Electron-Probe Microanalysis: Instrumental Calibration...

UO EPMA Workshop 2008

Electron-Probe Microanalysis:Instrumental Calibration, Standards,Quantitative Analysis, andProblem SystemsPaul CarpenterEarth and Planetary Sciences1 Brookings DriveWashington UniversitySt Louis, MO [email protected]


The Big Picture for EPMA

• Instrumental issues for EPMA:Column-spectrometer alignmentDetector linearity and stability (flow, sealed)WDS deadtime calibrationSpectrometer resolution, reproducibilityNew developments: SDD EDS mapping and quantitative analysis

• EPMA Standards:Proper selection of standards (sample vs. standard)Internal consistency of stds in your lab vs. international environment

• Problem Systems:Peak overlaps, high-order WDS interferencesAnalytical problems, high absorption correctionCorrection algorithms and mass absorption coefficient data sets

• Solutions:Interlaboratory collaboration, educationMultiple KV and multiple spectrometer analysis of core std setPayoff – proof of internal std comps and empirical macs


Washington University, Saint LouisEarth and Planetary Sciences JEOL JXA-8200


Calibration Issues for Electron-Probe Microanalysis

• Microprobe performance specifications are:Driven by capabilities and address problem solving for customersCapabilities are funded by purchases, user/vendor developmentRealistic specifications for WDS vs. EDS systems

• Instrument calibration during installation and testingSpectrometer alignment – to electron column and mutual agreementDetector linearity with count rate and deadtime issuesPrecision = reproducibility (mechanical, electronic)Accuracy = correct K-ratio measured

• Instrument calibration – short vs. long termConsistent performance with timeAccuracy in international interlaboratory environment

• Geological EPMACMAS silicate standards used for acceptance testing (CIT, WU)


Pulse-Height AnalysisWavelength-dispersive spectrometer


WDS PHA Measurement

•Low energy pulses must be discriminated from baseline noise. Need propersetting of noise threshold, baseline, and window settings of WDS pulseheight analyzer.•The pulse processing circuitry of WDS does not need to deal with pulseshaping like that of EDS, and is inherently faster.•Pulse energy shift with varying count rate results in instability. At highcount rates pulses are poorly discriminated from baseline noise. Use similarcount rates on standard and sample.•Avoid tight PHA window, use integral mode unless a PHA interference isobserved.•The P-10 detector gas flow rate must be stable or else gas amplificationfactor varies, and so does count rate.•Temperature variation will affect gas amplification factor as well as thermalexpansion of analyzer crystal.•Low energy peaks need to be integrated due to peak centroid and peakshape/area factors. Use area-peak factor or perform integration.


Bias Scan Si Kα 15kv 25 nADetector Bias for 4 volt SCA Peak: 1632

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1500 1525 1550 1575 1600 1625 1650 1675 1700 1725 1750 1775 1800

Bias, Volts

Coun

ts p

er 1

sec Si Ka, TAP1, 64x

Detector Bias Scan Si KαVary Bias at PHA Narrow Window

Detector bias scan using 3.9 volt baseline and 0.2 volt window on PHA.Intended to minimize energy gain shift of PHA.MSFC Spec 1, P-10 flow counter, TAP, 64x gain, Si Kα on SiO2 metal @ 10k cps.


SCA Scan Si Kα 15kv 25 nABias 1632 Volts, SCA Peak at 4 Volts

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Coun

ts p

er 1

sec

TAP1, 64x, 1632 Bias

Detector PHA Scan Si Kα

For Si Kα there is good separation between baseline and Si pulses.Nominal baseline is 0.5 V with 9.5 V window (integral mode)MSFC Spec 1, P-10 flow counter, TAP, 64x gain, Si Kα on SiO2 @ 10k cps.


Calibration of PHAUsing Bias vs. ln(E) plots

• For JEOL microprobe want SCA pulse at 4 volts, Cameca at 2 volts• Spectrometer at peak position• Bias scan with 3.8v base, 0.2v window gives bias for 4 volt SCA• Plot of bias vs ln of x-ray energy is linear• Calibration performed for minimum element set which spans energy

range of spectrometer for all analyzing crystals• Detector should give same bias for Ti Kα on PET vs. LIF, others• Calibration confirms systematic behavior of x-ray counter• As P-10 tank empties and Ar/CH4 changes, requires recalibration• Use y = mx + b fit to bias data to provide quick calibration• Similar plot for escape peak as function of x-ray energy


PHA Bias Plot for LIF/PET DataSi, Ti, Ni Bias data at 8, 16, 32, 64, and 128x Gain

WU 8200 Detector Bias Spectrometer 3Settings for 4 Volt Pulse

y = -87.037x + 1955.1

y = -94.949x + 1889

y = -98.905x + 1808

y = -108.8x + 1748.9

15001525155015751600162516501675170017251750177518001825185018751900

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Ln Energy

Bia

s, V

olts

LIF 8xLIF 16xLIF 32xLIF 64xLIF 128xPET 32xPET 64xPET 128xSi, PET

Ti, PET and LIFNi, LIF

y = mx + by = bias, x=ln(E)


Gain Shift Due to Count Rate

Gain shift due to count rate, detector bias arbitrarily set to 1700 volts.Observed shift is ~ 0.008 volts per 1 K cps (1.95 volt shift over 245 K cps range).At ~125k cps baseline noise discrimination deteriorates.Older PCS electronics exhibit complete shift into baseline noise.MSFC Spec 1, P-10 flow counter, TAP, 32x gain, Si Kα on Si metal.

5K cps3.75 V

60K cps3 V

125K cps2.6 V

250K cps1.8 V


PHA Scan Ti Lα 20K CPS

Light element / low energy x-rays are poorly resolved from baseline noise.Gain shifts with count rate – PHA peak shifts toward baseline with increasingcount rate. Use integral mode unless PHA energy discrimination required –counts extend to upper limit of PHA scan.MSFC Spec 1 with P-10 flow counter, LDE2, 128x gain, Ti Lα on Ti metal @20k cps.


Carbon Kα PHA Scans Graphite, Fe3C

Scaled PHA Scans C Kα LDE2 10 KeV

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0 1 2 3 4 5 6 7 8 9 10Baseline, Volts

Rel

ativ

e In

tens

ity

Graphite 100 nA > 65 kcps

Graphite 25 nA ~ 23 kcps

Fe3C 100 nA ~ 2 kcps

Scaled PHA scans demonstrateconsistent PHA behaviorNo baseline – noise is presentLDE2, 128x gain, 1750V

Baseline 0.5V, 9.5V Window


Deadtime Measurement on theWavelength-Dispersive Spectrometer


WDS Deadtime Issues in EPMA

• Deadtime – time interval during which counting electronics are unable toprocess subsequent incoming pulses• Deadtime error is non-negligible, systematic, affects all measurements• General problem:• Counting behavior of WDS systems is undocumented and poorly known• End-users make measurements with assumed WDS deadtime behavior• User knowledge of deadtime issues needs improvement• Specific problem areas:

No software to conveniently evaluate deadtime on turnkey systemsNo agreed method for setting bias, gain, and sca on systemsSCA pulse shift behavior with count rate undocumentedDeadtime dependence on X-ray energy undocumented and unknownLow vs. high count rate behavior and deadtimes inconsistent


Deadtime Behavior:Extending vs. Nonextending

Nonextending vs Extending Deadtime

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mal

ized

Out

put C

ount

Rat

e

Nonextending

Extending

Nonextending: N = Nm (1 – N τ), Nmax = 1/τExtending: N = Nm e –Nm τ , Nmax = 1/eτ

Nm τ

N τ


Deadtime LossesInput – Output Curves for μsec Deadtime Constants

WDS Deadtime Losses

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Input Counts per second

Out

put C

ount

s per

sec.

1.00E-062.00E-064.00E-065.00E-066.00E-06


Percentage Deadtime LossesPercent Level Corrections Apply to All Measurements

Deadtime Correction, Percentage

0123456789

10

0 10000 20000 30000 40000 50000Input Counts per second

Dea

dtim

e C

orre

ctio

n, %

6.00E-065.00E-064.00E-062.00E-061.00E-06

~1.25 μsec

At 1 μsec, 1% correction at 10Kcps, 5% at 50KcpsAt 2 μsec, 2% correction at 10Kcps, 10% at 50Kcps


Deadtime RelationsCalculation of Deadtime Constant

• N = true count rate, Nm = measured count rate withdeadtime losses (Nm < N), and τ is the deadtime constant,which ranges from 1 to several μsec for WDS countingsystems. It is necessary to know Nm and N to calculate τ.We assume the proportionality of N to the probe current iis constant. This may not be true at low count rates.

• Nm / i = measured count rate in counts per second per nA,and c is the constant N / iForm: y = mx +b (Nm / i) is y, x is Nm, y-intercept b is constant c (= N / i).

• Equivalent to τ = (1 – y / b) / xMeasure x-ray intensity at increasing probe currentUse count rate Nm and Nm / i to evaluate the deadtimeconstant τ over a range of intensity values

=

) N - (1N N

m

m

τ

)= τ N - c(1

iN m

m

Ν] / ) / Ν( −[1

=m

m ci τ


Deadtime Evaluation PlotNm vs. Nm / i to determine LS Fit to τ


Verification of Probe Current vs. Absorbed Current Linearityand/or Detection of Sample Charging

Identification of Sample Charging:Ratio of Absorbed Current to Probe Current

0.000.100.200.300.400.500.600.700.800.901.00

0 100 200 300 400 500 600 700 800 900Cup Current, nA

Abs

orbe

d / C

up C

urre

nt

Conductive Si WaferConductive Si Wafer Run 2Charging Si Wafer


Deadtime Calculation from Excel Spreadsheet

nA Abs Cur Abs/Probe Time Cps (x) Cps/nA (y) Fit All Fit Last DT us All DT Last2.00 1.63 0.82 100 4607.9 2302.57 2299.81 0.615.00 4.05 0.81 80 11436.9 2287.20 2286.17 0.83

10.01 8.10 0.81 80 22665.3 2264.44 2263.73 0.8520.05 16.25 0.81 60 44469.0 2217.95 2220.18 0.8925.00 20.29 0.81 60 54977.1 2199.08 2199.18 2197.08 0.87 0.8329.98 24.34 0.81 30 65298.1 2177.91 2178.56 2177.00 0.87 0.8435.02 28.54 0.81 30 75474.9 2155.07 2158.23 2157.20 0.88 0.8640.05 32.53 0.81 30 85510.0 2134.97 2138.18 2137.67 0.88 0.8649.99 40.74 0.81 30 105026.6 2101.04 2099.19 2099.70 0.86 0.8469.98 57.25 0.82 30 141942.7 2028.45 2025.44 2027.88 0.86 0.84

Regression Output: Mean deadtime 0.86 0.84All Y intercept 2309.01 Slope -0.0020 Sigma 0.02 0.01High CR Y intercept 2304.04 Slope -0.0019 Regression DT 0.87 0.84

Excel Sheet: X is Nm and Y is Nm/i. Deadtime evaluated from each intensity (DT) andfrom least squares fit to data (Fit) using Excel linest function. All data and high intensityonly data are compared with average values (Mean deadtime) and standard deviation.Ratio of absorbed/probe current checks conductivity. If linear all data agree.


Deadtime Si Kα TAP Spec 2 Caltech 733

1.001.101.201.301.401.501.601.701.801.902.002.10

0 25000 50000 75000 100000 125000 150000 175000Counts per second

Dea

dtim

e, μ

sec

4/25/91 Original Noran

Deadtime Variation with Count Rate

Caltech 733 Spec 2 with P-10 flow counterDeadtime at low count rates include darkcurrent and are not representative of dynamicrange of spectrometer


Deadtime Variation With Time and P-10 Gas ChemistryComparison of Original and New Tracor PCS Electronics


Alignment and Quantitative Analysis:Wavelength-Dispersive and Energy-Dispersive Spectrometers


Establishing Calibration of an Electron Microprobe

• Wavelength spectrometer aligned vertically (baseplate) to coincide withoptical microscope focal point in z-space• Diffracting crystal aligned to be on Roland circle• All WDS should focus on same z-axis and coincident xy area ~ 50 um indiameter• Characteristics of correct alignment

All WDS & EDS have identical X-ray takeoff angleMaximum X-ray intensity at z focus position, but also require:Measure identical k-ratio within counting statistics

• Simultaneous k-ratio measurement is ultimate test of alignment• Initial CMAS standard set used on Caltech MAC and JEOL JXA-733• Expanded CMASTF standard set used for Wash U JXA-8200


Electron Microprobe ColumnSpectrometer Alignment: Baseplate and Crystal

Baseplate: Place Rowland circle at Z focusCrystal: Align all crystals on Rowland circleSpectrometer design keeps detector on RCNote: Different K-ratio = misalignmentMultiple spectrometer comparison requiredto demonstrate all WDS and EDS aremutually aligned


CMASTF Silicate StandardsGeological materials are multicomponent

• End-member stoichiometric silicate and oxide mineral standards• Primary standards:

MgO, Al2O3, SiO2, CaSiO3 (CaO 48.27, SiO2 51.73), TiO2, and Fe2O3

• Analyzed suite of stoichiometric standards, natural and synthetic materials:Second set of primary standards on different mountsSpinel MgAl2O4, Enstatite MgSiO3, Forsterite Mg2SiO4Kyanite Al2SiO5Fayalite Fe2SiO4

• Well characterized natural mineral standards and glasses:Olivines (Mg,Fe)2SiO4

Diopside CaMgSi2O6, Anorthite CaAl2Si2O8, Sphene CaTiSiO5Ilmenite FeTiO3Synthetic glasses in CMAS and CMASF system:

Weill CMAS glasses, NBS K411, K412


CMASTF Standard Inventory: Natural & SyntheticComposition in Wt% Oxide

36.9942.9819.021.01Weill J26.0152.952.0119.03Weill I21.9730.9141.905.22Weill H2.8961.123.3132.69Weill G6.9452.0630.9310.07Weill F

59.850.0040.15Weill Enstatite Glass5.0479.978.996.00Weill E*16.0045.0720.9617.97Weill D20.9748.9916.0513.99Weill B23.1549.7216.0711.05Weill A

71.6628.34Taylor Spinel0.6637.8028.8230.831.36Taylor Sphene7.6241.1550.78Taylor Olivine0.1637.0062.700.00Taylor Kyanite16.6238.9543.58Springwater Olivine

42.7057.30Shankland Forsterite9.5540.8149.42San Carlos Olivine70.5129.49ORNL, RDS Fayalite0.260.0125.7855.400.0618.31Natural Bridge Diopside

37.0962.91Kyanite P2369.9615.2545.359.2719.33K412 Glass14.4215.4754.300.1014.67K411 Glass46.5445.700.31Ilmen Mtns Ilmenite7.1740.8551.63Boyd Olivine0.6219.0944.0036.03Alaska Anorthite

FeO* orFe2O3TiO2CaOSiO2Al2O3MgOStandard


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140

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Armstrong PRZ Heinrich 1986

Pouchou Experimental Binary K-ratio Data Set (n=756)Φ(ρz) Algorithm – No silicates or multi-element materials

Average Kcorr / Kexp = 1.0079 +/- 0.0382 (1 σ)

Armstrong Φ(ρz)Heinrich 1986 macs


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30 KV25 KV20 KV15 KV10 KV

Ag Lα NIST SRM 481 AgAu Alloy (ψ=40)

C Ag, weight fraction

C /

K

C vs. C / K plot for Ag Lα datay = mx + bα factor is b interceptslope is 1-α


Accuracy Study for EPMAComparison of Measured to Calculated K-ratio

•Kmeasured dependent on:Accelerating PotentialProbe currentDetector (gas, sealed)Pulse processingPHA calibrationDeadtimeSpectrometer alignmentSample homogeneityP-B determination, stripping, counting statisticsOther sampling/drift factors

•Kcalculated dependent on:Correct composition of standardCorrection algorithmsData sets, mass absorption coefficientsOther algorithmic factors

calculated

measured

calculated

standard

sample

measured

KK :Evaluate

ZAF / C K

ZAF*KC

B)(PB)(PK

=

=

−−=


Historical CMAS DataCaltech MAC Probe, Circa 1980’s

Shaw Data Set: Caltech MAC Probe (38.5 deg, 15 kV)Armstrong φ(ρz), FFAST macs

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Weight % Oxide

Mea

sure

d W

t% /

Acc

epte

d W

t%

Mg

Al

Si

Ca


Caltech JEOL 733 1990’sSpectrometer 1 TAP for Mg Al Si (Ca PET)

Shaw Data Set: Caltech Jeol 733 -- TAP1 MgAlSi PET3 CaArmstrong φ(ρz), FFAST macs, 15 kV

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epte

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t%

Mg

Al

Si

Ca




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Shaw Data Set: Caltech Jeol 733 -- TAP:1Mg 2Al 4SiArmstrong φ(ρz), FFAST macs, 15 kV

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sure

d W

t% /

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epte

d W

t%

Mg

Al

Si

Ca


Intercomparison of Measured vs. AcceptedConcentration for Standards on Microprobes

0.00630.00610.01880.0077Caltech 733 Mg1Al2Si4, 1sd0.99840.99050.98170.9894Caltech 733 Mg1Al2Si4, avg

0.00960.00590.01010.0095Caltech 733 Spec 4 MgAlSi, 1sd0.99710.99380.98620.9783Caltech 733 Spec 4 MgAlSi, avg



0.01070.00580.01710.0105MAC, 1sd1.00770.99400.99481.0030MAC, avg

Cmeas/CcalcCa

Cmeas/CcalcSi

Cmeas/CcalcAl

Cmeas/CcalcMgInstrument


WU JXA-8200 CMASTF Data SetAll WDS Data Superimposed

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Mg1 TAPMg2 TAPAl1 TAPAL2 TAPSi1 PETSi1 TAPSi2 TAPSi3 PETSi4 PETSi5 PETHCa1 PETCa3 PETCa4 PETCa5 PETHCa3 LIFCa4 LIFCa5 LIFHTi1 PETTi3 PETTi4 PETTi5 PETHTi3 LIFTi4 LIFTi5 LIFHFe3 LIFFe4 LIFFe5 LIFH

Oxide Weight Percent

Km

eas /

Kca

lc


WU JXA-8200 CMASTF Data SetSpectrometer 1 PET and TAP

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Mg1 TAPAl1 TAPSi1 PETSi1 TAPCa1 PETTi1 PET


Km

eas /

Kca

lc


WU JXA-8200 CMASTF Data SetSpectrometer 2 TAP

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Mg2 TAPAL2 TAPSi2 TAP


Km

eas /

Kca

lc


WU JXA-8200 CMASTF Data SetSpectrometer 3 PET and LIF

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Si3 PETCa3 PETCa3 LIFTi3 PETTi3 LIFFe3 LIF


Km

eas /

Kca

lc


WU JXA-8200 CMASTF Data SetSpectrometer 4 PET and LIF

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Si4 PETCa4 PETCa4 LIFTi4 PETTi4 LIFFe4 LIF


Km

eas /

Kca

lc


WU JXA-8200 CMASTF Data SetSpectrometer 5 PETH and LIFH

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Si5 PETHCa5 PETHCa5 LIFHTi5 PETHTi5 LIFHFe5 LIFH


Km

eas /

Kca

lc


Average Kmeas / Kcalc for CMASTF StandardsWashington University JEOL 8200

1.01311.00510.9962Fe LIF

1.00840.99490.9919Ti LIF

1.01151.00441.00591.0000Ti PET

0.99890.99480.9908Ca LIF

1.01011.00351.00641.0013Ca PET

0.98800.98370.98650.9855Si PET

0.99550.9981Si TAP

0.99460.9950Al TAP

0.99710.9997Mg TAP

Spec 5Spec 4Spec 3Spec 2Spec 1WDS


Accuracy, 1σ % Error in Kmeas / Kcalc CMASTFStandards Washington University JEOL 8200

1.261.271.75Fe LIF

1.141.150.61Ti LIF

1.540.981.442.27Ti PET

0.690.920.74Ca LIF

0.740.700.730.79Ca PET

0.700.750.710.71Si PET

0.640.74Si TAP

1.221.06Al TAP

1.300.65Mg TAP

Spec 5Spec 4Spec 3Spec 2Spec 1WDS


WU JXA-8200 CMASTF Data SetAll WDS Data Superimposed Expanded Scale

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Mg1 TAPMg2 TAPAl1 TAPAL2 TAPSi1 PETSi1 TAPSi2 TAPSi3 PETSi4 PETSi5 PETHCa1 PETCa3 PETCa4 PETCa5 PETHCa3 LIFCa4 LIFCa5 LIFHTi1 PETTi3 PETTi4 PETTi5 PETHTi3 LIFTi4 LIFTi5 LIFHFe3 LIFFe4 LIFFe5 LIFH


Km

eas /

Kca

lc


Washington UniversityEarth and Planetary Sciences JEOL JXA-8200 SDD

JEOL e2v Silicon Drift Detector130 eV resolution3 time constants T3 T2 T1Stage and beam mappingQuantitative EDS analysis LLSQ


JEOL 8200 Stage Maps: Lunar Meteorite SAU169WDS vs. SDD Mg @ 15KV, 120nA, 25ms dwell

Mg WDS 1061 max counts, Mg SDD 527 max counts1024x1024 stage map, 8 hours


Lunar Meteorite SAU169Stage map 1024x1024, 25 ms, 8 hr run

Backscattered electron vs. Fe SDD maps


Lunar Meteorite SAU169Stage map 1024x1024, 25 ms, 8 hr run: Ca SDD


WU8200 JEOL SDD55Fe Source Mn Kα Resolution 130 eV

Washington University JEOL 8200SDD Mn Spectra T3 15 KeV, 100 sec55Fe Source ~255 Cps 0.27% Deadtime

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nts p

er 1

00 se

c

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25nA T3

10nA T3

Mn 55Fe

140k cps

125k cpx

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50k cps

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10K cps


SDD Performance Data:WU8200 SDD Mn Target, T1 15 KeV, 100 sec

Washington University JEOL 8200SDD Mn Spectra T1 15 KeV, 100 sec

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300nA T1200nA T1150nA T1100 nA T150nA T125nA T110nA T1

210k cps150k cps125k cps80K cps50k cps25k cps10K cps


SDD Performance Data:WU8200 SDD Mn Target, T3 15 KeV, 100 sec


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nts p

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300nA T3200nA T3150nA T3100nA T350nA T325nA T310nA T3



WU8200 SDD Mn K SpectraT3, 100 sec


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Nor

mal

ized

Inte

nsity




WU8200 SDD Mn K SpectraT1, 100 sec


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mal

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Inte

nsity




WU8200 SDD Mn L SpectraT3, 100 sec


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mal

ized

Inte

nsity




WU8200 SDD Mn L SpectraT1, 100 sec


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Energy, KeV

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mal

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Inte

nsity




WU8200Probe Current vs. Count Rate

WU8200 JEOL SDD: Probe Current vs. Output

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Probe Current, nA

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nts p

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T3 Cps


WU8200 SDDDeadtime vs. Count Rate

Washington University JXA-8200 SDDDeadtime vs. Count Rate

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econ

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T3


WU8200 SDDCount Rate vs. Resolution

Washington University JXA-8200 SDDMn Resolution vs. Cps @ T1 - T3

y = 3E-05x + 146.68

y = 6E-05x + 133.93

y = 0.0001x + 128.66

125

130

135

140

145

150

155

160

0 50000 100000 150000 200000 250000 300000 350000

Counts per second

Res

olut

ion

T1T2T3


WU8200 SDDCount Rate vs. Resolution for C, Si, Mn, Ni

Washington University JXA-8200 JEOL SDDEnergy Resolution vs. Input Count Rate @ T3

Ni: y = 7E-05x + 144.11

Mn: y = 7E-05x + 129.75

C: y = -2E-06x + 121.46

Si: y = 6E-05x + 84.43

80

90

100

110

120

130

140

150

160

0 25000 50000 75000 100000 125000 150000 175000 200000

Counts per Second

Ene

rgy

Res

olut

ion

FWH

M

Ni

Mn

Si

C


Washington University JXA-8200 SDDCorning 95IRV: K, Ti, Cr, Fe, Ce, Hf

Washington University JXA-8200 SDDCorning 95-Series Trace Element Glasses @ 15 KeV, 50 nA

1

10

100

1000

10000

100000

1000000

0 1 2 3 4 5 6 7 8 9 10

Energy, KeV

Cou

nts

95IRV, T3, 250s95IRV, T3, 5s

K

O

CrTi,Ce

Ca

Mg, Al, Si

Fe Hf


Washington University JXA-8200 SDDCorning 95IRW: V, Mn, Co, Cu, Cs, Ba, La, Th

Washington University JXA-8200 SDDCorning 95-Series Trace Element Glasses @ 15 KeV, 50 nA

1

10

100

1000

10000

100000

1000000

0 1 2 3 4 5 6 7 8 9 10

Energy, KeV

Cou

nts

95IRW, T3, 250s95IRW, T3, 5s

O

Ca

Mg, Al, Si

BaMn Co Cu

VLa

Th


Washington University JEOL JXA-8200SDD Quantitative Analysis Data

• SDD great for mapping, what about quantitative analysis?• SDD EDS data acquired at 120s, 60s, and 3s acquisitions at T3• Standards used: MgO, Al2O3, SiO2, CaSiO3 (CaO 48.27, SiO2 51.73), TiO2,and Fe2O3

• Linear least-squares peak deconvolution (JEOL software)• Extracted raw K-ratios processed using Armstrong Φ(ρz) and FFAST macsfor comparison with WDS data


CMASTF Standard AnalysesWU8200 SDD LLSQ 120 sec. Acquisition T3

Measured K Relative to Calculated KW U8200 SDD 120 sec Acquisition

0.80

0.90

1.00

1.10

1.20

0 10 20 30 40 50 60 70 80 90 100

Weight Percent Oxide

Km

/ K

c

Mg Km/KcAl Km/KcSi Km/KcCa Km/KcTi Km/KcFe Km/Kc



Measured K Relative to Calculated KWU8200 SDD 60 sec Acquisition

0.80

0.90

1.00

1.10

1.20

0 10 20 30 40 50 60 70 80 90 100Weight Percent Oxide

Km

/ K

c




Measured K Relative to Calculated KWU8200 SDD 3 sec Acquisition

0.80

0.90

1.00

1.10

1.20

0 10 20 30 40 50 60 70 80 90 100

Weight Percent Oxide

Km

/ K

c



Average Kmeas / Kcalc for CMASTF StandardsWU8200 SDD Data @ 120, 60, 3 sec acquisition T3

2.091.192.141.042.591.61Relative %0.02110.01180.02130.01040.02630.01621 σ1.01230.99470.99331.00011.01351.0061Average

3s Data

1.121.510.670.691.611.17Relative %

0.01130.01500.00660.00690.01620.01181 σ

1.00830.99750.98950.99691.00221.0058Average60s Data

1.381.060.670.781.210.62Relative %0.01400.01060.00660.00780.01220.00631 σ1.01081.00210.99261.00171.00641.0122Average

FeTiCaSiAlMg120s Data


EPMA Standards


Advances in EPMA:Geological Materials -- Standards

•EPMA standards requirements: Homogeneous on micron scale, grain tograin, well characterized on both scales, and available in large enoughquantity to be used by microanalysis communities.•Most materials fail one or more of these requirements.•Natural and synthetic minerals, oxides, and glasses. Minerals impose stoichiometry but may be inhomogeneous Glasses lack stoichiometric control but can be homogeneous•Glasses: targeted compositions that can be made in bulk and utilized by themicroanalysis community.(Corning 95-series trace element glasses)•Internal consistency of EPMA standards used by the community is poorlyknown. Few comparison reports, generally anecdotal.•Solution: calculate expected x-ray intensity for element of interest in suite ofstandards, compare measured intensities relative to end-member standard(oxide), i.e., k = ZAF / C. This highlights errors in composition as well assystematic errors in algorithm.


Basalt Glass Indian Ocean USNM 113716:EPMA vs. Wet Chemistry Data

Of

Of the 3-5 mounts of UNSM 113716, this is the first observation of mineralinclusions or crystallites in the glass. This is otherwise a homogeneous standard,consistent with EPMA of other glasses, but based on wet chemistry comparison.How representative is this of the wet chemical analysis?

DevitrificationPlag

Glass


Olivine Standards: Mg-rich (Mg,Fe)2SiO4

Minor/Trace Els.Nat./Syn.Standard

<none>SyntheticLLNL “Fo67” (Fo70)

Ca, Cr, MnNaturalSpringwater olivine Fo82

Al, Ca, Cr, Mn, Co?, Ni?SyntheticLLNL “Fo80” (Fo85)

Al, Ca, Mn, ZnSyntheticFujisawa sintered Fo90

Na?, Mg, Al, Ca, Ti?, Cr, Mn, Co, NiNaturalSan Carlos olivine Fo90

<none>SyntheticLLNL “Fo85” (Fo93)

Mn, Co, Ni, Zn?NaturalBoyd olivine Fo93

Fe?SyntheticShankland forsterite Fo100

Shankland from ORNLLLNL olivines from George Rossman, Boyd and Fujisawa from CaltechSan Carlos and Springwater olivine from Smithsonian


Olivine Standards: Mn, Fe, Ni

Minor/Trace Els.Nat./Syn.Standard

Cr?, Fe, CoSyntheticNi-olivine P-877

Al?, Ca?, CrSyntheticFayalite ORNL

Mg, Ca, Cr, Mn, ZnNaturalRockport Fayalite

Mg, Cr, MnSyntheticFayalite RDS P-1086

MnSyntheticFayalite GRR-391

Mg, Ca, FeSyntheticMn-olivine RDS P-1087

FeSyntheticMn-olivine GRR-392

GRR and RDS from George Rossman, P numbers Caltech probe standardsRockport Fayalite from Smithsonian


Rockport Fayalite

• RF is widely used as primary Fe standardBut Mg and Zn present, not in wet chemistry analysis[Low level oxides suspected to be variable not reported in wc analysis]

• Is ferric iron present? – apparently not: Wet Chemistry: Fe2O3 1.32, FeO 66.36 %, Tot: 99.18 Dyar XANES: RF iron is completely reduced.• Grunerite in separate: Fe7

2+Si8O22(OH)2

• Magnetite at locality, in separate (Fe23+Fe2+O4) ??

• Analysts should use EPMA analysis when using RF as primary standard.


Fayalite Standards

1.9991.9791.9821.999Σ M2+

1.0001.0101.0091.001Si

(100.04)100.16100.4899.18Total0.0070.0060.575Not reportedZnO0.0110.0120.007NiO

(70.34)69.6167.6267.55FeO*0.2120.0922.132.14MnO0.01000.059Cr2O3

0.00400.045CaO(29.49)30.0429.9929.22SiO2

00.3850.046Not reportedMgO

GRR391EPMA**

RDS P-1086EPMA

RockportEPMA

Rockport WetChemistry

Oxide

Rockport WC: FeO 66.36, Fe2O3 1.32, FeO* 67.55. TiO2 0.04, H2O 0.1EPMA: PAPF, olivine stds, Heinrich 1986 macs, 20KV, n=4 **GRR391 std Si, Fe


Systematic Errors in Olivine M2+2SiO4

PAPF, Heinrich 1986 macs @ 20 KV, 40 TOA

1.9952.0181.9812.0222.0122.023

Σ M2+

2 ideal

0.0050.0060.0030.0010.0060.007

σ

0.0030.0030.0010.0010.0030.004

σ

0.300.330.230.200.370.42

σ, wt%

0.99199.32OxideMn,NiOlivines 1.002100.07Syn. Olivine

1.010100.34Syn. Olivine0.990100.93OxideFayalites0.994100.22Syn. Olivine0.989101.14OxideOlivines

Si cations1 ideal

AnalysisTotal

StandardType

OlivineGroup

Averages of total and cation stoichiometry for all olivines from test data set.For olivines, Mg/(Mg+Fe) = 0.860 ± 0.080 (ox) vs. 0.861 ± 0.079 (oliv).Identical k-ratios corrected using PAP full Φ(ρz) and Heinrich 1986 macs,relative to oxide vs. synthetic olivine standards.Olivine Formula: M2+

2SiO4


Systematic Error Using Oxide Standards

Olivines: Oxide Standards / Syn. Olivine StandardsPAPF Heinrich 1986 macs 20 KV

0.9750.9800.9850.9900.9951.0001.0051.0101.0151.0201.025

0 10 20 30 40 50 60 70 80

Wt% Oxide in Olivine (MgO, SiO2, FeO)

Oxi

de S

tds /

Oliv

ine

Stds

Olivine SiO2Olivine MgOOlivine FeO

Fe FayaliteFe Olivine

Si Olivine

Si Fayalite, Mn,Ni Olivine

Mg Olivine

Mg Fayalite


Status Report: EPMA of Olivine

• EPMA using synthetic olivine standards better than oxide standards:Superior analysis total, Si cation ~1.0, and ΣM2+ ~ 2.0

• Improvement in EPMA accuracy for olivine usingArmstrong Φ(ρz) coupled with FFAST mac data set.

• Using oxide standards we observe: Overcorrection of Mg and Fe in olivine across Fo-Fa binary

Undercorrection of Si in low-Mg olivine (Fayalite, Mn-ol, and Ni-ol)Marginal underestimation of Mg/(Mg+Fe).

• These relationships extend to all MgFe silicates relative to composition.• Alpha-factor analysis of systematic errors in Fo-Fa system: EPMA and wet chemistry of natural olivines are not internally consistent.

Worst: Boyd Forsterite Mg and Fe not consistent (Caltech standard)Best: Springwater Mg,Fe, and Mg in San Carlos (Fe in SC less so)


Accuracy of EPMA:Quantitative Analysis of Olivine


Olivine EPMA Accuracy Study:Alpha factor method extended to olivine

• Alpha factor (α-factor) method used to evaluate:Systematic errors for Φ(ρz) correction algorithmsInternal consistency of EPMA-only data and EPMA vs. wet chemistry.

• Compositional end-members for α-factor systems:Pure elements Mg – Fe, i.e., Ziebold-OgilviePure oxides MgO – FeO, i.e., Bence-AlbeeOlivine binary Mg2SiO4 – Fe2SiO4

• Synthetic olivines, pure Fo and Fa, used as primary standards for α-factoranalysis.• Natural olivines require projection onto Fo-Fa binary for comparison.• Anticipate decreased reliance on correction algorithm and fundamentalparameters as one moves from pure element end members to olivine endmembers. Measurement errors ultimately control accuracy.


Olivine Alpha Factor Study:Comparison of Calculated and Measured Concentration•Calculated α-factors using Φ(ρz) algorithms and mass absorptioncoefficients and a polynomial fit to the individually calculated values. C known, K calculated.•Experimental α-factors extracted from olivine analyses. K measured, C calculated. Compared with calculated α-factors. If measurements, algorithms, and data sets are correct, all experimentally determined analyses would lie on theoretical lines.•Wet chemistry data evaluated. K measured, C obtained from wet chemistry.

If wet chemistry data, algorithms and data sets are correct, all wet chemistry analyses would also lie on the theoretical lines.


Extraction of α-factors from Experimental Measurements

AAB

AABA

AB

AAB

AAB C

CKC

−

⎥⎦

⎤⎢⎣

⎡−

=1

α

0 CA, weight fraction 1

C / Kα = 1

α2 > 1

α1 < 1α1

α2slope = 1 - α

Abs

Enh

( )

stdsmp

AAB

AAB

AABA

AB

AAB

BPBPKmxby

CKC

)/()(

1

−−=

+=

−+= αα

For olivine:Forsterite: C = Wt Fraction MgO / [MgO in Mg2SiO4]Fayalite C = Wt Fraction FeO / [FeO in Fe2SiO4]


Analysis of Mg Kα in Shankland Forsteriteusing MgO Std: Experimental Determination of α-factors

C / K Data Mg Kα in SiO2 - MgOShankland Forsterite

y = -0.075x + 1.075y = -0.1428x + 1.1428y = -0.1909x + 1.1909

1.000

1.050

1.100

1.150

1.200

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Weight fraction MgO

Mg

Kα

C /

K

Exp 15 KVExp 20 KV

Exp 25 KV

Bence-Albee Analysis of Forsterite for Mg Kα using MgO


MgO Std – Shankland Fo Mg KαVariation of α-factors with Composition, kV

Oxide Binary a-factors: SiO2 - MgOExperimental Shankland Fo vs. φ(ρz)

1.050

1.100

1.150

1.200

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Weight fraction MgO

Mg

K α α

-fac

tor [

C /

K -

C ]

/ ( 1

- C

)

Arm PRZ H8625KVExp 25 KV

PAPF H8620KVArm PRZ H8620KVPDR H8620KVPDR H6620KVExp 20 KV

Arm PRZ H8615KVExp 15 KV

15 kV

20 kV

25 kV

Multiple kV Analysis Highlights X-ray Absorption Errors


Mg Kα in Olivine Using Forsterite StandardCalculated and Experimental Data, Effect of MAC’s

1.450

1.500

1.550

1.600

1.650

1.700

1.750

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Calc -- Heinrich 1966

Exp -- Heinrich 1966

Calc -- Heinrich 1986

Exp -- Heinrich 1986

Calc -- Henke

Exp -- Henke

Boyd Forsterite WC

San Carlos WC

Springwater WC

Calc -- FFAST

Armstrong φ(ρz) 15 KV 40 TOA

[MgO] / [MgO in Forsterite], wt fraction

RF Fo25 Fo35 Fo40 Fo60

Fo70 Fo85 Fo90 Fo93

SC

BF

SP

Mg

Kα

α-f

acto

r [(C

/ K

- C

)/(1

- C)]

1. Historical overcorrection, esp. H66 at Fo-rich, FFAST macs reduce overcorrection.2. Good agreement EPMA of syn. and natural olivines, esp. H86, Henke using Armstrong Φ(ρz).3. Boyd Forsterite Mg value of wet chemistry inconsistent with wc of San Carlos and Springwater.


Fe Kα A-factors in Fo-Fa BinaryBetter accuracy compared to Mg

Armstrong φ(ρz) 15KV 40 degrees

1.060

1.070

1.080

1.090

1.100

1.110

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

[FeO]/[FeO in Fayalite], wt fraction

Fe K

α α

-fac

tor [

C/K

-C] /

(1-C

)

Calc a-factors Henke

Calc a-factors Heinrich1986 and 1966Exp -- Heinrich 1986

Exp -- Henke

Exp -- Heinrich 1986sinteredExp -- GMR/Heinrich1986Boyd Forsterite

San Carlos Olivine

Springwater OlivineFo60 Fo40 Fo35 Fo25

Fo93 Fo90 Fo85 Fo80 Fo70

BFSP

SC

FFAST values intermediatebetween Henke and Heinrich

1. Minimal dependence on mac data set. Could calculate Mg by 2-Fe for binary olivines only.2. Good agreement EPMA of syn. and natural olivines with Armstrong Φ(ρz).3. Continuum fluorescence important for Fo-rich olivines.4. Boyd Forsterite and San Carlos Fe value of wet chemistry least consistent with others.


PDR: Philibert-Duncumb-Reed ZAF, oxide stds, Heinrich 1966 macsPAPF-1 and Arm-1: Φ(ρz) algorithms, oxide stds, Heinrich 1986 macsPAPF-2 and Arm-2: synthetic olivine stds, Heinrich 1986 macsPAPF-3 and Arm-3: synthetic olivine stds, FFAST macsSame k-ratios, n=4, CaO 0.09, Cr2O3 0.06, MnO 0.14, NiO 0.37 (wt %)Olivine Formula: M2+

2SiO4 [PFW 7/2004, PDR and PAPF algorithm errors corrected]

EPMA of San Carlos OlivineCorrection Method and macs @ 20 KV, 40 TOA

0.9000.8980.9010.8990.9000.8990.8980.902Mg/(Mg+Fe)

0.9970.9920.9910.9910.9820.9860.9860.997Si

2.016

100.60

9.89

40.58

49.44

Arm-2Ol / H86

2.014

99.90

9.89

40.34

48.98

PAPF-3Ol / FF

2.016

100.60

9.89

40.56

49.44

PAPF-2Ol / H86

2.025

101.47

10.08

40.66

50.04

PAPF-1Ox / H86

2.0032.0342.0252.005Σ M2+

100.12100.47101.66100.29Total

9.749.8910.139.55FeO*

40.6940.0740.7440.81SiO2

49.0049.8250.1049.42MgO

Arm-3Ol / FF

Arm-1Ox / H86

PDROx / H66

Wet ChemOxide


Effect of Tilting and Particle Effects


Inconel Spheres: Diameter ~ 30 um


Inconel Sphere EDS Spectra: Effect of Takeoff Angle

Inconel Sphere 15kv

1

10

100

1000

10000

0 1 2 3 4 5 6 7 8 9 10

Energy, KeV

Cou

nts p

er 1

00 se

c

Top of SphereToward EDSAway from EDS

Al

C

NiCoTi CrMo

Cr, Ni L-lines


Inconel Sphere Low Energy EDS Region

Inconel Sphere 15kv

1

10

100

1000

0 0.5 1 1.5 2 2.5 3

Energy, KeV

Cou

nts p

er 1

00 se

c

Toward EDSTop of SphereAway from EDS

Al

C

Mo

Cr L Ni L


WinXray: EDS Spectra at 30, 40, 50 degree TOA

Calculated WinXray EDS Spectra NiCrAl System, 15 KV

1

10

100

1000

10000

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15Energy, KeV

Cou

nts

NiCrAl 50 deg

NiCrAl 40 deg

NiCrAl 30 deg


Al Kα Peak Intensity at -10º to +10º Tilt Relative to 40º

Calculated WinXray EDS Spectra NiCrAl System, 15 KV

0

500

1000

1.3 1.4 1.5 1.6 1.7 1.8Energy, KeV

Cou

nts

NiCrAl 50 deg

NiCrAl 40 deg

NiCrAl 30 deg


Calculated Tilt Effect on Al-Cr-Ni Alloy Composition

269.42

268.49267.31265.79

263.80

Ni KαIntensity

59.6838.15447.863.3381.1250

59.4738.01446.133.1677.044559.2137.82443.952.9672.214058.8737.58441.182.7366.5235

58.4337.28437.572.4559.8530

NiWt %

CrWt %

Cr KαIntensity

AlWt %

Al KαIntensity

TakeoffAngle

GMR Thin Film program: calculate emitted intensity at each takeoff angle.(We don’t want k-ratio relative to standard at each takeoff angle)X-ray intensity relative to 40 degree value used to scale weight %Al range 0.88 wt% / 20 degrees = 0.044 wt% per degree = 1.5% relative/deg.Cr range 0.88 wt%, = 0.12% relative/degreeNi range 1.25 wt%, = 0.063 wt% per degree = 0.11% relative/degreeConclusion: 10 degree tilt error results in percent level analytical errors

Nominal


Problem Systems


Problem Systems in EPMA:Analytical Elements in Problem Matrices

• Analytical Problems:• X-ray peak overlaps• High x-ray absorption• Spatial issues, inhomogeneity• Particle, thin film, etc.• ----• Perform proper measurement to obtain correct k-ratio• Use standard as close to sample for high correction analysis• Necessary to evaluate all correction algorithms and mass absorptioncoefficients – do not blindly accept one pairing as the best


WDS Background Selection (Natural Peak Width)And High Order WDS Interferences

• Example AlCrNi alloy used in Lehigh Microscopy School lab• WDS scan on pure Al necessary to establish full natural peak width• People choose backgrounds too close to peak

If background is not true on pure element, also not true on any sample• Cr Kb IV reflection observed at Al Ka peak position on TAP


WDS Scan LIF: Al, Cr, Ni and NiCrAl SampleNote background intensity as function of Z

1

10

100

1000

1000014

9

150

151

152

153

154

155

156

157

158

159

160

161

162

163

164

165

166

167

168

169

Spectrometer position, mm LIF

Cou

nts

Cr stdNiCrAlNi stdAl std

Cr Kα 1,2


WDS Scan LIF: Al, Cr, Ni, and NiCrAl SampleNote background intensity as function of Z

1

10

100

1000

1000010

5

106

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

123

124

125

Spectrometer position, mm LIFH

Cou

nts

Ni stdNiCrAlCr stdAl std

Ni Kα 1,2

Ni Kβ 1,3


WDS Scan TAP: Al, Cr, Ni, and NiCrAl SampleNote Cr Kβ IV-order interference on Al Kα, Full Al peak width

10

100

1000

10000

10000082 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 10

0

101

102

Spectrometer position, mm TAP

Cou

nts p

er se

c

Al stdNiCrAlCr stdNi std

Al Kα 1,2

Al KβSatellites

Al KαSatellites

Al Kβ 1

Cr Kα 1,2IV-order

Cr Kβ 3IV-order


Corning 95IRV, 95IRW, and 95IRXLIF 60 - 250 mm

100

1000

10000

100000

60 80 100 120 140 160 180 200 220 240Spectrometer Position, mm

Cou

nts

95IRV95IRW95IRX

Pb L

α Zn K

αCu

Kα

Ca K

α

Cs L

α

La L

α

Cr K

α

Mn

KαFe

Kα

Ti K

αBa

Lα

Ni K

αCo

Kα

Ca K

β

V Kα

Zn K

αΙΙ

Hf

Lα

Ce L

α

WDS Scan: LiF Crystal 95IRV Green, 95IRW Blue, 95IRX Red


Corning 95IRV, 95IRW, and 95IRXLIF 170 - 210 mm

0

250

500

750

1000

1250

1500

1750

2000

2250

2500

170 175 180 185 190 195 200 205 210Spectrometer Position, mm

Cou

nts

95IRV95IRW95IRX

Ni K

β II

Cs L

α

Zn K

α I

I

Zn K

β II

Ba L

β1 Ba L

α

Ti K

α

Xe A

bs L

II I

Cs L

β1La L

α

La L

β1V

Kα

Ti K

β

Ce L

α

Cs L

β3

WDS Scan: LiF Crystal95IRV Green, 95IRW Blue, 95IRX Red


Corning 95IRV, 95IRW, and 95IRXPET 70 - 90 mm

0

200

400

600

800

1000

1200

1400

1600

1800

2000

70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90

S pe c po s mm

Cou

nts

per s

ec

95IRV95IRW95IRX

Cr K

α 1

,2

V Kα

1,2

Ce L

α

La L

α

Ba L

α

Ti K

β

Ti K

α 1

,2Cs

Lβ1

Cs L

β4Cs

Lβ3

Ba L

β1Ba

Lβ4

La L

β1

Ba L

β2Ce L

β1

Ba L

γ

V Kβ

Ce L

β4Ce

Lβ3

La L

β4La

Lβ3

Ba L

β4Cs

Lβ2

Cs L

γ

Cs L

γ2

WDS Scan: PET Crystal95IRV Green, 95IRW Blue, 95 IRX Red


Co rning 95IRV, 95IRW, and 95IRXPET 227-240 mm

0

20

40

60

80

100

120

227 228 229 230 231 232 233 234 235 236 237 238 239 240 241

S pe c po s mm

Cou

nts

per s

ec

95IRV95IRW95IRX

Rb Lα

S i Kα1,2

Hf Mβ

K Kα1,2 II

Hf Mα ->

WDS Scan: PET CrystalSi Kα limb and Hf Mβ Overlap on Rb Lα


Corning 95IRV, 95IRW, and 95IRXPET 213-226 mm

0

50

100

150

200

250

300

350

400

213 214 215 216 217 218 219 220 221 222 223 224 225 226

S pe c po s mm

Cou

nts

per s

ec

95IRV95IRW95IRX

Sr Lα

Si Kβ

Ca Kα1,2 II

Si skβ

Si skα

Si Kα ->

<- Sr LβK Kβ R

b L β

4

WDS Scan: PET CrystalSr Lα Peaks, Rb Lβ family overlaps


Corning 95IRV, 95IRW, and 95IRXP-10 Flow counter -- PET 116-134 mm

0

100

200

300

400

500

600

116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134

S pe c po s mm

Cou

nts

per s

ec

95IRV95IRW95IRX

K Kα1,2

Th Mα

Th Mβ

U Mα

U Mβ

Th Mγ Ar Kabs edge

WDS Scan: PET CrystalTh Mβ on U Mα, K Kα Peaks & Ovlp U Mβ


Elevated and Uncertain MAC Values for K, L, M Lines:Proximity to Absorption Edge of Matrix Element

K-Lines and absorber for K, L, M edgeLi Be B

Be,S,YCB,Ar,Tc

NC,Ca,Ag

ON,V,Sn

FO,Mn,I

NeF,Co,La

NaNe,Zn,Nd

MgNa,Ge,Gd

AlMg,Se,Er

SiAl,Kr,Hf

PSi,Sr,Re

SP,Zr,Au

ClS,Mo,Pb

ArCl,Ru,Rn

KAr,Pd,Ac

CaK,Cd,U

ScCa,Sn

TiSc,Sb

VSc,Xe

CrTi,Ba

MnV,Ce

FeCr,Nd

CoMn,Sm

NiFe,Gd

CuCo,Dy

ZnNi,Er

GaCu,Lu

GeZn,Ta

AsGa,Re

SeGe,Ir

BrAs,Au

KrAs,Hg

RbSe,Pb

SrBr,Po

YKr,Rn

ZrRb,Ra

NbSr,Th

MoY,U

TcFr

Ru~Ac

L-Lines and absorber for K, L, M edgeTiN,Sc,In

VN,Ti,Sn

CrO,V,Sb

MnO,Cr,I

FeF,Mn,Xe

CoF,Fe,Ca

NiF,Co,La

CuNe,Ni,Ce

ZnNe,Cu,Nd

GaNa,Zn,Pm

GeNa,Ga,Eu

AsNa,Ge,Tb

SeMg,As,Dy

BrMg,Se,Er

KrAl,Br,Yb

RbAl,Kr,Lu

SrSi,Rb,Ta

YP,Rb,W

ZrSi,Sr,Os

NbP,Y,Ir

MoP,Zr,Au

TcP,Nb,Tl

RuS,Mo,Pb

RhS,Tc,Po

PdCl,Ru,At

AgCl,Ru,Rn

CdCl,Rh,Ra

InAr,Pd,Ac

SnAr,Ag,Pa

SbAr,Cd,U

TeK,In,Np

IK,Sn,Np

XeCa,Sn

CsCa,Sb,

BaCa,Te

HfCo,Dy

TaCo,Ho

WNi,Er

ReNi,Tm

OsNi,Tm

IrCu,Yb

PtCu,Lu

AuZn,Hf

HgZn,Ta

TlZn,W

PbGa,Re

BiGa,Re

PoGe,Os

AtGe,Ir

RnGe,Pt

FrAs,Au

RaAs,Hg

LaSc,I

CeSc,Xe

PrTi,Cs

NdTi,Cs

PmTi,Ba

SmV,La

EuV,Ce

GdCr,Pr

TbCr,Nd

DyCr,Pm

HoMn,Sm

ErMn,Sm

TmFe,Eu

YbFe,Gd

LuFe,Tb

AcAs,Hg

ThSe,Tl

PaSe,Pb

UBr,Bi

NpBr,Po

PuBr,At

M-Lines and absorber for K, L, M edgeHfAl,Br,Lu

TaAl,Kr,Lu

WAl,Kr,Hf

ReSi,Rb,Ta

OsSi,Rb,W

IrSi,Sr,Re

PtSi,Sr,Os

AuSi,Y,Ir

HgP,Y,Pt

TlP,Zr,Pt

PbP,Zr,Au

BiP,Nb,Hg

PoS,Nb,Tl

AtS,Mo,Pb

RnS,Mo,Pb

FrS,Tc,Po

RaCl,Tc,At

LaF,Co,Ba

CeNe,Ni,La

PrNe,Ni,Ce

NdNe,Cu,Pr

PmNe,Ni,Nd

SmNa,Zn,Pm

EuNa,Ga,Sm

GdNa,Ga,Eu

TbNa,Ge,Gd

DyNa,Ge,Tb

HoMg,As,Dy

ErMg,As,Ho

TmMg,Se,Er

YbMg,Se,Tm

LuAl,Br,Yb

AcCl,Ru,Rn

ThCl,Ru,Rn

PaCl,Rh,Fr

UCl,Rh,Ra


Example problem:Identification of IrxSiy unknown


Mass Absorption Coefficients for Si KαBy Absorber Z, All MAC Data Sets Compared

MAC for Si Ka by Z Absorber Elements

0

1000

2000

3000

4000

5000

6000

7000

0 10 20 30 40 50 60 70 80 90 100

Atomic Number Z

MA

C

CitzmuLinemuMcMasterMac30MacJTAFFAST


Comparison of Si Kα MACSRelative percent σ


0

5

10

15

20

25

30

35

40

45

50

0 10 20 30 40 50 60 70 80 90 100

Atomic Number Z

Perc

ent S

tand

ard

Dev

iatio

n, R

elat

ive


Silicon Kα MAC at L-edge of Absorber


0

1000

2000

3000

4000

5000

6000

7000

25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45

Atomic Number Z

MA

C


Mn Fe Co Ni Cu Zn Ga Ge As Se Br Kr Rb Sr Y Zr Nb Mo Tc Ru Rh


Silicon Kα MAC at M-edge of Absorber


0

1000

2000

3000

4000

5000

6000

7000

55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80

Atomic Number Z

MA

C


Cs Ba La Ce Pr Nd PmSm Eu Gd Tb Dy Ho Er Tm Yb Lu Hf Ta W Re Os Ir Pt Au Hg


Error Analysis Ta Lα in TaSi2All algorithms and MAC sets (PAPF-FFAST = 1.0)

Error Histogram Ta Lα in TaSi2Relative to PAP-FFAST Nominal K-ratios

0

2

4

6

8

10

12

14

0.95

0

0.95

5

0.96

0

0.96

5

0.97

0

0.97

5

0.98

0

0.98

5

0.99

0

0.99

5

1.00

0

1.00

5

1.01

0

1.01

5

1.02

0

1.02

5

Kcorr / Kexp

Freq

uenc

y Philibert-Duncumb-ReedZAF

Φ(ρz) Models

PAPF

-FFA

ST =

1.0


Error Histogram Si Kα in TaSi2Relative to PAP--FFAST Nominal K-ratio

0

1

2

3

4

5

6

7

8

0.79

0

0.86

0

0.93

0

1.00

0

1.07

0

1.14

0

1.21

0

1.28

0

1.35

0

1.42

0

1.49

0

1.56

0

1.63

0

1.70

0

1.77

0

1.84

0

Kexp / Kcorr

Freq

uenc

yError Analysis Si Kα in TaSi2All algorithms and MAC sets (PAPF-FFAST=1.0)

Phili

bert-

Dun

cum

b-R

eed

ZAF

Φ(ρz) ModelsM

cMas

ter

Line

mu

Mac

30

citz

mu

Φ(ρz) Models

Phili

bert-

Dun

cum

b-R

eed

ZAF

PAPF

-FFA

ST =

1.0

Dramatic demonstration of choice of MAC data set:Variation of Φ(ρz) models and 4 mac data sets


Calculated Compositions of TaSi2Relative to PAP—FFAST Nominal K-ratios

102.8176.8525.96MM

101.3976.5224.87LM

10076.3123.69(FFAST)

89.6674.0215.64M30

88.4873.7414.74CM

TotalWt% TaWt% SiPAPFwith MAC


Conclusions

• Geological applications require multicomponent accuracy evaluation• Use of Kmeas/Kcalc plot used for data analysis, WDS and EDS• CMASTF standards provide instrument calibration data set• Experimental K-ratio data set available for development and testing• Identification of inconsistent compositions• Accuracy of analysis in CMASTF system better than 2%, precision limited• SDD quantitative analysis data highly competitive with WDS• Excellent prospects for high speed SDD quantitative analysis in particle,mapping applications

Date post:	17-Oct-2020
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