Trace metal analysis in carbonates using the
Cameca NanoSIMS
John Eiler
Sharp Professor of Geology and Geochemistry
Director, Caltech Microanalysis Center
California Institute of Technology
With contributions from
Jess Adkins, Anne Dekas, Rinat Gabitov, Alex Gagnon,
Amy Hofmann and Katie Snell
Wisc SIMS Paleoclimate Workshop
June 25th, 2013
Cation-exchange paleothermometry
CaCO3 + Mgaq = MgCO3 + Caaq
Keq ∞
Ca
x[ ]
[Mg
]
Ca
Mg
Mitsuguchi et al., 1996
min
fluid
Global budgets
Weathering
Sediments
Stanley and Hardie, 1998; model of Hardie, 1996
Hydrothermal
Alteration
Hitch #1: Vital effects
Foraminifera
Eggins et al., 2004;
Deep-sea coral
Gagnon et al., 2007
Hitch #2: Diagenesis
PA: Primary Aragonite; SA: Secondary Aragonite; SC: Secondary Calcite
Cements vs. ‘Primary’
Allison et al., 2007
The Cameca NanoSIMS
What puts the ‘nano’ in nanoSIMS
Geometry of focusing and extraction lenses
• Short working distance promotes small, dense probe
• Extraction optics easily contaminated or damaged
Minimum spot size
Si metal in Al matrix
<<1 pA Cs+; ca. 30 nm resolution
Illustration of the ‘84/16 %’ definition
1 µm
• Nominally 50 nm for Cs+, 150 nm for O- (‘84/16 %’ definition)
• Actual minimum ca. 20 nm for Cs+, ca. 100 nm for O• Brighter beams needed for trace element mapping typically in 100-300 nm range
• Actually tricky to measure in many samples; assume it is ~500 nm unless proven otherwise
Connection between beam current and resolution
TiCN; Cs+ primary beam
2 pA; 93 nm resolution
1 µm
TiCN; Cs+ primary beam
<<1 pA; 22 nm resolution
1 µm
• Images sharpen by minimizing beam current and carefully tuning primary beam
• Count rates decrease and errors increase in proportion to beam current
Even carefully tuned images ‘broaden’ features you can see clearly by SEM
Sub-micron rutile inclusion in zircon
Work of Amy Hoffman
The analyzer and detector array of the nanoSIMS are also distinctive
High-dispersion multi-collection
Fixed collector
Minimum mass spacing—1:58
Maximum mass spacing —22:1
• Conceived of as a tool for elemental mapping with exact spatial correlation of
measured species
• Also enables true multi-collection of almost any element/element ratio
Transmission and mass-resolving power
Relative sensitivity (%)
100
10
1
0
5000
10000
15000
20000
25000
30000
Mass resolving power
Absolute sensitivity comparison
Data from CIT nanoSIMS 50L; image from Frank Stadermann
Design purpose: Composition mapping at µm scale
Organic matter in 0.85 Ga Bitter Springs fm. Chert; Oehler et al., 2006
• Field of view: 200x200 µm in principle; 20x20 in practice. 10x10 or 5x5 is ideal
• Discretization: 64x64 to 1024x1024; typically set so 1 pixel ~ beam radius
Design purpose: Composition mapping at µm scale
Science, 2006
• Fundamental data of interest is presence/absence
of signal and spatial associations. Quantification is
a secondary issue
• Most imaging artifacts are of secondary importance
and cannot be seen in scaled images
Three dimensional ion imaging
3
% 15N
5
Interior
Edge
Work of Anne Dekas
Common tuning conditions for ‘spot’ analyses result in horrendous
imaging artifacts
Zr/Si ratio of zircon
0.2
94Zr/28Si
0.1
10
20
Distance (µm)
• Clearly unacceptable for even semi-quantitative ion imaging
• Must be corrected by tuning the primary beam octapole (‘stigmator’) and various
immersion lens electrodes
Work of Amy Hofmann
Even after careful tuning for ‘flatness’, edge effects are
generally still present
After tuning for ‘flatness’
0.2
94Zr/28Si
Before tuning for ‘flatness’
0.1
10
20
Distance (µm)
• Improves by pre-sputtering large area and keeping image ≤ 10 µm
• No recognized solution, other than ‘gating’ or culling data
• May be obscured by saturation of images
• Community should insist on demonstrations that stoichiometric ratios yield
roughly ‘flat’ images in domains of interest
Work of Amy Hofmann
The accuracy of ‘good’ images
40Ca
ion intensity image of Oka carbonatite
42Ca/40Ca
Cps
88Sr/40Ca
Image ‘Spots’
6.44E-3 6.52E-3
2.42E-4
2.78E-4
~ several % artifacts in average element and isotope abundance ratios are common
Work of Alex Gagnon
The accuracy of ‘good’ images
Integrals of 20x20 µm ion images of carbonate standards and samples
Oka
carbonatite
1.2
88Sr+
42Ca+
0.8
0.4
BCC
carbonatite
standard
Coral
5
10
15
Sr/Ca
(mmol/mol)
• Images can provide quantitative data at ~% level accuracy with effort, but the
community should insist that this accuracy is tested and demonstrated on a caseby-case basis
Work of Alex Gagnon
Where do spot measurements by nanoSIMS fit into our stable
of tools for element/element ratio analysis?
1 ppm
100 ppm
1%
Precision (1 s.e.)
10 %
1%
0.1 %
0.01 %
1nm
1µm
Spatial resolution (m)
1mm
10-7
10-5
10-3
Concentration
E-probe
ATEM
LA-ICPMS, conv. SIMS
Bulk (e.g., solution ICP)
M. Baker, pers. com; Cavosie et al., 2006; Klemme et al., 2008; Sobolev and Hofmann 2007; Hart and Cohen, 1997
10-1
‘Spot’ analyses of element/element ratios in carbonates
Internal errors
Various nominally homogeneous calcite standards; O- beam; 1-2 µm spots
Nano-SIMS 50L
0
-0.5
24_42
of ppm)
88
88_42
Sr/42Ca (1000’s of ppm)
138_42
138
Ba/42Ca (~1-10 ppm)
Count. Stat.
24Mg/42Ca (100’s
(1 error)
Log
log(2sigma/mean)
10 %
-1
-1.5
1%
-2
-2.5
1
22
Log
Ni.Nj
33
44
55
log[NX*N42/(NX+N42)]
X ~ Ni for trace species
6
7
1 m
=
Ni + N j
(X0.5/X = external error for ratio [I]/[j])
Follows counting statistics down to ~3 ‰ 1.s.e. error, across a wide range in concentration
Work of Rinat Gabitov
There are limits imposed by drift in ratios during long sputtering
Nano-SIMS
(five
single acquisitions)
Oka Carbonatite;
analyzed50L
on the
NanoSIMS
with a 2 µm rastered spot of O-
log(2sigma/mean)
Internal error (1
0
-0.5
10 %
-1
88Sr/
42Ca
88/42
-1.5
Count.Stat.
1%
-2
-2.5
1
22
33
Log
Ni.Nj
44
55
66
7
7
~ Log (Ni) for trace species
Ni +log[NX*N42/(NX+N42)]
Nj
(X0.5/X = external error for ratio [I]/[j])
• Reflects gradual ‘drift’ in intensity and ratios after reaching nominal steady-state sputtering
• Not sufficiently reproducible to correct completely by matching drift with standards
• Appears to limit precision to no better than ~0.15 % 1 s.e., relative
Work of Rinat Gabitov
Point-to-point reproducibility
log (rel. external stdev multiple spots)
Point-to-point reproducibility
(1)
0
-0.5
10 %-1
24Mg/42Ca
24/42
88Sr/42Ca
88/42
138/4242
138
-1.5
Ba/ Ca
1 %-2
-2.5
-2.5
-2
-1.5
-1
-0.5
1
%
10
%
log (rel. mean internal er multiple spots)
0
Average internal error
(1 s.e.)
• Tracks counting statistics errors down to ~0.3-1.0 %, 1 s.e.
• Likely only applies to central half of 1” rounds and central 3/4 of 1 cm rounds
• Illustrated data didn’t require heroic efforts at polishing, but normal caution
regarding topography effects is appropriate
Slopes of calibration curves vary session-to-session much more
than for other SIMS instruments
• This could reflect fractionations associated with changing the acceptance angle
when the immersion lens stack is tuned
• Session-to-session reproducibility for secondary standards (i.e., assuming given
value for a primary standard) follows internal errors down to ~0.8 % 1 s.e..
Many of the carbonate standards available
for trace element measurements by SIMS are crap
ID-ICPMS data for sub-samples
AG-1, NBS-19, 135-CC,
HUJ-AR & UCI-CC also
examined
• Oka is poor overall, but its calcite matrix has the best long-term reproducibility (±0.8 %)
• BlueCC is a close second, and lacks ‘nuggets’ of exotic carbonates
• All of the 7 other commonly used standards we explored are much worse
• 1 %-level accuracy requires independent analysis of the same crystal
Where do spot measurements by nanoSIMS fit into our stable
of tools for element/element ratio analysis?
1nm
1µm
1mm
1 ppm
100 ppm
1%
Precision (1 s.e.)
10 %
1%
NanoSIMS
0.1 %
0.01 %
10-9 10-8 10-7 10-6 10-5 10-4 10-3
10-7
10-5
10-3
Concentration
Spatial resolution (m)
E-probe
ATEM
LA-ICPMS, conv. SIMS
nanoSIMS
Bulk (e.g., solution ICP)
10-1
Semi-quantitative imaging of growth banding in biogenic carbonates
Foraminifera
Kunioka, 2006
Surface coral Mg/Ca
Meibom et al., 2004
Intergrown CaCO3 and Ca0.55Mg0.45CO3 in a sea urchin’s tooth!
5x5 µm ion image
Ma et al., 2009
Extended example of applied use as a quantitative tool
Experimental studies of vital effects
1.
2.
43Ca
• Calcein marks start of growth during experiment; later layers should carry ‘spikes’
• The sub-micron resolution of the NanoSIMS reduces culture time from several months to
a few days
Gagnon et al. 2013
Ion images of overgrowths
Calcein stain
43Ca/42Ca
Demonstrations of image ‘flatness’
Gagnon et al., 2012
A conceptual model of coral biomineralization
(after McConnaughey)
(extracellular
calcifying fluid)
Well-resolved gradients should measure
residence time in ECF ‘mother liquor’
Budget for a metal in ECF
[Ca]SW
Flow out
[Ca]
Flow in
P
Precipitation
External solution
Spike
Precipitated carbonate
Instantaneous
2 hrs
Natural
Time
Gagnon et al., 2012
Growth Axis
Measured growth rates are generally faster than can
be resolved by beam width
Model of a sharp boundary,
given beam ‘broadening’
Calcium turnover time (1/2) is less than 2 hrs, possibly much faster
Fastest growing measured foram 1/2 = 1.2 hrs
Comparison of profiles should provide evidence
for mechanisms of uptake
Mg2+
Ca2+
Growth Axis
Growth Axis
Delivery of metals to site of growth appears to be dominated by
transport of seawater to growing crystal surface
Uptake of 25Mg and 43Ca spikes
specific pumping
Growth Axis
seawater transport
Growth Axis
This conclusion is corroborated by uptake of spikes that are unlikely
to be biologically ‘pumped’ across membranes
Gagnon et al., 2012
43Ca
spike
159Tb
spike
Extracting quantitative partition coefficients from
ion images of ~µm overgrowths
Corals grown over a range of carbonate-ion concentrations
Gagnon et al., 2013
Related work has demonstrated that growth zonation is controlled by
variable extents of Rayleigh distillation on carbonate growth from ECF
Flow in
ECF
Flow out
Keqarag-fluid
Precipitation
Septa of deep-sea corals; Gagnon et al., 2007
Surface corals; Gaetani et al., 2011
This advance creates the possibility that models of vital effects
will be quantitative tools of paleoclimate reconstructions
Flow in
Flow out
ECF
Keqarag-fluid
Precipitation
Fit to Rayleigh distillation model
Gaetani et al., 2011
Thermometry using implied Kd
controlling the distillation fractionation
Using the NanoSIMS to unravel the thorny problem of
diagenetic modifications
Fossil 34-91; a Paleocene mollusk from the Bighorn Basin
Modified aragonite
growth plates
Mix of secondary
calcite and entombed
growth plates
Work of Katie Snell
Using the NanoSIMS to unravel the thorny problem of
diagenetic modifications
Fossil 34-91; a Paleocene mollusk from the Bighorn Basin
55Mn16O/40Ca16O
Work of Katie Snell
Summary and parting thoughts
• NanoSIMS may be uniquely suited to quantitative trace element analysis of
carbonates with µm to sub-µm zonation (synchrotron µ-XRF may be comparable)
• Imaging can yield several-per cent errors at scales down to 300 nm; much better
is likely unrealistic
• 0.8-1 % (1 s.e.) long-term external precision for ~1 µm domains are demonstrated
and half that seems possible
• Real limitation at present is poor quality of interlaboratory standards
• Relatively casual standardization could easily result in ~10 % errors
• There is no established community-wide practice for achieving and documenting
precision and accuracy; for the time being, this needs to be approached as an
experimental tool, and data in the literature should be approached with a
‘show me!’ attitude.