of Standards and Technology, Gaithersburg, MD 20899-8370**Sandia National Laboratory, Albuquerque, NM 87185-0886
Certain commercial equipment, instruments, or materials are identified in this talk to foster understanding. Such identification does not imply recommendation or endorsement by the National Institute of Standards and Technology, nor does it imply that the materials or equipment identified are necessarily the best available for the purpose.
Advanced Instrumental Techniques and Software Algorithms in EPMA Workshop
X-ray Mapping in the Spectrum Image Modeat Output Count Rates above 100 kHz with
the Silicon Drift Detector (SDD)
Dale E. NewburySurface and Microanalysis Science Division
National Institute of Standards andTechnology
Gaithersburg, MD 20899-8370
50 years of x-ray mapping: a tribute to Peter Duncumb
At the 2006 M&M Conference in Chicago, I gave the following paper:
SDD
Si(Li)
The need for speed!
The new EDS: Silicon Drift Detector (SDD)
This paper examined the performance of the SDD forvarious parameters but especially for high speed X-ray Spectrum Imaging (XSI).
SDD
Si(Li)
The need for speed!
The new EDS: Silicon Drift Detector (SDD)
This paper examined the performance of the SDD forvarious parameters but especially for high speed X-ray Spectrum Imaging (XSI).
But as I gave the paper, Iwas already aware (thanks toJuly ‘06 communication fromJoe Michael at Sandia) that myresults were stale: 100 kHz OCRwas already way behind the limiting performance envelopefor SDD technology.
What had happened?
ElectronsHoles
X-rays
Au electrode, ~20 nm
Window: Be, BN, C (diamond), or polymer 0.1 - 7 μm
Active silicon (intrinsic), 3 mm
- 1000 V
Inactive silicon (n-type), ~100nm
Rear Au electrode, ~20 nm
Si 'dead' layer (p-type), ~100 nm
Al reflective coating, 20 - 50 nm
Ice
The Si(Li) Energy Dispersive X-ray SpectrometerFitzgerald, R, Keil, K. and Heinrich, K. Science v 159 (1968) 528“Solid-State Energy-Dispersion Spectrometer for Electron-Microprobe X-ray Analysis”
EDS MappingAdvantages:1. Detects entire x-ray spectrum enabling mapping of allelements simultaneously2. The unexpected can bediscovered!3. No defocusingDisadvantages1. Poor resolution: interferences2. Lower P/B; more susceptibleto continuum effects; poorer limits of detection3. OCR: 2 kHz to 20 kHz
Al Fe Ni
50 μm
X-ray detection
Photon Energy (keV)
Inte
nsity
Tiesc
TiKα +TiKα
1.74 keV Coincidence peak
EDS Artifacts: Si escape peak and coincidence peak
Only for majorelements at highcount rate
Escape peakalways formsat same fraction
Spectrum appears to be continuously measured at all energies,but it is actually one photon at a time: deadtime
SiK-edge
Drastic decreasein detector efficiency
0
500
1000
1500
2000
0 2000 4000 6000 8000 10000 12000
Conventional EDS (time constant 50 microseconds)O
utpu
t Cou
nt R
ate
(cou
nts/
seco
nd)
Input Count Rate (counts/second)
Current State-of-the Art Si(Li)-EDS (30 mm2)
Resolution = 134 eV (MnKα)
Target: Mn E0 = 20keV
OC
R
ICR
“Best resolution”Max OCR ~ 1.9 kHz
“Paralyzable deadtime”
0
10000
20000
30000
40000
50000
60000
70000
100
120
140
160
180
200
220
0 20 40 60 80 100
Manganese (Beam energy 20 keV)
OCR at 40%DT
FWHM (MnKa)
Out
put C
ount
Rat
e at
40%
dea
dtim
eR
esolution (FWH
M at M
nKα)
Time Constant (microseconds)
Current digital signal processing with conventional Si-EDS enables count rates > 30 kHz (40% DT) with FWHM of ~180 eV (MnKα)
Si-EDS (30 mm2)
0
5000
10000
15000
20000
25000
0 20000 40000 60000 80000 100000 120000 140000
Conventional EDS (time constant 4 microseconds)O
utpu
t Cou
nt R
ate
(cou
nts/
seco
nd)
Input Count Rate (counts/second)
Current State-of-the Art Si(Li)-EDS (30 mm2)
Resolution = 178 eV (MnKα)
Target: Mn E0 = 20keV
“Mapping throughput”Max OCR ~ 22.5 kHz
ICR
OC
R
SDD Backsurface
Central anode,80 μm diameter
Resistor bridge
Ring electrodes
300 μm
SDDs are thin!
SDDs have a complexback surface electrodestructure. Appliedpotential creates internal collection channel
Active area 5 mm2 to 100 mm2
X-rays
The anode of an SDDis ~ 0.005 mm2 for a 50 mm2 detector, about1/10,000 the area of EDS
Silicon Drift Detector: Same detection physics as Si(Li)-EDS, but a radically different design X-ray absorption and ejection of
photoelectron; inelastic scatteringcreates electron-hole pairs.
SDD EDS with thermoelectric cooling to ~ -20 to -50 oC
Conventional Si(Li) EDS withLiquid nitrogen cooling to~ -190 oC
100
150
200
250
0
50
100
150
200
250
300
350
0 1 2 3 4 5 6 7 8
Radiant Detectors SDD Performance
FWHM (MnKa)
OCR(40%DT)
y = 173.93 * x^(-0.1418) R= 0.9744
y = 94.748 * x^(-1.0105) R= 0.98328
FWH
M (M
nKa)
Output C
ount Rate (40%
DT)
Time Constant (microseconds)
134 eV
3rd generation Radiant “Vortex” 50 mm2 SDD
0
5000
10000
15000
20000
0 20000 40000 60000 80000 100000
SDD with 8 microsecond time constant
Out
put c
ount
rate
(cou
nts/
seco
nd)
Input count rate (counts/second)
MnKα FWHM = 134 eV50 mm2 8 μs shaping time
Limit of conventional Si(Li) EDSat optimum resolution
0
500
1000
1500
2000
0 2000 4000 6000 8000 10000 12000
Conventional EDS (time constant 50 microseconds)
Out
put C
ount
Rat
e (c
ount
s/se
cond
)
Input Count Rate (counts/second)
Peak OCR = 13.6 kHz
Si(Li)
0 10 0
5 10 4
1 10 5
1.5 10 5
2 10 5
0 10 0 2 10 5 4 10 5 6 10 5 8 10 5 1 10 6 1 10 6
SDD 1 microsecond time constantO
utpu
t cou
nt ra
te (c
ount
s/se
cond
)
Input count rate (counts/second)
MnKα FWHM = 163 eV50 mm2 1 μs shaping time
Peak OCR = 160 kHz
0 10 0
1 10 5
2 10 5
3 10 5
4 10 5
5 10 5
0 10 0 5 10 5 1 10 6 2 10 6 2 10 6
SDD Time constant = 500 nanosecondsO
utpu
t cou
nt ra
te (c
ount
s/se
cond
)
Input Count Rate (counts/second)
MnKα FWHM = 188 eV50 mm2 500 ns shaping time
Peak OCR = 280 kHz
0 10 0
1 10 5
2 10 5
3 10 5
4 10 5
5 10 5
6 10 5
0 10 0 5 10 5 1 10 6 2 10 6 2 10 6 3 10 6 3 10 6 4 10 6
SDD Time constant = 250 nanosecondsO
uput
Cou
nt R
ate
(cou
nts/
seco
nd)
Input Count Rate (counts/second)
MnKα FWHM = 217 eV50 mm2 250ns shaping time
Peak OCR = 510 kHz
10 3
10 4
10 5
10 6
10 3 10 4 10 5 10 6 10 7
Input Count rate (c/s)
Out
put C
ount
rat
e (c
/s)
8 μs
1 μs500 ns
250 ns
Radiant Detectors 50 mm2 VORTEX SDD
Detector solid angle plus processing speed revolutionizes x-ray mapping!
The Real Promise of the SDD: High Speed Spectrum Image Mapping
Radiant SDD/SAMx spectrum imaging software128x128x10ms (1.3 ms overhead) = 185 s total
50 mm2 detector; 500 ns time constant; Res = 188 eV(MnKα)
E0 = 20 keV i = 10nAICR: 320 kHz OCR: 220 kHz ~40%DT
“Three-minute eggx-ray spectrum image”
X-ray spectrum imagingA complete spectrum is recorded at each pixel!
X-ray E
nergy
X
Y
Channel (X-ray Energy)
Cou
nts
Cou
nts
Gorlen et al.,Rev.Sci.Inst. v55(1984) 912.
20μm
Raney Nickel AlloyE0 = 20 keV 10 nATC = 500 ns (188 eV at MnKα)128x128 10 ms per pixel Mapping 185 sec
H
I
Al
Al
Ni
Fe
BSEPhasesAl 99.5 Ni 0.5Al 71.2 Ni 24.6 Fe 4.2 Al 60 Ni 40 “I”Al 46.5 Ni 53.5 “H”
Update on Silicon Drift Detector (SDD) Performance
• Processing speed
Bruker SDD Performance
Detector rise time <100nsOptimum shaping time 700 ns (90 kcps max. throughput)Maximum cooling -25°C (at Iopt=2,5A, ta = 23°C, still air)Thermostat set point -20°C
Values for sum spectrum over all 4 detectors (measured at MnKa)Peak shift (20 ... 800 kcps)<5eVPeak drift (24h) <10eV Peak/Background 2200:1 Energy resolution and processed countrate of 5.899 keV, Mn k
Joe Michael’s news: he had obtained a quad detector with this performance!
Source: Bruker
100x fasterthan Si(Li)!
0
200
400
600
800
1000
1200
1400
0 200 400 600 800 1000 1200 1400
220 ns
400 ns
680 ns
Input Count Rate (kcps)
Out
put C
ount
Rat
e (k
cps)
0
10
20
30
40
50
60
70
80
0 200 400 600 800 1000 1200 1400
220 ns
400 ns
680 ns
Input Count Rate (kcps)%
Dea
d Ti
me
The latest SDD (Bruker 4th generation)
Bruker Quad SDDData: Joe Michael, Sandia National LabAlbuquerque, NM
Bruker: single SDD performance
Four 10 mm2 SDDs with multiplexing givesOCR > 1 MHz with resolution < 140 eV.
127 eV
131 eV
150 eV
0
200
400
600
800
1000
1200
1400
0 200 400 600 800 1000 1200 1400
220 ns
400 ns
680 ns
Input Count Rate (kcps)
Out
put C
ount
Rat
e (k
cps)
0
10
20
30
40
50
60
70
80
0 200 400 600 800 1000 1200 1400
220 ns
400 ns
680 ns
Input Count Rate (kcps)%
Dea
d Ti
me
But wait! The latest SDD (Bruker 4th generation)
Bruker 10 mm2 single SDD (from P-N Sensors)
127 eV
131 eV
145 eV
Si(Li) EDS “best resolution”OCR vs ICR performance disappears on this plot!!(covering only 1% of the0 – 200 unit spacing)
Data: Joe Michael, Sandia National LabAlbuquerque, NM
Four 10 mm2 SDDs with multiplexing givesOCR > 1 MHz with resolution < 140 eV.
.Even thisperiod istoo big!
0
500
1000
1500
2000
0 2000 4000 6000 8000 10000 12000
Conventional EDS (time constant 50 microseconds)
Out
put C
ount
Rat
e (c
ount
s/se
cond
)
Input Count Rate (counts/second)
Si(Li)
Bruker “Tear–drop” Shaped SDDOCR speed: On-chipintegrated chargeamplifier eliminatesmicrophonics; off-centerlocation protects amplifierfrom x-rays
Why is this SDD so much faster?
M&M2005_Optimized Readout Methods of Silicon Drift Detectors for High Resolution Spectroscopy in Micro-Beam AnalysisH.Soltau*, P.Lechner*, A. Niculae*, G. Lutz**, L. Strüder**, C. Fiorini*** and A. Longoni ***R. Eckhard,* G. Schaller,** and F. Schopper**
0 1 2 3 4 5 6 7 8 9
FeK
α
FeK
β NiK
α
NiK
β
CrK
α
CrK
βM
nKα
TiK
α
CaK
α
CaK
β
KK
α
SKα
PKα
SiK
αA
lKα
MgK
αN
aKα
OK
αFe
L
CK
α
NiL
FeS Si
keV
This is a 12 second x-ray spectrum image (128x96 pixels)!
QUAD SDDat 500 kHz OCR
Examining peaks inThe SUM PIXELSpectrum (filled):
50 μm
Update on Silicon Drift Detector (SDD) Performance
• Processing speed• Spectral quality
– Resolution and peak position stability
100
150
200
250
0 10 20 30 40 50
8 microseconds1 microsecond0.5 microsecond0.25 microsecond
y = 133.75 + 0.0030488x R= 0.11043
y = 162.98 + 0.10743x R= 0.97422
y = 187.5 + 0.16057x R= 0.98415
y = 217.48 + 0.38724x R= 0.99124
Res
olut
ion
(FW
HM
)
Deadtime (%)
Slope = 0.003 eV/1%DT
Slope = 0.107 eV/1%DT
Slope = 0.161 eV/1%DT
Slope = 0.387 eV/1%DT
0.25 μs, 217 eV
0. 5 μs, 188 eV
1 μs, 163 eV
8 μs, 134 eV
8 μs1 μs0.5 μs0.25 μs3rd generation
Radiant50 mm2 SDD
Note constancyof peak shape with input count rate!This is vital for spectral studies, includingspectrum imaging.
130
132
134
136
138
140
0 10 20 30 40 50 60
Manganese (Beam energy 20 keV)R
esol
urio
n (F
WH
M M
nKα
)
Deadtime (%)
For a given choice of time constant, the resolutionshould remain constant with deadtime.
Current state-of-the-art Si(Li)-EDS (30 mm2)
3 eV
5.9
5.905
5.91
5.915
5.92
0 50 100 150 200 250 300
8 mus1 mus500 ns250 ns
Peak
Ene
rgy
(keV
)
Input Count Rate (kHz)
Peak Channel Stability3rd generationRadiant50 mm2 SDD
One10-eVchannel
1 eV
1 eV
220 ns
680 ns
400 ns
120
130
140
150
160
0 200 400 600 800 1000 1200 1400
Res
olut
ion
Mn
Kα
(ev)
Input Count Rate (kcps)
-20
-15
-10
-5
0
5
10
15
20
0 200 400 600 800 1000 1200 1400
220 ns
680 ns
400 ns
Input Count Rate (kcps)
Peak
Shi
ft M
n K
α (e
v)
Bruker Quad SDDData: Joe Michael, Sandia National LabAlbuquerque, NM
Stability of Resolution and Peak Position
Bruker “Tear–drop” Shaped SDDOCR speed: On-chipintegrated chargeamplifier eliminatesmicrophonics; off-centerlocation protects amplifierfrom x-rays
Why is this SDD so much faster?
Peak stability: pulse reset operationwith reset diode integrated into the readout anode on the chip.M&M2005_Optimized Readout Methods of Silicon Drift Detectors for High Resolution Spectroscopy in Micro-Beam AnalysisH.Soltau*, P.Lechner*, A. Niculae*, G. Lutz**, L. Strüder**, C. Fiorini*** and A. Longoni ***R. Eckhard,* G. Schaller,** and F. Schopper**M&M2006_Optimization of the Peak-to-Background Ratio and the Low Energy Response of Silicon Drift Detectors for High Resolution X-ray SpectroscopyA. Niculae*, H.Soltau*, P.Lechner*, A.Liebl*, G. Lutz**, L. Strüder**, A. Longoni***R. Eckhard*, G. Schaller** and F. Schopper**
Update on Silicon Drift Detector (SDD) Performance
• Processing speed• Spectral quality
– Resolution and peak position stability– Low photon energy peaks
BC O
Photon Energy (keV)
Inte
nsity
(cou
nts)
0 0.25 0.5 0.75 1.0 1.25 1.50 1.750
9200Mg
Radiant Vortex SDD8 μs TC
Low photon energy performance
CaF2E0 = 5 keV8 μs shaping time
0 0.25 0.5 0.75 1.0 1.25 1.50 1.75 2.0 2.25 2.5
Photon Energy (keV)
Inte
nsity
(cou
nts)
0
15197F K
Radiant Detectors “VORTEX”
Low photon energy performance
CaCO3E0 = 5 keV8 μs shaping time
O K
C K
0 0.25 0.5 0.75 1.0 1.25 1.50 1.75 2.0 2.25 2.5
Photon Energy (keV)
Inte
nsity
(cou
nts)
0
37347
Radiant Detectors “VORTEX”
Low photon energy performance
AlN7 nm carbonE0 = 5 keV8 μs shaping time
0 0.25 0.5 0.75 1.0 1.25 1.50 1.75 2.0 2.25 2.5
Photon Energy (keV)
Inte
nsity
(cou
nts)
0
8601AlK
O K
N K
C K
Radiant Detectors “VORTEX”
Low photon energy performance
CarbonE0 = 5 keV8 μs shaping time
0 0.25 0.5 0.75 1.0 1.25 1.50 1.75 2.0 2.25 2.5
Photon Energy (keV)
Inte
nsity
(cou
nts)
0
12204
SiKabC dbl
C K
Radiant Detectors “VORTEX”
Low photon energy performance
CarbonFill = C (ideal) strippedE0 = 5 keV8 μs shaping time
0 0.25 0.5 0.75 1.0 1.25 1.50 1.75 2.0 2.25 2.5
Photon Energy (keV)
Inte
nsity
(cou
nts)
0
12204
SiKabC dbl
C K
Radiant Detectors “VORTEX”
Low photon energy performance
CarbonE0 = 5 keV8 μs shaping time
??? = B K
0 0.25 0.5 0.75 1.0 1.25 1.50 1.75 2.0 2.25 2.5
Photon Energy (keV)
Inte
nsity
(cou
nts)
0
12204
SiKabC dbl
C K
Radiant Detectors “VORTEX”
Low photon energy performance
0
6916
0 0.25 0.5 0.75 1.0 1.25 1.5
MnLα
Photon Energy (keV)
Inte
nsity
(cou
nts)
MnE0 = 20 keVSDD (131 eV at MnKα)
MnLl
OCR5 kHz10 kHz20 kHz50 kHz100 kHz150 kHz200 kHz250 kHz
Spectral stability in low photon energy range
Update on Silicon Drift Detector (SDD) Performance
• Processing speed• Spectral quality
– Resolution and peak position stability– Low photon energy peaks– Coincidence peaks
TC = 1 μs 45% DT 107,000 cps OCR28% DT 72,500 cps OCR16% DT 42,300 cps OCR8% DT 21,000 cps OCRResolution = 166 eV at MnKα
Al+
NiL
Al+
Al
Ni+
Al
Al
NiL
FeK
α
NiK
α
NiK
β
ClK
α
Photon Energy (keV)
Cou
nts
3rd Generation SDD (Radiant Detectors LLC)
Al+
NiL
Al+
Al
Ni+
Al
Al
NiL
FeK
α
NiK
α
NiK
β
ClK
α
Photon Energy (keV)
Cou
nts
Oxford Analog 48% DT 30,600 cps OCR38% DT 26,200 cps OCR 22% DT 17,200 cps OCR8% DT 9,900 cps OCRResolution = 166 eV at MnKα
Al+
NiL
Al+
Al
Ni+
Al
Al
NiL
FeK
α
NiK
α
NiK
β
ClK
α
Photon Energy (keV)
Cou
nts
EDAX Genesis DSP TC=4 μs48% DT 38,800 cps OCR36% DT 26,100 cps OCR 20% DT 12,900 cps OCR10% DT 6,600 cps OCRResolution = 173 eV at MnKα
SDD can provide the OCR speed
• To exploit this OCR speed for mapping (e.g.,by x-ray spectrum imaging), we need:
• Suitably intense x-ray production, that is, anSEM that can deliver high beam currents (10 –1000 nA) and a specimen that can withstandhigh dose without degradation.
SDD can provide the OCR speed
• To exploit this OCR speed for mapping (e.g.,by x-ray spectrum imaging), we need:
• Suitably intense x-ray production, that is, anSEM that can deliver high beam currents (10 –1000 nA) and a specimen that can withstandhigh dose without degradation.
• Low (ideally “no”) overhead x-ray eventprocessing (try to avoid wasting time sortingand storing “no information” channels)
Al Ni Fe
10 ms
5 ms
2 ms
1 ms
100 μm
How fast?
217 s192 s 12%
121 s 96 s 21%
63 s 38 s 40%
44 s 19 s 57%
160x120 pixels+1.3 msoverhead
SDD can provide the OCR speed• To exploit this OCR speed for mapping (e.g., by x-ray
spectrum imaging), we need:• Suitably intense x-ray production, that is, an SEM that
can deliver high beam currents (10 – 1000 nA) and aspecimen that can withstand high dose withoutdegradation.
2. Low (ideally “no”) overhead x-ray event processing:use “position tagged spectrometry” implemented as“event streaming in hardware”, e.g., see:
Efficient handling of data stream from SDD: EventStreaming (No overhead; move units of information)
• X-ray events are outputted directly from the x-raypulse processor’s auxiliary interface bus into the x-yscan generator. The events are then interpreted andcombined with the x-ray position information into pixelevents. The pixel events are packetized andstreamed to a host computer where they are bufferedand stored. The whole process takes place at thehardware level with an extremely high speed and isthus highly efficient. (Pixel overhead μs rather thanms)
High Speed Spectrum Imaging of Raney Nickel Alloy Using a Large AreaSilicon Multi-Cathode Detector (Vortex-EMTM) and Event Streaming TechniqueM&M 2006L. Feng*, V. D. Saveliev*, S. Barkan*, C. R. Tull*, M. Takahashi*, N. Matsumori*, S. D.Davilla**, J. S. Iwanczyk***, D. E. Newbury**** and J. A. Small****
SDD can provide the OCR speed• To exploit this OCR speed for mapping (e.g., by x-ray spectrum
imaging), we need:• Suitably intense x-ray production, that is, an SEM that can deliver
high beam currents (10 – 1000 nA) and a specimen that canwithstand high dose without degradation.
2. Low (ideally “no”) overhead x-ray event processing: use “positiontagged spectrometry” implemented as “event streaming inhardware”,
With these conditions reasonably satisfied:Specimen: Portland St. MeteoriteOCR = 550kHz Quad SDD, resolution MnKα < 140 eV128 x 96 pixels; 1 ms dwell per pixel = 12.3 seconds
0 1 2 3 4 5 6 7 8 9
FeK
α
FeK
β NiK
α
NiK
β
CrK
α
CrK
βM
nKα
TiK
α
CaK
α
CaK
β
KK
α
SKα
PKα
SiK
αA
lKα
MgK
αN
aKα
OK
αFe
L
CK
α
NiL
FeS Si
keV
This is a 12 second x-ray spectrum image (128x96 pixels)!
QUAD SDDat 500 kHz OCR
Examining peaks inThe SUM PIXELSpectrum (filled):
50 μm
S
Si
Fe
S Fe Si
50 μm
This is a 12 second x-ray spectrum image (128x96 pixels)!
0 1 2 3 4 5 6 7 8 9
FeK
α
FeK
β NiK
α
NiK
β
CrK
α
CrK
βM
nKα
TiK
α
CaK
α
CaK
β
KK
α
SKα
PKα
SiK
αA
lKα
MgK
αN
aKα
OK
αFe
L
CK
α
NiL
CaAl Ni
keV
50 μm
Examining peaks inThe MAX PIXELSpectrum (line):
QUAD SDDat 500 kHz OCR
This is a 12 second x-ray spectrum image (128x96 pixels)!
S Ni
Fe
50 μm
This is a 12 second x-ray spectrum image (128x96 pixels)!
Al
P Ca
Cr Ni Mn
Ti
Mg O
50 μm
This is a 12 second x-ray spectrum image!
With x-ray spectrum imaging now possible in10 to 100 seconds with optimized SDD:
• 1. How can we recover information buried in these ~ 100Mbyte – 1 Gbyte files?– Sophisticated statistical approach, see:
- Simple minded, operator intensive approach:NIST LISPIX (available for free at www.nist.gov; search “LISPIX”)
LISPIX is a comprehensive image manipulation software engine thatincludes many tools that are useful for the study of x-ray spectrumimages and extraction of information.
LISPIX “Derived Spectrum” Tools
• Two views of the x-ray spectrum image (XSI)– As an array of true spectra, one at each pixel
X-ray spectrum imagingA complete spectrum is recorded at each pixel!
X-ray E
nergy
X
Y
Channel (X-ray Energy)
Cou
nts
Cou
nts
Gorlen et al.,Rev.Sci.Inst. v55(1984) 912.
LISPIX “Derived Spectrum” Tools
• Two views of the x-ray spectrum image (XSI)– As an array of true spectra, one at each pixel– As a “card deck” of x-ray images, each 10-eV wide
Cube slices are x-raymaps (images)
X-ray E
nergy
X
Y
The x-ray spectrum image can be viewed as a card deck of x-rayimages, each a 10-eV energy slice
LISPIX “Derived Spectrum” Tools
• Two views of the x-ray spectrum image (XSI)– As an array of true spectra, one at each pixel– As a “card deck” of x-ray images, each 10-eV wide
• Basis of Lispix approach: “derived spectra” SUM Spectrum– Add all counts on a card to find intensity for that keV
3/5/2004
Sum Spectrum:Add the counts fromevery pixel in eachenergy plane; theSUM from a planebecomes the intensityin the correspondingenergy channel of thederived spectrum.
Derived x-ray spectra are calculated from measured spectra within the cube.
X-ray E
nergy
X
Y
Cou
nts
Channel (X-ray Energy)
ReferencesGorlen et al., Rev.Sci.Inst. 55 (1984) 912.
Jeanguillaume and Colliex,Ultramicroscopy, 28 (1989)252.
NiKαNiKbα
AlKα
NiL
LISPIX “Derived Spectrum” Tools
• Two views of the x-ray spectrum image (XSI)– As an array of true spectra, one at each pixel– As a “card deck” of x-ray images, each 10-eV wide
• SUM Spectrum– Add all counts on a card to find intensity for that keV– Peaks identify high abundance features
Peaks in the SUM spectrum correspond to x-ray lines of elements.
Single ‘slice’ or x-ray channel
Multichannel image for Ni peak.
Peaks in sum spectrum correspond to dominant features.
Cou
nts
Channel (X-ray Energy)
LISPIX constructs the image corresponding toan energy plane or group of energy planes.
Developing Derived Spectrum Tools
• SUM spectrum quickly locates spectralfeatures with high abundance
• Problem: How do we find rare, unanticipatedfeatures in the datacube (200 Mbytes):– Rare feature may occur only at one pixel. For a
256x200 scan, one pixel represents 1/51,200– Any element (except H, He, Li) may be of interest
Test every pixel in anenergy plane to findthe MAXIMUMvalue. Thismaximum valuebecomes the intensityin the correspondingenergy channel of thederived MaximumPixel Spectrum.
Maximum Pixel Spectrum
X-ray E
nergy
X
Y
Cou
nts
Channel (X-ray Energy)
Bright and Newbury,J. Microscopy, 216 (2004) 186
10 μm
Cr
Al Cr Ni
LISPIX “Derived Spectrum” Tools
• Two views of the x-ray spectrum image (XSI)– As an array of true spectra, one at each pixel– As a “card deck” of x-ray images, each 10-eV wide
• SUM Spectrum– Add all counts on a card to find intensity for that keV– Peaks identify high abundance features
• MAX PIXEL Spectrum– Find maximum value on a card and plot for that keV– Locates rare, unanticipated features
Time: 123 seconds
Time: 12.3 seconds Of couse, Max Pixel islimited by thestatistics of asingle pixel
LISPIX “Derived Spectrum” Tools• Two views of the x-ray spectrum image (XSI)
– As an array of true spectra, one at each pixel– As a “card deck” of x-ray images, each 10-eV wide
• SUM Spectrum– Add all counts on a card to find intensity for that keV– Peaks identify high abundance features
• MAX PIXEL Spectrum– Find maximum value on a card and plot for that keV– Locates rare, unanticipated features– May not be sensitive to dilute constituents
• RUNNING MAX Spectrum– First average over n-m to n+m cards (e.g., m = 3) to create new
naverage card– Then perform maximum value search on naverage card
RUNNING MAX 12.3 s XSI
RUNNING MAX 6.2 s XSI
RUNNING MAX 3.1 s XSI
Gone!
LISPIX “Derived Spectrum” Tools
• Two views of the x-ray spectrum image (XSI)– As an array of true spectra, one at each pixel– As a “card deck” of x-ray images, each 10-eV wide
• SUM Spectrum– Add all counts on a card to find intensity for that keV– Peaks identify high abundance features
• MAX PIXEL Spectrum– Find maximum value on a card and plot for that keV– Locates rare, unanticipated features– May not be sensitive to dilute constituents
Cl CrK, Ag, or Cd
Maximum pixel spectrum
Log of the SUM SpectrumC
ount
sL
og10
Cou
nts
Channel (X-ray Energy)
NiKα
Al
NiL
Fe
CO
SiO
CAl
NiL NiKα
NiKβ
NiKβCuKα
Where is the Iron?
Fe is not visible in single slice
Fe is confined to one type of region.
Finding dilute iron with the Log of the Sum Spectrum
Cou
nts
Channel (X-ray Energy)
NiKα
NiKβ
Developing Strategy for Rapid Mapping
• How many counts are “enough” to establish visibilityfor an object in a compositional map?
• How many counts are “enough” to establish visibilityfor an object in a compositional map?
• The answer depends on several factors:1. The concentration, C (mass fraction)2. The characteristic x-ray energy
a. Overvoltage, U0 = E0/Ec Ich ~ (U0- 1)n
b. Specimen self-absorption I/I0 = exp [-(μ/ρ) ρ s]c. X-ray detector efficiency
3. X-ray background (continuum) Icm~ Z (U – 1)4. The level of compositional contrast, e.g. vs. Bkg or vs. a different concentration.
Developing Strategy for Rapid Mapping
128x96 1 ms dwell, 10 frames 123 s total 550kHz OCR
Fe
Ni
Al 10 μm
PhasesAl 99.5 Ni 0.5 Al 60 Ni 40Al 71.2 Ni 24.6 Fe 4.2 Al 46.5 Ni 53.5
Almax=3846
Nimax=662
Femax=93
This dose gives sufficient Fe countsto perform a background correction.
Fe raw
BackgroundCorrected;Fe Contrast vsbackground
128x96 1 ms dwell, 10 frames 123 s total 550kHz OCR
Al Fe
Ni Al Fe Ni
10 μm
PhasesAl 99.5 Ni 0.5 Al 60 Ni 40Al 71.2 Ni 24.6 Fe 4.2 Al 46.5 Ni 53.5
Femax= 93
Reduce dose by 10; 128x96 1 ms dwell, 1 frame 12.3 s total 550kHz OCR
Al Fe
Ni Al Fe Ni
10 μm
PhasesAl 99.5 Ni 0.5 Al 60 Ni 40Al 71.2 Ni 24.6 Fe 4.2 Al 46.5 Ni 53.5
Femax= 9
128x96 512 μs dwell, 1 frame 6.2 s total 550kHz OCR
Al Fe
Ni Al Fe Ni
10 μm
PhasesAl 99.5 Ni 0.5 Al 60 Ni 40Al 71.2 Ni 24.6 Fe 4.2 Al 46.5 Ni 53.5
Femax= 5
128x96 256 μs dwell, 1 frame 3.1 s total 550kHz OCR
Al Fe
Ni Al Fe Ni
10 μm
PhasesAl 99.5 Ni 0.5 Al 60 Ni 40Al 71.2 Ni 24.6 Fe 4.2 Al 46.5 Ni 53.5
Femax= 3
128x96 128 μs dwell, 1 frame 1.6 s total 550kHz OCR
Al Fe
Ni Al Fe Ni
10 μm
PhasesAl 99.5 Ni 0.5 Al 60 Ni 40Al 71.2 Ni 24.6 Fe 4.2 Al 46.5 Ni 53.5
Femax= 2
n1
n2
n
Developing Strategy for Rapid Mapping
= P= P+B
= B
For an element localized in one phase
• How many counts are “enough” to establish visibility for an object in acompositional map?
• This issue is closely related to the classic Rose (1948) criterion for contrastvisibility threshold in scanned images. For an object relative to a featurelessbackground, Rose requires the signal to exceed the noise by a factor (“Rosefactor”, RF) of at least 5:
Signal = (n2 – n1) > RF * σn (noise) = RF n11/2
Consider the case of a compositional feature containing element A viewedagainst a featureless background that does not contain element A
For x-rays, n1 = B (continuum) while n2 = P (characteristic) + B
Signal = (n2 – n1) = (P+B – B) = P > RF B1/2
P/B > RF B1/2/B
P/B > RF/B1/2
P/B > 5/B1/2
0
5
10
15
20
25
30
35
40
0 2 4 6 8 10 12
P/B
E (keV)
K
Al
SiP
S
ClMg
CaSc
Ti
V CrMn Fe
Co NiCu
Zn GaGe As Se
Measurements of Peak-to-Background (P/B)
Si(Li) EDS 134 eV at MnKαPure elements (or equivalent)E0 = 20 keV Kα+β peaks
0.01
0.1
1
10
100
0 2 4 6 8 10 12
P/B10% Conc1% Conc
P/B
E (keV)
Pure elements (or equivalent)E0 = 20 keV Kα+β peaksDiluted by element Z+1K
AlSiPSClMg
CaSc
TiV Cr
MnFe Co Ni
Cu Zn GaGe As Se Pure
0.1 mass frac
0.01 mass frac
Measured and Estimated of Peak-to-Background (P/B)
Pure
0.01
0.1
1
10
100
0 2 4 6 8 10 12
P/B10% Conc1% Conc
P/B
E (keV)
Pure elements (or equivalent)E0 = 20 keV Kα+β peaksDiluted by element Z+1K
AlSiPSClMg
CaSc
TiV Cr
MnFe Co Ni
Cu Zn GaGe As Se
B = 25 counts
Pure
0.1 mass frac
0.01 mass frac
B = 2500 counts
P/B > 5/B1/2
Measured and Estimated of Peak-to-Background (P/B)
Pure
• How many counts are “enough” to establish visibilityfor an object in a compositional map?
• The answer depends on several factors:1. The concentration, C (mass fraction)2. The characteristic x-ray energy
a. Overvoltage, U0 = E0/Ec Ich ~ (U0- 1)n
b. Specimen self-absorption I/I0 = exp [-(μ/ρ) ρ s]c. X-ray detector efficiency
3. X-ray background (continuum) Icm~ Z (U – 1)4. The level of compositional contrast, e.g. vs. B or vs.
a different concentration.• A compositional image simulator is needed:
– DTSA for spectral details, such as P/B (soon NIST Monte)– LISPIX to synthesis and process the images for display
Developing Strategy for Rapid Mapping
K961O 0.470Na 0.030Mg 0.030Al 0.058Si 0.299P 0.002K 0.025Ca 0.036Ti 0.012Mn 0.003Fe 0.035
E0 = 20 keV0-20keV: ~1,000 counts
0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0
Photon Energy (keV)
Cou
nts
57
0
K KαP = 14B = 18P/B = 0.8
Desktop Spectrum Analyzer (DTSA) Simulation
Feature: 1 pixel (Rose criterion) = 0.4% of image width (256 pixels)
Size Matters! Effect of Feature Size on Visibility
P/B = 0.2
P/B = 0.4
P/B = 0.6
P/B = 0.8
P/B = 1
P/B = 2
P/B = 4
Detection
B = 25 counts
P/B = 0.2
P/B = 0.4
P/B = 0.6
P/B = 0.8
Feature: 5 pixels square = 2% of image width (256 pixels)
Detection
Determineshape
P/B = 1
Size Matters! Effect of Feature Size on Visibility
B = 25 counts
Feature: 64 pixels square = 25% of image width (256 pixels)
P/B = 0.2
P/B = 0.4
P/B = 0.6
P/B = 1
Determineshape
Detection
Size Matters! Effect of Feature Size on Visibility
B = 25 counts See: Bright, D. S., Newbury, D. E., and Steel, E. B., “Visibility of objects in computer simulations of noisy micrographs”, J. Micros., 189 (1998) 25-42.
Conclusions• SDD performance enables XSI mapping in 10 to
200 seconds (512x394_1ms) if the specimencan withstand the high beam current necessaryto generate high x-ray flux.
• NIST LISPIX interactive tools enable detectionand recovery of compositional features,including those that are rare and unanticipated.
• Strategy for mapping can be developed with thespectral simulation tool in NIST DTSA and thenew image simulation tool embedded in NISTLISPIX.