Abstract Trace element analyses of silicate materials by secondary ion mass spectrometry (SIMS) typically normalize the secondary ion count rate for the isotopes of interest to the count rate for one of the silicon isotopes. While the great majority of SIMS analyses use the signal from Si+, some laboratories have used a multiply charged ion (Si2+ or Si3+). We collected data and constructed calibration curves for lithium, beryllium, and boron using these different normalizing species on synthetic basaltic glass and soda-lime silicate glass standards. The calibrations showed little effect of changing matrix when Si+ was used, but larger effects (up to a factor of ~2) when using Si2+ or Si3+ are a warning that care must be taken to avoid inaccurate analyses. The smallest matrix effects were observed at maximum transmission compared to detecting ions with a few tens of eV of initial kinetic energy (“conventional energy filtering”). Normalizing the light element ion intensities to Al3+ showed a smaller matrix effect than multiply-charged Si ions. When normalized to 16O+ (which includes oxygen from the sample and from the primary beam), the two matrices showed distinct calibration curves, suggesting that changing sputter yields (atoms ejected per primary atom impact) may play a role in the probability of producing multiply charged silicon ions.
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Secondary ion mass spectrometry techniques are used to study trace elements in organic samples where matrix compositions vary spatially. This study was conducted to develop calibrations for lithium content and lithium isotope measurements in kerogen. Known concentrations of Li ions (6Li and7Li) were implanted into organic polymers, with a range of H/C and O/C ratios similar to kerogen, along with glassy carbon (SPI Glas‐22) and silicate glass (NIST SRM 612). Results show that Li content calibration factors (
K *) are similar for carbonaceous samples when analysed using a 5 kV secondary ion accelerating voltage. Using a 9 kV secondary ion accelerating voltage,K * factors are negatively correlated with the sample O content, changing ~ 30% between 0 and 15 oxygen atomic %. Thus, to avoid the matrix effect related to O content, using a 5 kV secondary ion accelerating voltage is best for quantification of Li contents based on7Li+/12C+ratios. Under these analytical conditions, Li ppm (atomic) = (132 (± 8) × 7Li+/12C+) × 12C atom fraction of the sample measured. Lithium isotope ratio measurements of SPI Glas‐22 and NIST SRM 612 are within uncertainty; however, the organic polymer samples as a group show a 10‰ higher δ7Li than NIST SRM 612. -
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Rationale Back‐side thinning of wafers is used to eliminate issues with transient sputtering when analyzing near‐surface element distributions. Precise and accurate calibrated implants are created by including a standard reference material during the implantation. Combining these methods allows accurate analysis of low‐fluence, shallow features even if matrix effects are a concern.
Methods Implanted Na (<2.0 × 1011ions/cm2, peaking <50 nm) in diamond‐like carbon (DLC) film on silicon (solar wind returned by NASA's Genesis mission) was prepared for measurement as follows. Implanted surfaces of samples were epoxied to wafers and back‐side‐thinned using physical or chemical methods. Thinned samples were then implanted with reference ions for accurate quantification of the solar wind implant. Analyses used a CAMECA IMS 7f‐GEO SIMS in depth‐profiling mode.
Results Back‐side‐implanted reference ions reduced the need to change sample mounts or stage position and could be spatially separated from the solar wind implant even when measuring monoisotopic ions. Matrix effects in DLC were mitigated and the need to find an identical piece of DLC for a reference implant was eliminated. Accuracy was only limited by the back‐side technique itself.
Conclusions Combining back‐side depth profiling with back‐side‐implanted internal standards aides quantification of shallow mono‐ and polyisotopic implants. This technique helps mitigate matrix effects and keeps measurement conditions consistent. Depth profile acquisition times are longer, but if sample matrices are homogeneous, procedural changes can decrease measurement times.
