Auger Spectroscopy
of better than 100 nm and multi-collection capability ( Figure 1a ). Samples are sputtered with a ~1 pA primary Cs + focused ion beam that is rastered over an area of interest, typically 10 × 10 µm in size, in the fi ne-grained matrix of a primitive meteorite ( Figure 2 ) to
look for isotopically anomalous oxygen signatures. Secondary ions of the three oxygen isotopes ( 16 O – , 17 O – , 18 O – ) are collected simultaneously at a mass-resolving power (M/M > 5000) suffi cient to separate the 17 O peak from the adjacent 16 OH peak. T e ion images are then processed offl ine to produce oxygen isotope ratio images ( Figure 3 ). Compared to the surrounding isotopically normal matrix material, the presolar grains exhibit
unusual isotopic compositions, such as anomalously high 17 O/ 16 O ratios.
Figure 2 : Secondary electron image, taken with the Auger Nanoprobe, of the fi ne-grained matrix from a thin section of the Queen Alexandra Range 99177 meteorite. The bright squares are areas measured with the NanoSIMS, where the carbon coat has been sputtered away. Each square measures 10 × 10 µm. Field of view = 200 µm.
Figure 3 : False color NanoSIMS raster ion images, showing signal intensities (violet = low, green = medium, red = high)
for the three isotopes of oxygen: (a) 16 O – , (b) 17 O – , and (c) 18 O – ; and the ratios of those images: (d) 17 O – / 16 O – and (e) 18 O – / 16 O – . The red circle highlights a presolar grain from the Adelaide carbonaceous chondrite that is enriched in 17 O
relative to 16 O and 18 O. The isotopic signature of this grain indicates that it formed around a low-mass star in which 17 O is produced during H burning in the core of the star. The arrows pointing to the color scales in the bottom two images refer to the solar system ratios for 17 O/ 16 O and 18 O/ 16 O, respectively. The fi eld of view for each image = 10 µm.
2018 March •
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Auger spectroscopy . Following the identifi cation of the presolar grains in the NanoSIMS, elemental compositions are determined using Auger spectroscopy. In AES, identifi cation of elements is accomplished by exciting atoms in the specimen with a primary electron beam of modest energy (2–20 keV) and measuring the energies of emitted Auger electrons, which are characteristic of the elements present. Analyses are conducted under ultra-high vacuum conditions so that the elemental concentrations measured refl ect the actual sample composition without interference from contaminating surface layers. T e primary electron beam can be focused to about 10 nm, and the spatial resolution of Auger elemental maps is of the same order. T e development of this technique for the analysis of presolar grains is discussed in detail elsewhere [ 2 ] and is summarized briefl y here. Specifi c analytical protocols were established for the measurement of presolar silicates to reduce the possibility of electron beam damage, which can occasionally produce artifacts in the Auger spectra. T ese include the use of a low-beam current (typically 10 kV, 0.25 nA), beam rastering over the grain of interest, and acquisition of multiple spectral scans that are added together to obtain a single Auger spectrum. Auger spectra are typically smoothed and diff erentiated prior to peak identifi - cation. T e Auger intensities can then be determined from the peak-to-peak heights in the derivative spectrum ( Figure 4 ) in order to obtain quantitative compositional information [ 2 ]. In order to take into account matrix eff ects in our complex geological samples, sensitivity factors were determined for the major rock-forming elements from a variety of olivine and pyroxene standards. Reported errors are based on the 1σ uncertainties in the sensitivity factors (O: 3.6%; Si: 11%; Fe: 11.2%; Mg: 9.4%; Al: 24.9%; Ca: 10.8%). T ese values, which are based on the standard deviation of the Auger/electron probe ratios for the diff erent elements in the standards used [ 2 ], can be considered lower limits since they do not include a correction for background noise or take into account other factors that can aff ect the quality of a spectrum (for example, sample charging, residual surface contamination). In addition to localized composition measurements, high-resolution elemental distribution maps can provide detailed qualitative
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