Summer 2001: Arrival of new accelerator, courtesy of CFI and other partners

1
Summer 2001 Arrival of new accelerator, courtesy
of CFI and other partners
Its main job is to provide a 3 MeV proton beam
for PIXE activities
2
Thanks to

• B. Teesdale, J.Maxwell, Z,Nejedly, T.Hopman,
  T.Papp, B. Morton, T.Riddolls, C. Gielen, D.
  Urbshas (accelerator installation)
• R. Protz (LRS, deceased) H. Jamieson (Queens)
• G. Grime (Oxford) A.Denker (Berlin)
• L.Cabri, B.Kjaarsgard (Nat. Resources Canada)
• N.Halden (U.Manitoba)
• J.Babaluk, J.Reist, A.Kristofferson (DFO/Arctic)
• R. Eldred, G.Czamanske (California)
• R.Hoff, J.Brook, R.Vet, M.Shepherd (Environment
  Canada)

3
Origins of PIXE and micro-PIXE

• 1970 Johansson et al at Lund urban air
  particulate collected on carbon foil can
  analyze sub-mg samples at ppm limits using
  proton-induced X-rays.
• Ionization cross-sections poorly known PIXE
  analysis needs standards or better physics
• 1972 Cookson (UK) first micron-diameter proton
  beam permits micro-PIXE
• 1989 GUPIX program launched from Guelph

4
Our timeline
Experiments on atomic inner-shell
processes Dabbling in PIXE as a curiosity with
potential
1970s
Develop PIXE as a quantitative technique Refine
the atomic physics database Start GUPIX
Start a proton microprobe
1980s
Consolidate micro-PIXE and identify new
applications GUPIX widely used 90 groups
feedback identifies physics needs extensive
development
1990s
2000
Create national facility for environmental
analysis
5
Electron microprobe
Proton microprobe
Synchrotron radiation microprobe
6
Niches

• PIXE can handle small samples (100 µg) e.g.
  PM2.5 air particulate (component of smog health
  issue)
• Can focus to micron-size spot analyze mineral
  grains in situ
• Can bring beam into the air handle large or
  delicate objects archaeometry and art,
  manuscripts (eg Galileo, Vinland map)
• ppm detection limits in point analysis
• Trace element imaging in mineral grains, fly ash
  particles, otoliths, etc

7
Small-scale niche
Recent contributions to mineralogy of the
Norilsk sulfide deposit in Siberia looking at
PGE-rich ores distribution of Pd, Rh and Ru
among pyrrhotite, pentlandite etc.
Objectives of such work Economics and technology
of recovery and processing Test genetic models
involving differentiation of mantle
sulfide-silicate melts
8
Large-scale niche
Egyptian artefact undergoing 68 MeV PIXE analysis
at Institut Hahn-Meitner in Berlin
9
Guelph proton probe
10
Thin-window detector for 1-6 keV X-rays of light,
major elements
Trace element Si(Li) looks thru absorber foil
that suppresses bremsstrahlung
Focussing quadrupole doublet
X300 optical microscope
11
GUPIX The Guelph PIXE Software Package

• Provides manipulation of the database
• Fits the spectra in single and batch modes ( a
  few seconds per spectrum)
• Converts peak intensities to concentrations by
  the Guelph H-value method
• Provides concentrations, two error estimates,
  detection limits, Y/N/? outcomes, depth probed,
  etc detailed individual output files plus four
  project spreadsheets

12
ION-SOLID PHYSICS 1

• Characteristic X-ray yield is
• Y(Z) Y1(Z) Q ? CZ transZ effZ
• Y1(Z) is COMPUTED yield per unit charge, unit
  solid angle, unit concentration needs a lot of
  atomic physics information
• Q is charge or charge equivalent
• CZ is concentration
• ? is detector solid angle

13
ION-SOLID PHYSICS 2

• Ef
• Y1(Z) ? ?Z(E) TZ(E) / SM(E)dE
• E0
• where
• E
• TZ(E) exp -(?/?) G(?) ? dE / SM(E)
• E0
  
• Integration is over proton range of a few tens of
  microns

14
ION-SOLID PHYSICS 3

• In addition there is secondary fluorescence
• And in a multiple-layer target, X-rays from 1
  layer may fluoresce elements in a different
  layer need tabulation of photo-electric
  cross-sections

15
SPECTRUM FITTING 1

• Non-linear least squares approach
• Model spectrum takes library of relative X-ray
  line intensities and modifies them for
• - relative absorption in target
• relative detector efficiency
• transmission through absorbers inserted to reduce
  bremsstrahlung and low energy X-rays (electron
  probes use no absorbers work entirely at low
  energy)

16
SPECTRUM FITTING 2

• Fitting can not be divorced from major element
  concentrations which may not be known!
• Fitting depends upon detector and absorber
  description demands a characterization exercise
  that has no counterpart in RBS or ERD PIXE is
  more demanding in this regard
• The following are important issues but are
  ignored today
• continuum background
• Detector resolution function ie peak shape

17
Example of trace element fit
18
CONCENTRATIONS?STANDARDIZATION BY THE GUELPH
H-VALUE METHOD

• Y(Z) Y1(Z) Q H CZ transZ effZ
• H is effectively the solid angle
• H should be a constant PROVIDED
• (a) the database is accurate
• (b) the detector is well-characterized
• (c ) beam charge is properly integrated
• Look at single-element H values for 3 MeV protons

19
H-values measured for K X-rays (squares) and L
X-rays (triangles)
20
STANDARDIZATION BY H-VALUE 2

• Now we need a quick method to determine H daily
• Y(Z) Y1(Z) Q H CZ transZ effZ
• This is a compromise between
• a fundamental parameters approach (all physics,
  no standards analytical chemists do not like
  this) and
• total reliance on standards (necessitates far too
  much chemistry)
• H must be determined with standard reference
  materials or SRMs, but these need not be of
  identical matrix to the specimens

21
Our H-determination Method with NIST alloys

• Use a homogeneous reference material with a high
  energy X-ray and a low-energy X-ray
• Example Mo and Fe in a NIST Mo-steel standard
• Mo Ka provides the H value, only slightly
  affected by absorber thickness
• With that H value fixed, Fe Ka determines the
  absorber thickness (typically 100-500 µm)
• Iterate back to the H value using Mo

22
PIXE spectra of NIST alloy standards
23
H-values from alloys
24
Quality assurance/Quality control

• Quality assurance (QA) Run SRMs and participate
  in intercomparisons
• BCR air filters 2nd most accurate of 14 labs
  in IAEA inter-comparison
• NIST glasses
• Geochemical standards eg BHVO1 and 30 others
• Quality Control Run micromatter films or NIST
  steels every day prior to analysis

25
Ni in geochemical SRMs
Relevant to Ni-in-garnet geothermometer used to
identify potentially diamondiferous kimberlites
26
PIXE data for air quality across US-Canada
border Guelph versus Univ. California at Davis
27
Is the basic atomic physics well enough known?

• What about the ionization cross-sections?
• GUPIX uses ECPSSR of Brandt with DHS wave
  functions (Chen and Crasemann)
• We also have reference cross-sections created
  from the entire literature data by Paul (K) and
  by Orlic (L), using statistical selection
  processes
• Measure H using each of these sets

28
H-values for K X-rays (squares) and L X-rays
(triangles)
ECPSSR theory OK for K shell but has problems in
L shells AND What is wrong with the reference
cross-sections?
29
Thorium L X-ray spectraVoigtians versus
Gaussians (with tailing)
Papp and Campbell 1996 Nucl. Instr. Meth. B114,
225
30
L2 and L3 natural level widths
Campbell and Papp 2001. ADNDT 77,1
31
Natural width of M3 level
Campbell and Papp 2001. ADNDT 77,1
32

• The independent-particle model (IPM) heavily
  over-estimates atomic level widths in situations
  (L1, M1, M2, M3, N1 N6) where 2-vacancy final
  states are involved therefore X-ray widths are
  poorly known causes fitting errors serious
  for L1
• As a result, Coster-Kronig probabilities for
  vacancy rearrangement are badly predicted
  induces error in working back from measured L
  spectra to L sub-shell cross-sections
• May explain part of L cross-section problem
• Also introduces error into fitting PIXE spectra

33
Critically selected best values of vacancy
transfer probability f13 c/f with IPM theory
Campbell, to appear in ADNDT 2003
34
Earth, air, fire and water Some applications of
micro-PIXE at Guelph

• Mineral grains precious metals impact of mine
  tailings on environment
• Mineral grain boundaries percolation (fire)
• Imaging in contaminated soil (earth)
• Metals dispersal in and settling from smelter and
  power plant plumes (TSRI) (air)
• Fish otoliths anadromy stock identification
  fisheries management (water!)

35
Mineral grains in a sulfide rock courtesy of
L.J. Cabri
36
Halden et al 1993. Can. Mineralogist 33,
961. Linescans to study a lozenge-shaped titanite
grain in a radiation-damaged rock
37
LS1 shows Mn, Zn, Y, Pb, U on edges of the grain
38
LS2 shows Mn, Fe, Zn, Sr, Y, Nd, Pb, Th, U in
cracks in surrounding material
39
Tomlin et al 1993. Geoderma 57, 89. Artistic
portrayal of a soil block
40
View down vertical worm tunnel in
methacryalate-fixed soil Note fecal material on
burrow edge
41
PIXE spectra far from burrow (above) and near the
burrow (below) note heavy deposit of metals at
sides of burrow they are carried in fecal
material deposited by the worm
42
2-D images of soil section
43
DFO collaborators collect fish in Canadian Arctic
(courtesy of DFO)
44
Lake Hazen on Ellesmere Island
45
Arctic char
46
Char otolith (residual earbone)
47
1-inch probe mount with 7 otoliths aligned
48
Note the intense strontium peaks in PIXE spectra
of otoliths
49
(No Transcript)
50
This slide and following three Babaluk et al
1997. Arctic 50, 224
Linescans of known non-anadromous arctic char
from Lake 104 and Capron Lake
51
Known anadromous charr from Halovik River, Jayco
River, Paliryuak River, Ekalluk River
52
Conclude Small morphotype from Lake Hazen is
anadromous
53
Surprise large morphotype from Lake Hazen is NOT
anadromous
54
STOCK IDENTIFICATION ISSUE In a mixed summer
fishery at sea, can we identify stock or
sub-species being exploited?
55
(No Transcript)
56

57
Otolith of a young-of-year Dolly Varden char
under oil-immersion objective PIXE-imaged at
OXFORD and at GUELPH
58
Guelph Linescan results
Central Sr peak is maternally-derived outer Sr
signal reflects environment
59
Mean Sr from point analyses in outer lobes
Fish Sr ppm Sr ppm
Left Right
Vittrewka 43989 445 15 518 53
Vittrewka 43984 372 39 425 26
Cache BF5 681 162 650 64
Cache BF6 1004 98 1001 66
60
Sr from 50 micron rasters of outer lobes
Fish Sr ppm Sr ppm Sr ppm Sr ppm Sr ppm
L Dorsal L ventral R Dorsal R Ventral Mean
V9 423 7 406 7 444 7 428 7 425 13
V4 404 7 390 7 423 7 405 7 406 12
C BF5 652 9 607 8 610 8 579 8 612 26
C BF6 965 11 997 11 998 11 1041 17 1003 27
Technique now shows promise for stock
identification
61
Last remarks

• PIXE and micro-PIXE are well-established methods
  for trace analysis and imaging, but exist at only
  a few labs in any country
• They occupy special niches where they are
  accurate and versatile
• Environmental science is well served
• We get to meet interesting collaborators!
• Experimental and theoretical work is needed to
  refine the atomic physics database because
  neither the IPM nor the experimental data are
  quite good enough