Polytopic Vector Analysis (PVA) modelling of whole-rock and apatite chemistry from the Karkonosze composite pluton (Poland, Czech Republic)

Lisowiec, Katarzyna; Słaby, Ewa; Förster, Hans‐Jürgen

doi:10.1016/j.lithos.2015.05.015

Cited by 15 publications

(18 citation statements)

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“…Rock samples used in the present study include three granodiorites -RUD1, RUD2, FOJ, one porphyritic granite -MIL, and equigranular granite -EQU. Fluorapatite crystals are usually 20-200 μm in size and demonstrate complex zonation patterns, indicating significant trace-element variations during crystal growth (Przywóski 2006;Słaby 2006;Lisowiec et al 2015). Grains were separated from the crushed and sieved rock by a combination of magnetic and heavy liquid (LST Fastfloat, Polytungstates Europe, Chippenham, UK) separation methods and subsequently prepared as polished grain mounts embedded in epoxy.…”

Section: Samples and Analytical Methodsmentioning

confidence: 99%

Visualization of trace-element zoning in fluorapatite using BSE and CL imaging, and EPMA and μPIXE/μPIGE mapping

et al. 2016

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In this paper, zonation patterns of trace elements in fluorapatite are discussed that were visualized using four analytical techniques, namely back-scattered electrons (BSE) and cathodoluminescence (CL) imaging, electron probe micro-analysis (EPMA), and micro-proton-induced X-ray/ gamma ray emission (μPIXE/μPIGE) mapping. Each method demonstrates the in-grain compositional variations in a slightly different way. Both BSE and CL provide qualitative data, and the internal textures are displayed in most detail. Additionally, CL points to specific elements enriched in certain growth zones. Qualitative EPMA maps show detailed zonation patterns for specific elements (with high spatial resolution), which are in general correspondence with the patterns observed in BSE and CL images. The μPIXE/μPIGE maps are fully quantitative and the detection limits are relatively low compared to EPMA mapping. In present spot measurements μPIXE demonstrates lower detection limits than EPMA, however, the latter could be considerably improved by extending the acquisition times. There is no significant overlap of REE (rare earth elements) peaks in the acquired μPIXE energy spectra, however, when multiple REEs are present with sufficiently high concentrations, peak deconvolution may pose some difficulties. Spatial resolution of μPIXE/μPIGE images is not sufficiently high to reflect minor textural features, which also result from the greater interaction depth of the proton beam. However, major growth zones are distinguishable. Even though each method has their advantages and limitations, when applied together, they provide an almost complete characterization of compositional variability in trace-element-bearing minerals.

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Section: Samples and Analytical Methodsmentioning

confidence: 99%

Visualization of trace-element zoning in fluorapatite using BSE and CL imaging, and EPMA and μPIXE/μPIGE mapping

et al. 2016

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“…Igneous rock researchers have also been an adapter of these unmixing algorithms. These include Horkowitz et al (1989), Stattegger and Morton (1992), Tefend et al (2007), Vogel et al (2008, Deering et al (2008), Barclay et al (2010), Szymanski et al (2013), Lisowiec et al (2015) and most recently by Blum-Oeste and Wörner (2016).…”

Section: Review Of the Applications Of Constant Sum Unmixingmentioning

confidence: 99%

Linear Unmixing in the Geologic Sciences: More Than A Half-Century of Progress

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2018

Handbook of Mathematical Geosciences

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For more than a half-century, scientists have been developing a tool for linear unmixing utilizing collections of algorithms and computer programs that is appropriate for many types of data commonly encountered in the geologic and other science disciplines. Applications include the analysis of particle size data, Fourier shape coefficients and related spectrum, biologic morphology and fossil assemblage information, environmental data, petrographic image analysis, unmixing igneous and metamorphic petrographic variable and the unmixing and determination of oil sources, to name a few. Each of these studies used algorithms that were designed to use data whose row sums are constant. Non-constant sum data comprise what is a larger set of data that permeates many of our sciences. Many times, these data can be modeled as mixtures even though the row sums do not sum to the same value for all samples in the data. This occurs when different quantities of one or more end-member are present in the data. Use of the constant sum approach for these data can produce confusing and inaccurate results especially when the end-members need to be defined away from the data cloud. The approach to deal with these non-constant sum data is defined and called Hyperplanar Vector Analysis (HVA). Without abandoning over 50 years of experience, HVA merges the concepts developed over this time and extends the linear unmixing approach to more types of data. The basis for this development involves a translation and rotation of the raw data that conserves information (variability). It will also be shown that HVA is a more appropriate name for both the previous constant sum algorithms and future programs algorithms as well.

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“…The petrological and geochemical evolution of the pluton has been extensively studied using whole-rock and mineral chemistry (Słaby and Götze 2004;Awdankiewicz et al 2005;Słaby and Martin 2005;Awdankiewicz 2007;Słaby et al 2007aSłaby et al , 2007bSłaby and Martin 2008;Lisowiec et al 2015). One of the main differentiation mechanisms responsible for the compositional diversity is mixing between mantlederived lamprophyric melt and crust-derived granitic magma.…”

Section: Geological Setting and Sample Descriptionmentioning

confidence: 99%

“…IG -Izera gneisses and granito-gneisses with belts of mica schists; EKC -Eastern Karkonosze Complex; LV -Leszczyniec unit; SKC -Southern Karkonosze Complex. Geographical coordinates of the sampling sites are given in Lisowiec et al (2015) mafic magma was injected in smaller quantities into slightly more viscous granitic magma and formed less evolved porphyritic granites with minor mafic enclaves. Late stage of mixing is represented by the presence of abundant magmatic enclaves (Fig.…”

Section: Geological Setting and Sample Descriptionmentioning

confidence: 99%

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Geochemical evolution of a composite pluton: insight from major and trace element chemistry of titanite

et al. 2020

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Titanite from various rocks of the Karkonosze granitoid pluton (South-Eastern Poland) was studied, in order to evaluate its precision in recording magma evolution processes. The rocks are of lamprophyric, dioritic, granodioritic and granitic composition, including hybrid structures such as microgranular magmatic enclaves and composite dykes. Based on textures, chemistry and Zr-in-titanite geothermometry, titanites can be divided into magmatic and post-magmatic populations. Late- to post-magmatic titanite is present in almost all rock types, especially in the most evolved ones (where magmatic titanite is absent) and can be characterized by low trace element and high Al and F contents. Magmatic titanite crystallized in temperatures between 610 and 870 °C, after apatite and relatively simultaneously with amphibole and zircon. Titanite from lamprophyre exhibits compositional features typical of titanites formed in mafic rocks: low Al and F, high Ti4+/(Al + Fe3+), LREE (light rare earth elemet)-enriched chondrite-normalized REE patterns, low Y/Zr, Nb/Zr, Lu/Hf, high (Ce + Nd)/Y, Th/U and Zr. Titanite from hybrid rocks inherited these characteristics, indicating major contribution of the mantle-derived magma especially during early stages of magmatic evolution. Titanite compositional variations, as well as a wide range of crystallization temperatures in hybrid granodiorites point to prolonged crystallization from distinct magma domains of variable mafic versus felsic melt proportions. The extent of compositional variations decreases through subsequent stages of magmatic evolution, and titanite with the least contribution of the mafic component is characterized by higher total REE, Al and F contents, lower Ti4+/(Al + Fe3+), (Ce + Nd)/Y and Th/U ratios, LREE-depleted chondrite-normalized REE patterns and higher Y/Zr, Nb/Zr and Lu/Hf ratios. Titanite composition from the intermediate and late stage hybrids bears signature of decreasing amount of the mafic melt and higher degree of its evolution, however, the exact distinction between the former and the latter is very limited.

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Polytopic Vector Analysis (PVA) modelling of whole-rock and apatite chemistry from the Karkonosze composite pluton (Poland, Czech Republic)

Cited by 15 publications

References 53 publications

Visualization of trace-element zoning in fluorapatite using BSE and CL imaging, and EPMA and μPIXE/μPIGE mapping

Visualization of trace-element zoning in fluorapatite using BSE and CL imaging, and EPMA and μPIXE/μPIGE mapping

Linear Unmixing in the Geologic Sciences: More Than A Half-Century of Progress

Geochemical evolution of a composite pluton: insight from major and trace element chemistry of titanite

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