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Gc 8a user manual11/3/2022 ![]() ![]() This work highlights a clear advantage of N 2 O for low-level Ca determinations with high matrix loads, as well as compatibility with other instrumentation sensitive to corrosion that supports reaction cell technology. Further investigation of matrix interferences with synthetic standards highlighted that the N 2 O approach supports the separation of potassium (K) and magnesium (Mg)–based interferences at tested concentrations of more than 600 times and almost 800 times higher than Ca respectively, whereas NH 3 was found to only support the removal of Mg. Instrument performance testing demonstrated that N 2 O was capable of reaching equivalent detection limits (0.015 ng g ⁻¹ ) and background equivalence concentrations (0.041 ng g ⁻¹ ) to that of NH 3 and limited by the blank only. Therefore, this work proposes the use of nitrous oxide (N 2 O) to mass shift the target analyte ⁴⁰ Ca to ⁴⁰ Ca ¹⁶ O ⁺ as a non-corrosive and non-toxic alternative. However, NH 3 is highly corrosive and toxic and cannot remove isobaric ⁴⁰ K. Ammonia (NH 3 ) has proven to be an effective reaction gas by process of a charge transfer reaction. ![]() A powerful approach is to remove the interference by using a reaction gas in a reaction cell. In inductively coupled plasma mass spectrometry, the most abundant Ca isotope ( ⁴⁰ Ca) suffers from isobaric interference with argon, hindering the potential for low detection limits of Ca. The Bi content data obtained from this study for a cosmochemical sample are in excellent agreement with neutron activation values in literature. The Pb isotopic composition data obtained from this study are in good agreement with the literature values obtained using multicollector inductively coupled plasma mass spectrometry and thermal ionization mass spectrometry, which ensures the accuracy of the Pb isotopic ratios obtained by our method. Our developed analytical procedure was applied to geological and cosmochemical reference samples to evaluate the accuracy of our data. Lead is chosen as the most appropriate internal standard element to reduce the matrix effect when determining Bi content. For this purpose, an accurate determination scheme of Pb isotopic ratios is established using standard-sample bracketing and matrix-matching methods due to the significantly differences of Pb isotope ratios in commercial standard solution, geochemical and cosmochemical samples. Pb and Bi contents are determined using isotope dilution and calibration methods, respectively. Our statistical analysis shows that the geochemical signatures of magmas vary with the tectono-magmatic setting, as do the geochemical processes involved in magma generation.Ī method for accurately determining Pb and Bi contents in geochemical and cosmochemical solid samples using inductively coupled plasma quadrupole mass spectrometry (ICP–QMS) is described. Based on the extracted geochemical characteristics, we discuss the processes that may lead to the formation of magmas in different tectono-magmatic settings. The extracted geochemical features and associated diagrams can be used to examine geochemical similarities and differences between tectono-magmatic settings and to identify the geochemical characteristics of unknown samples. Based on the statistical analysis, we present a small number (2–4) of key geochemical features for each tectono-magmatic setting. This approach allowed us to identify a small number of representative geochemical features from a total of 857 variables, including major and trace element concentrations, isotope ratios, and all possible ratios and multiplications of elements. We used the sparse modeling approach, with which we can objectively identify a small number of fundamental features from a large number of observations. We analyzed geochemical data for volcanic rocks compiled from the global geochemical databases based on statistical model fitting. In this study, key geochemical features of magmas formed in eight different tectono-magmatic settings (mid-ocean ridges, oceanic islands, oceanic plateaus, continental flood basalt provinces, intra-oceanic arcs, continental arcs, island arcs, and back-arc basins) are presented that were obtained using a machine-learning-based statistical model. ![]()
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