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Trace metal analysis in carbonates using the Cameca NanoSIMS John Eiler Sharp Professor of Geology and Geochemistry Director, Caltech Microanalysis Center.

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Presentation on theme: "Trace metal analysis in carbonates using the Cameca NanoSIMS John Eiler Sharp Professor of Geology and Geochemistry Director, Caltech Microanalysis Center."— Presentation transcript:

1 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 25 th, 2013

2 Mitsuguchi et al., 1996 CaCO 3 + Mg aq = MgCO 3 + Ca aq K eq ∞ Mg Ca Mg [ ] min [ ] fluid x Cation-exchange paleothermometry

3 Stanley and Hardie, 1998; model of Hardie, 1996 Global budgets Weathering Hydrothermal Sediments Alteration

4 Eggins et al., 2004; Hitch #1: Vital effects Gagnon et al., 2007 Foraminifera Deep-sea coral

5 Allison et al., 2007 Hitch #2: Diagenesis PA: Primary Aragonite; SA: Secondary Aragonite; SC: Secondary Calcite Cements vs. ‘Primary’

6 The Cameca NanoSIMS

7 Geometry of focusing and extraction lenses What puts the ‘nano’ in nanoSIMS Short working distance promotes small, dense probe Extraction optics easily contaminated or damaged

8 Minimum spot size 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 nm range Actually tricky to measure in many samples; assume it is ~500 nm unless proven otherwise 1 µm Si metal in Al matrix <<1 pA Cs+; ca. 30 nm resolution Illustration of the ‘84/16 %’ definition

9 Connection between beam current and resolution Images sharpen by minimizing beam current and carefully tuning primary beam Count rates decrease and errors increase in proportion to beam current TiCN; Cs+ primary beam 2 pA; 93 nm resolution TiCN; Cs+ primary beam <<1 pA; 22 nm resolution 1 µm

10 Work of Amy Hoffman Even carefully tuned images ‘broaden’ features you can see clearly by SEM Sub-micron rutile inclusion in zircon

11 High-dispersion multi-collection The analyzer and detector array of the nanoSIMS are also distinctive 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 Fixed collector Six mobile collectors

12 Transmission and mass-resolving power Data from CIT nanoSIMS 50L; image from Frank Stadermann Relative sensitivity (%) Mass resolving power Absolute sensitivity comparison

13 Design purpose: Composition mapping at µm scale 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 Organic matter in 0.85 Ga Bitter Springs fm. Chert; Oehler et al., 2006

14 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 Design purpose: Composition mapping at µm scale

15 Work of Anne Dekas Interior Edge 3 5 % 15 N Three dimensional ion imaging

16 Clearly unacceptable for even semi-quantitative ion imaging Must be corrected by tuning the primary beam octapole (‘stigmator’) and various immersion lens electrodes Zr/ 28 Si Distance (µm) Zr/Si ratio of zircon Work of Amy Hofmann Common tuning conditions for ‘spot’ analyses result in horrendous imaging artifacts

17 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 Zr/ 28 Si Distance (µm) After tuning for ‘flatness’ Before tuning for ‘flatness’ Work of Amy Hofmann Even after careful tuning for ‘flatness’, edge effects are generally still present

18 40 Ca ion intensity image of Oka carbonatite Cps Image‘Spots’ 42 Ca/ 40 Ca 88 Sr/ 40 Ca 6.44E-36.52E E-42.78E-4 ~ several % artifacts in average element and isotope abundance ratios are common The accuracy of ‘good’ images Work of Alex Gagnon

19 51015 Sr/Ca (mmol/mol) Sr + 42 Ca + Integrals of 20x20 µm ion images of carbonate standards and samples Oka carbonatite BCC carbonatite standard Coral The accuracy of ‘good’ images Images can provide quantitative data at ~% level accuracy with effort, but the community should insist that this accuracy is tested and demonstrated on a case- by-case basis

20 Where do spot measurements by nanoSIMS fit into our stable of tools for element/element ratio analysis? Precision (1 s.e.) Spatial resolution (m)Concentration 1nm 1µm 1mm % 1 % 0.1 % 0.01 % 1 % 100 ppm 1 ppm 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

21 Log N i. N j N i + N j (X 0.5 /X = external error for ratio [I]/[j]) X = ~ N i for trace species % 10 % Log (1  error) Follows counting statistics down to ~3 ‰ 1.s.e. error, across a wide range in concentration ‘Spot’ analyses of element/element ratios in carbonates Internal errors Various nominally homogeneous calcite standards; O - beam; 1-2 µm spots Work of Rinat Gabitov 138 Ba/ 42 Ca (~1-10 ppm) 88 Sr/ 42 Ca (1000’s of ppm) 24 Mg/ 42 Ca (100’s of ppm) 1  m

22 Log N i. N j N i + N j (X 0.5 /X = external error for ratio [I]/[j]) ~ Log (N i ) for trace species % 10 % 88 Sr/ 42 Ca There are limits imposed by drift in ratios during long sputtering 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 Internal error (1  Oka Carbonatite; analyzed on the NanoSIMS with a 2 µm rastered spot of O - Work of Rinat Gabitov

23 Point-to-point reproducibility Tracks counting statistics errors down to ~ %, 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 10 %1 % 10 % 1 % Point-to-point reproducibility (1  ) Average internal error (1  s.e.) 138 Ba/ 42 Ca 88 Sr/ 42 Ca 24 Mg/ 42 Ca

24 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..

25 Many of the carbonate standards available for trace element measurements by SIMS are crap ID-ICPMS data for sub-samples 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 AG-1, NBS-19, 135-CC, HUJ-AR & UCI-CC also examined

26 Precision (1 s.e.) Spatial resolution (m) Concentration 1nm 1µm 1mm % 1 % 0.1 % 0.01 % 1 % 100 ppm 1 ppm E-probe ATEM LA-ICPMS, conv. SIMS nanoSIMS Bulk (e.g., solution ICP) NanoSIMS Where do spot measurements by nanoSIMS fit into our stable of tools for element/element ratio analysis? NanoSIMS

27 Kunioka, 2006 Semi-quantitative imaging of growth banding in biogenic carbonates Meibom et al., 2004 Foraminifera Surface coral Mg/Ca

28 Ma et al., 2009 Intergrown CaCO 3 and Ca 0.55 Mg 0.45 CO 3 in a sea urchin’s tooth! 5x5 µm ion image

29 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 Ca Gagnon et al Extended example of applied use as a quantitative tool Experimental studies of vital effects

30 Ion images of overgrowths Calcein stain 43 Ca/ 42 Ca Demonstrations of image ‘flatness’ Gagnon et al., 2012

31 A conceptual model of coral biomineralization (after McConnaughey) (extracellular calcifying fluid)

32 Time [Ca] SW [Ca] P 2 hrs Instantaneous Growth Axis 43 Ca 25 Mg Flow in Flow out Precipitation Budget for a metal in ECF External solutionPrecipitated carbonate Natural Spike Well-resolved gradients should measure residence time in ECF ‘mother liquor’ Gagnon et al., 2012

33 Calcium turnover time (  1/2 ) is less than 2 hrs, possibly much faster Fastest growing measured foram  1/2 = 1.2 hrs Measured growth rates are generally faster than can be resolved by beam width Model of a sharp boundary, given beam ‘broadening’

34 Growth Axis Ca 2+ Mg 2+ Comparison of profiles should provide evidence for mechanisms of uptake

35 specific pumping seawater transport Growth Axis Uptake of 25 Mg and 43 Ca spikes Delivery of metals to site of growth appears to be dominated by transport of seawater to growing crystal surface

36 Gagnon et al., 2012 This conclusion is corroborated by uptake of spikes that are unlikely to be biologically ‘pumped’ across membranes 43 Ca spike 159 Tb spike

37 Gagnon et al., 2013 Extracting quantitative partition coefficients from ion images of ~µm overgrowths Corals grown over a range of carbonate-ion concentrations

38 Septa of deep-sea corals; Gagnon et al., 2007Surface corals; Gaetani et al., 2011 ECF Flow in Flow out Precipitation Related work has demonstrated that growth zonation is controlled by variable extents of Rayleigh distillation on carbonate growth from ECF K eq arag-fluid

39 Gaetani et al., 2011 Fit to Rayleigh distillation model Thermometry using implied K d controlling the distillation fractionation ECF Flow in Flow out Precipitation This advance creates the possibility that models of vital effects will be quantitative tools of paleoclimate reconstructions K eq arag-fluid

40 Fossil 34-91; a Paleocene mollusk from the Bighorn Basin Work of Katie Snell Using the NanoSIMS to unravel the thorny problem of diagenetic modifications Modified aragonite growth plates Mix of secondary calcite and entombed growth plates

41 Fossil 34-91; a Paleocene mollusk from the Bighorn Basin 55 Mn 16 O/ 40 Ca 16 O Work of Katie Snell Using the NanoSIMS to unravel the thorny problem of diagenetic modifications

42 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 % (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.


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