Predicting instrumental mass fractionation (IMF) of stable isotope SIMS analyses by response surface methodology (RSM) [Dataset]
Cita com:
hdl:2117/102417
Càtedra / Departament / Institut
Universitat Politècnica de Catalunya. Departament d'Enginyeria Minera, Industrial i TIC
Tipus de documentConjunt de dades
Data publicació2017-02
EditorUniversitat Politècnica de Catalunya
Versió1
Condicions d'accésAccés obert
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Publicacions relacionadesFàbrega, C., Parcerisa, D., Rossell, Josep M., Gurenko, A., Franke, C. Predicting instrumental mass fractionation (IMF) of stable isotope SIMS analyses by response surface methodology (RSM). "Journal of analytical atomic spectrometry", 10 Febrer 2017.
http://hdl.handle.net/2117/100911
Parcerisa Duocastella, D. [et al.]. (2016). Geostandards of the Valentí Masachs Geology Museum [Dataset]. 1 v. Universitat Politècnica de Catalunya. https://doi.org/10.5821/data-2117-103444-1 http://hdl.handle.net/2117/103444
Fàbrega, C. [et al.]. (2018). Geochemical data of albitized profiles in Europe [Dataset]. 1 v. Universitat Politècnica de Catalunya. http://hdl.handle.net/2117/114114
Fàbrega, C. [et al.]. Permian–Triassic red-stained albitized profiles in the granitic basement of NE Spain: evidence for deep alteration related to the Triassic palaeosurface. "International journal of Earth sciences", 1 Octubre 2019, vol. 108, núm. 7, p. 2325-2347. http://hdl.handle.net/2117/170191
Parcerisa Duocastella, D. [et al.]. (2016). Geostandards of the Valentí Masachs Geology Museum [Dataset]. 1 v. Universitat Politècnica de Catalunya. https://doi.org/10.5821/data-2117-103444-1 http://hdl.handle.net/2117/103444
Fàbrega, C. [et al.]. (2018). Geochemical data of albitized profiles in Europe [Dataset]. 1 v. Universitat Politècnica de Catalunya. http://hdl.handle.net/2117/114114
Fàbrega, C. [et al.]. Permian–Triassic red-stained albitized profiles in the granitic basement of NE Spain: evidence for deep alteration related to the Triassic palaeosurface. "International journal of Earth sciences", 1 Octubre 2019, vol. 108, núm. 7, p. 2325-2347. http://hdl.handle.net/2117/170191
Abstract
Instrumental mass fractionation (IMF) of isotopic SIMS analyses (Cameca 1280HR, CRPG Nancy) was predicted by response surface methodology (RSM) for 18O/16O determinations of plagioclase, K-feldspar and quartz. The three predictive response surface models combined instrumental and compositional inputs. The instrumental parameters were: (i) X and Y position, (ii) LT1DefX and LT1DefY electrostatic deflectors, (iii) chamber pressure and, (iv) primary-ion beam intensity. The compositional inputs included: (i) anorthite content (An%) for the plagioclase model and, (ii) orthoclase (Or%) and barium (BaO%) contents for the K-feldspar model. The three models reached high predictive powers. The coefficients R2 and prediction-R2 were, respectively, 90.47% and 86.74% for plagioclase, 87.56% and 83.17% for K-feldspar and 94.29% and 91.59% for quartz. The results show that RSM can be confidently applied to IMF prediction in stable isotope SIMS analyses by the use of instrumental and compositional variables.
Descripció
The dataset contains four files. File S1 corresponds to cathodoluminescence and BSE images of standard minerals. File S2 contains geochemical data of mineral standards ans samples obtained by SIMS and EPMA. File S3 contains the parameters used to obtain response surface models of IMF in mineral standards. File S4 is a response surface methodology tutorial.
CitacióParcerisa Duocastella, D. [et al.]. (2017). Predicting instrumental mass fractionation (IMF) of stable isotope SIMS analyses by response surface methodology (RSM) [Dataset]. 1 v. Universitat Politècnica de Catalunya. https://doi.org/10.5821/data-2117-102417-1
Fitxers | Descripció | Mida | Format | Visualitza |
---|---|---|---|---|
S1. CL+BSE imag ... ounts of the standards.pdf | 1,205Mb | Visualitza/Obre | ||
S2.SIMS+EPMA+Fluorination.xlsx | 125,2Kb | Microsoft Excel 2007 | Visualitza/Obre | |
S3. Response Surface Models.xlsx | 714,7Kb | Microsoft Excel 2007 | Visualitza/Obre | |
S4. Response Surface Model construction.pdf | 1,831Mb | Visualitza/Obre |