TY - JOUR
AU - Ferlito,, Carmelo
AB - Abstract Solidification, emplacement and fluid dynamics of a sub-volcanic rock at Mt Etna have been investigated through two-dimensional (2D) and three-dimensional (3D) textural analyses of the hosted bubbles and minerals. This rock is a 4·3 m thick aphyric dyke (DK) that solidified at a depth of 100–300 m, below the pristine surface level. Seven samples from the dyke rim (DK1) to core (DK7) have been analysed in two dimensions by using a high-resolution scanner, a transmission optical microscope and scanning electron microscopy imaging with back-scattered electrons, and in three dimensions by microfocus X-ray computed tomography. Field observations and mesoscopic polished rock surfaces show bubble-rich, -poor and -free patches even in rock pieces of a few cubic centimetres, with changes in sizes and shapes; even so, their shapes and spatial arrangement can never be attributed to high degrees of strain. In parallel, the amount of bubbles irregularly varies from dyke rim to core, whereas plagioclase (plg), clinopyroxene (cpx), titanomagnetite (timt), and olivine (ol) show only limited variations. The fabric of bubbles retrieved by 3D orientation of their maximum length (i.e. elongation) is invariably random in space for each DK sample. These bubble features have been attributed to transitional to turbulent flows; that is, non-laminar regimes (Reynolds number > 1000), predicted for a long time from numerical models and that occurred before the crystallization of minerals. Water solubility, volume of bubbles, magma density and viscosity models indicate that, at pressure higher than 10 MPa, 1 wt % H2O was dissolved in the original trachybasaltic magma, which, in turn, was close to its liquidus temperature. As the pressure decreased at very shallow levels, the magma significantly degassed and volatile exsolution induced marked crystallization (mostly plg followed by cpx). The viscosity of the system increased, decelerating and halting the magmatic suspension. The textures and fabrics of bubbles were suddenly frozen in, despite crystals continuing to grow under the effect of cooling rate variables from the inner (DK7) to outer (DK1) dyke portions. Fluid-dynamic computations suggest that the DK trachybasaltic magma ascended with a velocity of few metres per second in a transitional to turbulent regime, before the growth of minerals. INTRODUCTION The ascent of magmas to shallow crustal levels occurs mainly along dykes, which are categorized as discrete, vertical, sheet-like bodies. When the pressure at the top of a magmatic reservoir overcomes the tensile resistance of the overlying rocks, failures can develop by coalescence of cracks under stress induced by pressurized volatiles (gas cap of H2O and CO2) and fluids (melt ± dissolved volatiles ± minerals ± bubbles). Failures then propagate upwards responding to the mechanical properties of the overlying rocks, regional and local stress fields, and the fluid-mechanical behaviour of injected magmas (Pollard, 1973, 1976, 1987; Spera, 1980; Delaney et al., 1986; Lister & Kerr, 1991; Rubin, 1995; Gudmundsson et al., 1999; McLeod & Tait, 1999; Menand & Tait, 2001; Gudmundsson, 2006; Acocella & Neri, 2009; Geshi & Neri, 2011; Daniels et al., 2012; Maimon et al., 2012; Mangan et al., 2014; Gonnerman & Taisne, 2015; Rivalta et al., 2015; and references therein). Most dykes develop near-vertically in the host rocks and, rarely, produce eruptions. This depends on the physico-chemical conditions of the magma and its host-rock, such as the bulk composition, temperature (T), pressure (P), volatile and/or mineral contents, as well as kinetic effects dictating crystal nucleation and growth, degassing, and outgassing. Kinetic effects are governed by heat transfer from the magma to the surrounding host-rock and the ascent rate imposed by magmatic overpressure and density contrast between the magma and cross-cut rock(s) (Spera, 1980; Bruce & Huppert, 1990; Carrigan et al., 1992; Rubin, 1995; Carrigan, 2000; Jaupart, 2000; Pinel & Jaupart, 2004; Taisne & Jaupart, 2009; Maccaferri et al., 2011; Taisne et al., 2011; Zuan Chen et al., 2011; Maimon et al., 2012; Yamato et al., 2012, 2015; Mangan et al., 2014; Gonnerman & Taisne, 2015; Rivalta et al., 2015; and references therein). Theoretical aspects of dyke emplacement, such as the central topic concerning fluid-dynamic regimes in dykes (Maccaferri et al., 2011; Galindo & Gudmundsson, 2012; Daniels et al., 2014; Gonnerman & Taisne, 2015; Rivalta et al., 2015), require corroboration by field and petrological data. In this context, theoretical and numerical models predict both laminar and non-laminar regimes (Huppert & Sparks, 1985; Emerman & Turcotte, 1986; Spence & Turcotte, 1990; Carrigan, 2000; Jaupart, 2000), but turbulence in dykes has only been suggested based on crude field observations (Kille et al., 1986). Pioneering two-dimensional (2D) textural and fabric studies of minerals and bubbles have unveiled both petrological and rheological magmatic processes in dykes (Teall, 1884; Queneau, 1902; Holmes & Iarwood, 1929; Quinn, 1943; Winkler, 1948; Campbell & Schenk, 1950; Cashman, 1992; Sigurdsson, 2000; Mangan et al., 2014). These studies were followed by more quantitative 2D investigations (Gray, 1970, 1978; Komar, 1972, 1976; Ikeda, 1977; Howard, 1980; Shelley, 1985; Wada, 1992; Hastie et al., 2011, 2013), revealing variations in the size and shape of minerals and bubbles, as well as in the fabric moving from the central to the external parts of dykes. In recent decades, dykes have been largely investigated by three-dimensional (3D) anisotropic magnetic susceptibility (AMS) (Ernst & Baragart, 1992; Callot et al., 2001; Herrero-Bervera et al., 2001; Femenias et al., 2004; Aubourg et al., 2008; Eriksson et al., 2011; Bjarne et al., 2012; Andersson et al., 2016; and references therein) and to a lesser extent by 2D textures combined with magnetic properties (Poland et al., 2004; Clemente et al., 2007; Philpotts & Philpotts, 2007; Hastie et al., 2013). Conversely, a few studies on volcanic rocks have been performed using other 3D methods to investigate crystal lattice preferred orientation such as electron backscatter diffraction (EBSD) (Bascou et al., 2005), neutron diffraction (Walter et al., 2013) and X-ray computed microtomography (µCT) (Álvarez-Valero et al., 2016). The orientation of magnetic tensors mainly depends on the texture and fabric of iron-bearing crystals with relevant magnetic signals such as titanomagnetite (timt), with a moderate effect for biotite (bt) and amphibole (amph), and a low effect for plagioclase (plg), clinopyroxene (cpx) and olivine (ol). Hence, AMS may be not suitable to measure absolute dimensions and shapes of bubbles and the whole mineral phases, recording only the late stage of deformation (Iezzi & Ventura, 2002; Cañón-Tapia & Chàves-Álvarez, 2004; Cañón-Tapia & Herrero-Bervera, 2009). Magma dynamics in dykes can also be successfully investigated by variations in mineral compositions (e.g. Chistyakova & Latypov, 2009; Tartese & Boulvais, 2010; Mollo et al., 2011, 2012; Scarlato et al., 2014). The combination of texture, fabric, and composition of each phase is the most complete strategy to reconstruct the solidification paths of magmas feeding dykes. Unfortunately, dykes are scarcely investigated by modern microchemical and 2D imaging methods, as well as 3D imaging techniques. Only recently has X-ray µCT been applied to dacitic magmas (Álvarez-Valero et al., 2016), which have obvious compositional, textural, and rheological differences from the trachybasaltic magma analyzed here. In this study, the textural and fabric attributes of seven rock samples representative of the internal variability of an Etnean dyke from rim to core have been investigated to complement major and trace element changes previously documented for plg, cpx and timt (Mollo et al., 2011; Scarlato et al., 2014). The rock samples have been analyzed by 2D methods (on polished rock surfaces and thin sections) and 3D imaging using laboratory X-ray µCT. The size, shape, and orientation of bubbles and minerals allow us to reconstruct the solidification behaviour of the magma and appear to confirm the fluid-dynamic scenario suggested by theoretical models. Similar investigations can be extended to other dykes or lavas to better understand the mechanisms responsible for the transport of magmas at shallow crustal levels and in volcanic eruptions. THE ETNEAN DYKES Geological setting Mt Etna is an active stratovolcano located in eastern Sicily (Italy) and is characterized by effusive and Strombolian activity associated with persistent degassing from its four main craters (Monaco et al., 1997; Ferlito & Lanzafame, 2010; Ferlito et al., 2014). The main edifice of the volcano was built in the last 220 kyr (Gillot et al., 1994; Tanguy et al., 1997, 2007; De Beni et al., 2005; Branca et al., 2008) and developed through four major phases: Ancient Alkaline Centers (AAC; 220–120 ka), Trifoglietto (80–60 ka), Ellittico (60–15 ka) and Recent Mongibello (15 ka to present) (Cristofolini et al., 1979; Romano, 1982; Gillot et al., 1994; Catalano et al., 2004; Monaco et al., 2005; and references therein). On its eastern side the current edifice is characterized by the Valle del Bove depression, bordered on its western part by the high reaches of the volcano and on its northern and southern sides by steep walls formed by remains of the Trifoglietto and Ellittico products (McGuire, 1982; Romano, 1982; Lanzafame & Vestch, 1985; Ferlito & Cristofolini, 1989; Calvari et al., 1994; Coltelli et al., 1994; D’Orazio et al., 1997; Monaco et al., 2010). Several dykes crop out over these steep walls, displaying portions of the ancient shallow plumbing system feeding the various eruptive centres (see Ferlito & Nicotra, 2010). Features and sampling of the dyke On the southern wall of the Valle del Bove, at the head of the wide gully named Canalone dei Faggi at about 1700 m a.s.l. (Fig. 1), several dykes are observable with common features: thickness of a few metres, near-vertical attitude, sharp contacts with wall-rocks, absence or very limited content of observable crystals (aphanitic texture), and moderate amounts of slightly deformed bubbles distributed in bubble-rich, -poor and -free patches. The bubbles do not follow any textural trends from rim to core and primarily form eddies or vortices with diameters from several centimetres to a few decimetres. Fig. 1. Open in new tabDownload slide (a) Location of the dyke (yellow star) and Canalone dei Faggi (yellow dashed line); Google Earth image (b) The dyke characteristics in the field, with lateral contacts (red dashed lines) and the position and orientation of the DK samples. z, x and y are vertical, rim-to-rim (thickness) and normal to the plane dyke directions, respectively. Fig. 1. Open in new tabDownload slide (a) Location of the dyke (yellow star) and Canalone dei Faggi (yellow dashed line); Google Earth image (b) The dyke characteristics in the field, with lateral contacts (red dashed lines) and the position and orientation of the DK samples. z, x and y are vertical, rim-to-rim (thickness) and normal to the plane dyke directions, respectively. We focused on a 4·3 m thick dyke (i.e. DK), which intruded lava and pyroclastic sequences ascribed to the Ellittico activity before 15 ka. This portion of the dyke was originally located at a depth of 100–300 m below the ground surface (Mollo et al., 2011). According to the field characteristics of the DK outcrop (Fig. 1), the dyke was emplaced in a single magmatic pulse, because of its very sharp contacts, absence of any engulfment of wall-rocks and systematic chemical variations of minerals from rim to core (Mollo et al., 2011). From outermost to innermost DK portions, seven samples, DK1 to DK7, were collected with a sampling distance of ∼350 mm. These prismatic samples were oriented coaxially to the field: z is the vertical direction, x is the thickness (rim to rim) and y is the horizontal direction of DK (Fig. 1). The sampled rocks have edges of about 100–200, 100–200 and 50–100 mm. Each sample was cut normally to the dyke walls such as to expose the representative z–x surfaces (Fig. 1), then seven surfaces (or portions of them) with areas in the order of 103–104 mm2 were polished for statistically significant mesoscopic observations. The short and long sides of these sections are coaxial with the z and x directions, respectively. We collected these samples in the half-width right part of the dyke, assuming that the rocks are representative of the entire dyke. Although some dykes may show a non-symmetrical fabric from rim to rim (Femenias et al., 2004; Nkono et al., 2006), the small overall thickness of the dyke presented in this study ensures symmetrical characteristics. Mineralogy and geochemistry The seven rock samples that are the object of this study have been previously investigated by Mollo et al. (2011, 2013) and Scarlato et al. (2014). The DK dyke is trachybasaltic with (wt %) SiO2 = 48·6 (±0·3), TiO2 = 1·9 (±0·1), Al2O3 = 16·9 (±0·2), FeO = 11·3 (±0·2), MnO = 0·2 (±0·1), MgO = 4·2 (±0·1), CaO = 10·4 (±0·1), Na2O = 3·8 (±0·2), K2O = 1·6 (±0·1) and P2O5 = 1·2 (±0·1). The phase assemblage of the dyke comprises cpx, plg, and timt, plus ol xenocrysts (Mollo et al., 2011). Plg, cpx and timt compositions progressively change from dyke core to rim (Mollo et al., 2011, 2013). Specifically, albite (Ab), diopside (Di) and ulvöspinel (Usp) contents increase, counterbalanced by a decrease of anorthite (An), Tschermak (Ts) and magnetite (Mg) (Supplementary Data Fig. 1S; supplementary data are available for downloading at http://www.petrology.oxfordjournals.org). The increasing amounts of Ts from dyke core to rim are also accompanied by increasing concentrations of rare earth elements (REE) in cpx (Supplementary Data Fig. 1S) (Scarlato et al., 2014). MATERIALS AND METHODS 2D imaging, processing, and analysis The mesoscopic polished surfaces with areas ranging from 103 to 104 mm2 were prepared to expose phases with maximum dimension >1 mm. Thin sections show 2D textural attributes at the 1:1 scale, acquired by a high-resolution scanner (HRS), at 2·5× and 10× magnification (parallel and cross polarizers) with a transmission optical microscope (TOM) and at 100× to 3000× magnification by scanning electron microscope with back-scattered electrons (BS-SEM). HRS analyses were performed with a high-resolution Epson V750 Pro scanner and TOM investigations were carried out with a Zeiss Axioscope optical microscope, both installed at the Dipartimento di Ingegneria & Geologia of the University G. d’Annunzio (Chieti, Italy). For BS-SEM analyses a Jeol-JXA8200 scanning electron microscope, equipped with an energy-dispersive spectroscopy (EDS) probe and installed at the HPHT Laboratory of Experimental Volcanology and Geophysics of the Istituto Nazionale di Geofisica e Vulcanologia (INGV) in Rome (Italy) was used. Variable areas and related magnifications of digital images allowed us to constrain statistically all phases with sizes from centimetre to micrometre scale (down to 1 µm), avoiding over-sampling (excess counting of tiny objects) and under-sampling effects (excess counting of large objects). The techniques employed for textural quantification, on the basis of phase sizes, are summarized in Table 1. Nine images per sample with a total of 63 digital images were recorded, following the protocols and procedures reported in previous studies (Higgins, 2006; Iezzi et al., 2008, 2011, 2014; Lanzafame et al., 2013; Vetere et al., 2013, 2015b). The 2D image processing and analysis were performed using Image Pro-Plus 5.0 Media Cybernetics commercial software. Each image, obtained at various magnifications, was first transformed to grey levels (where zero is black and 255 is white) and calibrated to a millimetre scale. After the use of a 2D median filter to remove noise, each phase (bubbles and crystals) with its distinctive grey levels was identified. Thereafter, the phases were reproduced in false colours, segmented, and automatically counted. Table 1 Two-dimensional textural results Sample . Distance . Phase . >1 mm . >0·1 and . <0·1/0·2 mm . 2D whole . No. mm–2 . label . from wall- . . (area %) . ≤1 mm . (area %) . amount . . . rock (cm) . . (HRS) . (area %) . (BS-SEM) . (area %) . . . . . . (TOM) . . . . DK1 0 bubbles 0·4 10·8 (3·2) — 11·2 3·50 plg — — 72·1 (1·7) 72·1 — cpx — — 22·3 (1·4) 22·3 4113 ol — — 1·8 (0·8) 1·8 1076 timt — — 3·9 (0·9) 3·9 1192 DK2 36 bubbles 10·5 9·1 (3·4) — 19·6 0·69 plg — — 72·1 (2·3) 72·1 — cpx — — 20·6 (2·8) 20·6 2491 ol — — 2·5 (0·4) 2·5 1097 timt — — 4·9 (0·8) 4·9 727 DK3 72 bubbles 5·4 3·6 (4·5) — 8·9 0·31 plg — — 71·0 (2·4) 71 — cpx — — 17·9 (1·6) 17·9 2651 ol — — 3·3 (0·7) 3·3 1812 timt — — 7·7 (1·6) 7·7 1401 DK4 108 bubbles 13·6 12·8 (3·5) — 26·4 0·90 plg — — 71·3 (2·4) 71·3 — cpx — — 19·0 (1·1) 19 1853 ol — — 5·1 (1·0) 5·1 1280 timt — — 4·8 (0·8) 4·8 441 DK5 144 bubbles 27·4 1·6 (2·1) — 29 0·21 plg — — 67·5 (2·5) 67·5 — cpx — — 18·8 (1·8) 18·8 1443 ol — — 6·8 (2·2) 6·8 1291 timt — — 6·9 (1·4) 6·9 680 DK6 180 bubbles 8·5 0·7 (0·8) — 9·2 0·15 plg — — 67·3 (0·8) 67·3 — cpx — — 20·6 (2·4) 20·6 1349 ol — — 6·8 (0·9) 6·8 1609 timt — — 5·4 (0·9) 5·4 426 DK7 216 bubbles 20·9 1·3 (1·4) — 22·2 0·23 plg — — 70·7 (3·6) 70·7 — cpx — — 19·7 (2·6) 19·7 1423 ol — — 5·5 (0·5) 5·5 1614 timt — — 3·9 (0·6) 3·9 423 Sample . Distance . Phase . >1 mm . >0·1 and . <0·1/0·2 mm . 2D whole . No. mm–2 . label . from wall- . . (area %) . ≤1 mm . (area %) . amount . . . rock (cm) . . (HRS) . (area %) . (BS-SEM) . (area %) . . . . . . (TOM) . . . . DK1 0 bubbles 0·4 10·8 (3·2) — 11·2 3·50 plg — — 72·1 (1·7) 72·1 — cpx — — 22·3 (1·4) 22·3 4113 ol — — 1·8 (0·8) 1·8 1076 timt — — 3·9 (0·9) 3·9 1192 DK2 36 bubbles 10·5 9·1 (3·4) — 19·6 0·69 plg — — 72·1 (2·3) 72·1 — cpx — — 20·6 (2·8) 20·6 2491 ol — — 2·5 (0·4) 2·5 1097 timt — — 4·9 (0·8) 4·9 727 DK3 72 bubbles 5·4 3·6 (4·5) — 8·9 0·31 plg — — 71·0 (2·4) 71 — cpx — — 17·9 (1·6) 17·9 2651 ol — — 3·3 (0·7) 3·3 1812 timt — — 7·7 (1·6) 7·7 1401 DK4 108 bubbles 13·6 12·8 (3·5) — 26·4 0·90 plg — — 71·3 (2·4) 71·3 — cpx — — 19·0 (1·1) 19 1853 ol — — 5·1 (1·0) 5·1 1280 timt — — 4·8 (0·8) 4·8 441 DK5 144 bubbles 27·4 1·6 (2·1) — 29 0·21 plg — — 67·5 (2·5) 67·5 — cpx — — 18·8 (1·8) 18·8 1443 ol — — 6·8 (2·2) 6·8 1291 timt — — 6·9 (1·4) 6·9 680 DK6 180 bubbles 8·5 0·7 (0·8) — 9·2 0·15 plg — — 67·3 (0·8) 67·3 — cpx — — 20·6 (2·4) 20·6 1349 ol — — 6·8 (0·9) 6·8 1609 timt — — 5·4 (0·9) 5·4 426 DK7 216 bubbles 20·9 1·3 (1·4) — 22·2 0·23 plg — — 70·7 (3·6) 70·7 — cpx — — 19·7 (2·6) 19·7 1423 ol — — 5·5 (0·5) 5·5 1614 timt — — 3·9 (0·6) 3·9 423 Crystals were measured only by BS-SEM, whereas bubbles were measured only by HRS and TOM owing to their sizes >0·1 mm. Table 1 Two-dimensional textural results Sample . Distance . Phase . >1 mm . >0·1 and . <0·1/0·2 mm . 2D whole . No. mm–2 . label . from wall- . . (area %) . ≤1 mm . (area %) . amount . . . rock (cm) . . (HRS) . (area %) . (BS-SEM) . (area %) . . . . . . (TOM) . . . . DK1 0 bubbles 0·4 10·8 (3·2) — 11·2 3·50 plg — — 72·1 (1·7) 72·1 — cpx — — 22·3 (1·4) 22·3 4113 ol — — 1·8 (0·8) 1·8 1076 timt — — 3·9 (0·9) 3·9 1192 DK2 36 bubbles 10·5 9·1 (3·4) — 19·6 0·69 plg — — 72·1 (2·3) 72·1 — cpx — — 20·6 (2·8) 20·6 2491 ol — — 2·5 (0·4) 2·5 1097 timt — — 4·9 (0·8) 4·9 727 DK3 72 bubbles 5·4 3·6 (4·5) — 8·9 0·31 plg — — 71·0 (2·4) 71 — cpx — — 17·9 (1·6) 17·9 2651 ol — — 3·3 (0·7) 3·3 1812 timt — — 7·7 (1·6) 7·7 1401 DK4 108 bubbles 13·6 12·8 (3·5) — 26·4 0·90 plg — — 71·3 (2·4) 71·3 — cpx — — 19·0 (1·1) 19 1853 ol — — 5·1 (1·0) 5·1 1280 timt — — 4·8 (0·8) 4·8 441 DK5 144 bubbles 27·4 1·6 (2·1) — 29 0·21 plg — — 67·5 (2·5) 67·5 — cpx — — 18·8 (1·8) 18·8 1443 ol — — 6·8 (2·2) 6·8 1291 timt — — 6·9 (1·4) 6·9 680 DK6 180 bubbles 8·5 0·7 (0·8) — 9·2 0·15 plg — — 67·3 (0·8) 67·3 — cpx — — 20·6 (2·4) 20·6 1349 ol — — 6·8 (0·9) 6·8 1609 timt — — 5·4 (0·9) 5·4 426 DK7 216 bubbles 20·9 1·3 (1·4) — 22·2 0·23 plg — — 70·7 (3·6) 70·7 — cpx — — 19·7 (2·6) 19·7 1423 ol — — 5·5 (0·5) 5·5 1614 timt — — 3·9 (0·6) 3·9 423 Sample . Distance . Phase . >1 mm . >0·1 and . <0·1/0·2 mm . 2D whole . No. mm–2 . label . from wall- . . (area %) . ≤1 mm . (area %) . amount . . . rock (cm) . . (HRS) . (area %) . (BS-SEM) . (area %) . . . . . . (TOM) . . . . DK1 0 bubbles 0·4 10·8 (3·2) — 11·2 3·50 plg — — 72·1 (1·7) 72·1 — cpx — — 22·3 (1·4) 22·3 4113 ol — — 1·8 (0·8) 1·8 1076 timt — — 3·9 (0·9) 3·9 1192 DK2 36 bubbles 10·5 9·1 (3·4) — 19·6 0·69 plg — — 72·1 (2·3) 72·1 — cpx — — 20·6 (2·8) 20·6 2491 ol — — 2·5 (0·4) 2·5 1097 timt — — 4·9 (0·8) 4·9 727 DK3 72 bubbles 5·4 3·6 (4·5) — 8·9 0·31 plg — — 71·0 (2·4) 71 — cpx — — 17·9 (1·6) 17·9 2651 ol — — 3·3 (0·7) 3·3 1812 timt — — 7·7 (1·6) 7·7 1401 DK4 108 bubbles 13·6 12·8 (3·5) — 26·4 0·90 plg — — 71·3 (2·4) 71·3 — cpx — — 19·0 (1·1) 19 1853 ol — — 5·1 (1·0) 5·1 1280 timt — — 4·8 (0·8) 4·8 441 DK5 144 bubbles 27·4 1·6 (2·1) — 29 0·21 plg — — 67·5 (2·5) 67·5 — cpx — — 18·8 (1·8) 18·8 1443 ol — — 6·8 (2·2) 6·8 1291 timt — — 6·9 (1·4) 6·9 680 DK6 180 bubbles 8·5 0·7 (0·8) — 9·2 0·15 plg — — 67·3 (0·8) 67·3 — cpx — — 20·6 (2·4) 20·6 1349 ol — — 6·8 (0·9) 6·8 1609 timt — — 5·4 (0·9) 5·4 426 DK7 216 bubbles 20·9 1·3 (1·4) — 22·2 0·23 plg — — 70·7 (3·6) 70·7 — cpx — — 19·7 (2·6) 19·7 1423 ol — — 5·5 (0·5) 5·5 1614 timt — — 3·9 (0·6) 3·9 423 Crystals were measured only by BS-SEM, whereas bubbles were measured only by HRS and TOM owing to their sizes >0·1 mm. Objects attributed to each phase were characterized considering their corresponding equal-area ellipses. We calculated the phase abundance expressed as area % (ratio between the area occupied by the investigated phase and the total area of the sample section), the areal number density (defined as the number of objects per unit area, no. mm–2), the object size in terms of aspect ratio (defined by the long and short axes of their equal-area ellipses and their ratio), and the orientation of the long axis with respect to the x direction (see Fig. 1). Bubbles having sizes >0·1 mm were quantified by means of images from HRS and TOM. Because crystal sizes never exceed ∼0·2 mm they were measured on BS-SEM images (see below). Plg phases aggregate along their longest axis, preventing the accurate identification of single crystals and thus providing only their phase abundances (area %). In contrast, cpx, timt, and ol phases occur mainly as single crystals, with only some of them showing aggregation features. Consequently, we assumed that agglomerated grains invariably correspond to a single crystal (see Fig. 2). Bubbles can be sharply identified and quickly measured as single objects. A schematic view of the 2D image processing and analysis protocol is represented in Fig. 2. Fig. 2. Open in new tabDownload slide Examples of 2D observation and segmentation of phases by image analysis. Top: mesoscopic polished surface (DK5) used for general inspection of large phases and their disposition in space. Lower left: high-resolution scanner (HRS) original scanned image (above) and its corresponding segmented image (below) used for counting phases >1 mm in size (in red). Lower middle: transmission optical microscopy (TOM) parallel and cross-polarized digital images at 2·5× (above and middle) with segmented phases >0·1 and ≤1 mm in size (in red) (below). Lower right: back-scattered scanning electron microscopy (BS-SEM) image at 200× (above) and the corresponding segmented phases with size <0·2 mm (below). False colours on HRS, TOM and BS-SEM images are red for bubbles, yellow for cpx, cyan for ol, and blue for timt (red is used for plg only in BS-SEM images). In this dyke, bubbles with size <0·1 mm are not observed or are extremely rare, whereas the single crystal length is ≤0·2 mm. Fig. 2. Open in new tabDownload slide Examples of 2D observation and segmentation of phases by image analysis. Top: mesoscopic polished surface (DK5) used for general inspection of large phases and their disposition in space. Lower left: high-resolution scanner (HRS) original scanned image (above) and its corresponding segmented image (below) used for counting phases >1 mm in size (in red). Lower middle: transmission optical microscopy (TOM) parallel and cross-polarized digital images at 2·5× (above and middle) with segmented phases >0·1 and ≤1 mm in size (in red) (below). Lower right: back-scattered scanning electron microscopy (BS-SEM) image at 200× (above) and the corresponding segmented phases with size <0·2 mm (below). False colours on HRS, TOM and BS-SEM images are red for bubbles, yellow for cpx, cyan for ol, and blue for timt (red is used for plg only in BS-SEM images). In this dyke, bubbles with size <0·1 mm are not observed or are extremely rare, whereas the single crystal length is ≤0·2 mm. 3D imaging, processing, and analysis Seven DK samples with dimensions from 4·2 to 10·8 cm3 (see Table 2) were cut and imaged by laboratory X-ray µCT using the TomoLab station at the Elettra synchrotron light facility in Basovizza (Trieste, Italy) (Mancini et al., 2007; Polacci et al., 2009). The TomoLab is equipped with a sealed microfocus X-ray tube operating in a voltage range from 40 to 130 kV, a maximum current of 300 μA and a minimum focal spot size of 5 μm. The used detector consisted of a full frame CCD imager (4008 × 2672 pixels) coupled to a gadolinium oxysulphide scintillator by a fiber-optic tape. The water-cooled CCD camera has a 12-bit dynamic range, and an effective pixel size of 12·5 × 12·5 μm2. Owing to the cone-beam geometry, it is possible to achieve a spatial resolution close to the focal spot size, on samples from a few millimetres to a few centimetres in size. The experimental parameters used for the X-ray µCT scans are reported in Table 2. Scans for DK1 and DK5 were acquired with a pixel size of 6·25 μm, whereas for samples DK2, DK3, DK4, DK6 and DK7 a pixel size of 8 μm was set. The slice reconstruction was performed using the commercial software COBRA (Exxim) based on the Feldkamp algorithm (Feldkamp et al., 1984). The same software allowed us to correct beam hardening artefacts (Kitchen et al., 2007). Table 2 Three-dimensional analytical conditions Sample . d1 . d2 . Volume . Tube . Current . Filter . Voxel . No. of . Angle of . Exposure . label . (mm) . (mm) . (cm3) . voltage . (μA) . . size . projections . rotation . time . . . . . (kV) . . . (µm) . . (deg) . (s) . DK1 100 400 10·8 130 61 1·5 mm Al 6·25 2400 360 6·5 DK2 80 250 5·3 130 61 1·5 mm Al 8 1800 360 4 DK3 80 250 3·8 130 61 1·5 mm Al 8 1800 360 4 DK4 80 250 10·1 130 61 1·5 mm Al 8 1800 360 4 DK5 100 400 4·2 130 61 1·5 mm Al 6·25 2400 360 6·5 DK6 80 250 6·2 130 61 1·5 mm Al 8 1800 360 4 DK7 80 250 6·3 130 61 1·5 mm Al 8 1800 360 4 Sample . d1 . d2 . Volume . Tube . Current . Filter . Voxel . No. of . Angle of . Exposure . label . (mm) . (mm) . (cm3) . voltage . (μA) . . size . projections . rotation . time . . . . . (kV) . . . (µm) . . (deg) . (s) . DK1 100 400 10·8 130 61 1·5 mm Al 6·25 2400 360 6·5 DK2 80 250 5·3 130 61 1·5 mm Al 8 1800 360 4 DK3 80 250 3·8 130 61 1·5 mm Al 8 1800 360 4 DK4 80 250 10·1 130 61 1·5 mm Al 8 1800 360 4 DK5 100 400 4·2 130 61 1·5 mm Al 6·25 2400 360 6·5 DK6 80 250 6·2 130 61 1·5 mm Al 8 1800 360 4 DK7 80 250 6·3 130 61 1·5 mm Al 8 1800 360 4 Experimental parameters used for the X-ray µCT scans. d1, source to sample distance; d2, source to detector distance. Table 2 Three-dimensional analytical conditions Sample . d1 . d2 . Volume . Tube . Current . Filter . Voxel . No. of . Angle of . Exposure . label . (mm) . (mm) . (cm3) . voltage . (μA) . . size . projections . rotation . time . . . . . (kV) . . . (µm) . . (deg) . (s) . DK1 100 400 10·8 130 61 1·5 mm Al 6·25 2400 360 6·5 DK2 80 250 5·3 130 61 1·5 mm Al 8 1800 360 4 DK3 80 250 3·8 130 61 1·5 mm Al 8 1800 360 4 DK4 80 250 10·1 130 61 1·5 mm Al 8 1800 360 4 DK5 100 400 4·2 130 61 1·5 mm Al 6·25 2400 360 6·5 DK6 80 250 6·2 130 61 1·5 mm Al 8 1800 360 4 DK7 80 250 6·3 130 61 1·5 mm Al 8 1800 360 4 Sample . d1 . d2 . Volume . Tube . Current . Filter . Voxel . No. of . Angle of . Exposure . label . (mm) . (mm) . (cm3) . voltage . (μA) . . size . projections . rotation . time . . . . . (kV) . . . (µm) . . (deg) . (s) . DK1 100 400 10·8 130 61 1·5 mm Al 6·25 2400 360 6·5 DK2 80 250 5·3 130 61 1·5 mm Al 8 1800 360 4 DK3 80 250 3·8 130 61 1·5 mm Al 8 1800 360 4 DK4 80 250 10·1 130 61 1·5 mm Al 8 1800 360 4 DK5 100 400 4·2 130 61 1·5 mm Al 6·25 2400 360 6·5 DK6 80 250 6·2 130 61 1·5 mm Al 8 1800 360 4 DK7 80 250 6·3 130 61 1·5 mm Al 8 1800 360 4 Experimental parameters used for the X-ray µCT scans. d1, source to sample distance; d2, source to detector distance. The 3D image processing and analysis of the seven imaged samples were performed using the Pore3D software library developed at Elettra (Elettra, 2009; Brun et al., 2010; Zandomeneghi et al., 2010), which allows extraction of quantitative microstructural and textural parameters of porous and multiphase systems. The software includes tools for filtering and segmentation of digital images, and procedures for the analysis of morphology, texture and anisotropy, as well as for the skeletonization and skeleton analysis functions to extract topological information. The Pore3D software was also used to reduce ring artefacts from the reconstructed axial slices (Sijbers & Postnov, 2004; Brun et al., 2011). The 3D visualization (through surface and volume rendering procedures) of reconstructed and processed volumes was done employing the commercial software VGStudio MAX 2.0 (Volume Graphics). The image acquisition protocol adopted for the X-ray μCT imaging in this study allows the investigation of bubbles at medium (∼10 µm) spatial resolution on centimetre-sized samples. For that reason, we worked in absorption mode and this did not allow us to characterize tiny crystals, such as ol, plg and cpx, with refractive indices close to the rock matrix. Conversely, it was possible to investigate fully, within the limit of the selected spatial resolution, the morphological and textural features of timt crystals, owing to the high contrast of this phase with respect to the rock sample matrix. The quantitative analysis was performed on suitable Volumes of Interest (VOIs), extracted from each imaged sample with the aim of detecting all the representative structures of the rocks (Table 3). To verify the representativeness of the selected VOIs, Representative Elementary Volumes (REVs) were determined. An REV is defined as the minimum volume large enough to enclose a significant amount of the sample heterogeneity (Gitman et al., 2007; Zandomeneghi et al., 2010). For each sample, we considered the bubble and timt volume fraction as the parameter for REV determination applying the box-counting method (Al-Raoush & Papadopoulos, 2010; Zhang et al., 2012). Table 3 Three-dimensional textural results Sample label: . . DK1 . DK2 . DK3 . DK4 . DK5 . DK6 . DK7 . Voxels 651 × 796 × 826 × 667 × 468 × 598 × 740 × 516 × 857 1122 × 1270 990 × 1280 1374 × 1280 1080 × 1270 916 × 1270 924 × 1270 Isotropic-voxel length (mm) 0·0063 0·0080 0·0080 0·0080 0·0063 0·0080 0·0080 Volume (mm3) 70·3 580·7 535·9 600·6 156·7 356·2 444·6 Volume % bubbles 10·9 16·8 12·2 13·9 22·9 10·8 19·4 timt 2·48 2·80 2·65 2·89 2·63 2·59 2·63 Number bubbles 4143 729 2993 781 2495 353 389 timt 6338 30470 33356 47302 17505 24965 35120 Number per volume (no. mm–3) bubbles 58·9 1·3 5·6 1·3 15·9 1·0 0·9 timt 90·2 52·5 62·2 78·8 111·7 70·1 79·0 Average volume (mm3) bubbles 0·002 0·133 0·022 0·107 0·014 0·109 0·221 timt 2 × 10–4 4 × 10–4 4 × 10–4 3 × 10–4 2 × 10–4 3 × 10–4 3 × 10–4 Average aspect ratio bubbles 0·25 0·38 0·33 0·35 0·22 0·36 0·36 Average sphericity bubbles 0·69 0·71 0·71 0·72 0·71 0·73 0·73 Specific surface area (mm–1) bubbles 4·5 0·6 0·6 0·3 0·1 0·2 0·3 Integral of mean curvature (mm–2) bubbles 53·1 2·3 4·5 1·1 2·5 0·9 1·0 Euler characteristic (mm–3) bubbles 51·9 0·7 4·5 0·9 15·5 0·7 0·6 Connectivity density bubbles –10·45 0·40 0·17 0·41 1·66 0·35 0·40 Elongation index bubbles 0·03 0·09 0·10 0·05 0·10 0·04 0·08 timt 0·06 0·06 0·07 0·06 0·02 0·04 0·04 Isotropy index bubbles 0·73 0·74 0·70 0·71 0·78 0·71 0·77 timt 0·93 0·88 0·89 0·90 0·90 0·90 0·89 Sample label: . . DK1 . DK2 . DK3 . DK4 . DK5 . DK6 . DK7 . Voxels 651 × 796 × 826 × 667 × 468 × 598 × 740 × 516 × 857 1122 × 1270 990 × 1280 1374 × 1280 1080 × 1270 916 × 1270 924 × 1270 Isotropic-voxel length (mm) 0·0063 0·0080 0·0080 0·0080 0·0063 0·0080 0·0080 Volume (mm3) 70·3 580·7 535·9 600·6 156·7 356·2 444·6 Volume % bubbles 10·9 16·8 12·2 13·9 22·9 10·8 19·4 timt 2·48 2·80 2·65 2·89 2·63 2·59 2·63 Number bubbles 4143 729 2993 781 2495 353 389 timt 6338 30470 33356 47302 17505 24965 35120 Number per volume (no. mm–3) bubbles 58·9 1·3 5·6 1·3 15·9 1·0 0·9 timt 90·2 52·5 62·2 78·8 111·7 70·1 79·0 Average volume (mm3) bubbles 0·002 0·133 0·022 0·107 0·014 0·109 0·221 timt 2 × 10–4 4 × 10–4 4 × 10–4 3 × 10–4 2 × 10–4 3 × 10–4 3 × 10–4 Average aspect ratio bubbles 0·25 0·38 0·33 0·35 0·22 0·36 0·36 Average sphericity bubbles 0·69 0·71 0·71 0·72 0·71 0·73 0·73 Specific surface area (mm–1) bubbles 4·5 0·6 0·6 0·3 0·1 0·2 0·3 Integral of mean curvature (mm–2) bubbles 53·1 2·3 4·5 1·1 2·5 0·9 1·0 Euler characteristic (mm–3) bubbles 51·9 0·7 4·5 0·9 15·5 0·7 0·6 Connectivity density bubbles –10·45 0·40 0·17 0·41 1·66 0·35 0·40 Elongation index bubbles 0·03 0·09 0·10 0·05 0·10 0·04 0·08 timt 0·06 0·06 0·07 0·06 0·02 0·04 0·04 Isotropy index bubbles 0·73 0·74 0·70 0·71 0·78 0·71 0·77 timt 0·93 0·88 0·89 0·90 0·90 0·90 0·89 Average aspect ratio is the ratio between the longest and the shortest segment passing through the centre of mass. Average sphericity is the ratio of the diameter of the maximum inscribed sphere in a blob and the diameter of the sphere with the same volume as the blob. Specific surface area is the ratio between the surface of the objects and their volume. For the integral of mean curvature, positive and negative values indicate the dominance of convex and concave objects (bubbles) respectively. Euler characteristic is an index of connectivity of the object network (bubbles), where positive and negative values are indicative of isolated versus connected or aggregated objects (bubbles). Connectivity density is the number of redundant connections normalized to the total volume, with negative and positive values indicative of low and high connection respectively. Elongation index measures the preferred orientation of a fabric, varying between zero (no preferred orientation) and unity (perfect preferred orientation). Isotropy index measures the similarity of fabric to a uniform distribution, changing between zero (fully anisotropic) and unity (perfect isotropy). Table 3 Three-dimensional textural results Sample label: . . DK1 . DK2 . DK3 . DK4 . DK5 . DK6 . DK7 . Voxels 651 × 796 × 826 × 667 × 468 × 598 × 740 × 516 × 857 1122 × 1270 990 × 1280 1374 × 1280 1080 × 1270 916 × 1270 924 × 1270 Isotropic-voxel length (mm) 0·0063 0·0080 0·0080 0·0080 0·0063 0·0080 0·0080 Volume (mm3) 70·3 580·7 535·9 600·6 156·7 356·2 444·6 Volume % bubbles 10·9 16·8 12·2 13·9 22·9 10·8 19·4 timt 2·48 2·80 2·65 2·89 2·63 2·59 2·63 Number bubbles 4143 729 2993 781 2495 353 389 timt 6338 30470 33356 47302 17505 24965 35120 Number per volume (no. mm–3) bubbles 58·9 1·3 5·6 1·3 15·9 1·0 0·9 timt 90·2 52·5 62·2 78·8 111·7 70·1 79·0 Average volume (mm3) bubbles 0·002 0·133 0·022 0·107 0·014 0·109 0·221 timt 2 × 10–4 4 × 10–4 4 × 10–4 3 × 10–4 2 × 10–4 3 × 10–4 3 × 10–4 Average aspect ratio bubbles 0·25 0·38 0·33 0·35 0·22 0·36 0·36 Average sphericity bubbles 0·69 0·71 0·71 0·72 0·71 0·73 0·73 Specific surface area (mm–1) bubbles 4·5 0·6 0·6 0·3 0·1 0·2 0·3 Integral of mean curvature (mm–2) bubbles 53·1 2·3 4·5 1·1 2·5 0·9 1·0 Euler characteristic (mm–3) bubbles 51·9 0·7 4·5 0·9 15·5 0·7 0·6 Connectivity density bubbles –10·45 0·40 0·17 0·41 1·66 0·35 0·40 Elongation index bubbles 0·03 0·09 0·10 0·05 0·10 0·04 0·08 timt 0·06 0·06 0·07 0·06 0·02 0·04 0·04 Isotropy index bubbles 0·73 0·74 0·70 0·71 0·78 0·71 0·77 timt 0·93 0·88 0·89 0·90 0·90 0·90 0·89 Sample label: . . DK1 . DK2 . DK3 . DK4 . DK5 . DK6 . DK7 . Voxels 651 × 796 × 826 × 667 × 468 × 598 × 740 × 516 × 857 1122 × 1270 990 × 1280 1374 × 1280 1080 × 1270 916 × 1270 924 × 1270 Isotropic-voxel length (mm) 0·0063 0·0080 0·0080 0·0080 0·0063 0·0080 0·0080 Volume (mm3) 70·3 580·7 535·9 600·6 156·7 356·2 444·6 Volume % bubbles 10·9 16·8 12·2 13·9 22·9 10·8 19·4 timt 2·48 2·80 2·65 2·89 2·63 2·59 2·63 Number bubbles 4143 729 2993 781 2495 353 389 timt 6338 30470 33356 47302 17505 24965 35120 Number per volume (no. mm–3) bubbles 58·9 1·3 5·6 1·3 15·9 1·0 0·9 timt 90·2 52·5 62·2 78·8 111·7 70·1 79·0 Average volume (mm3) bubbles 0·002 0·133 0·022 0·107 0·014 0·109 0·221 timt 2 × 10–4 4 × 10–4 4 × 10–4 3 × 10–4 2 × 10–4 3 × 10–4 3 × 10–4 Average aspect ratio bubbles 0·25 0·38 0·33 0·35 0·22 0·36 0·36 Average sphericity bubbles 0·69 0·71 0·71 0·72 0·71 0·73 0·73 Specific surface area (mm–1) bubbles 4·5 0·6 0·6 0·3 0·1 0·2 0·3 Integral of mean curvature (mm–2) bubbles 53·1 2·3 4·5 1·1 2·5 0·9 1·0 Euler characteristic (mm–3) bubbles 51·9 0·7 4·5 0·9 15·5 0·7 0·6 Connectivity density bubbles –10·45 0·40 0·17 0·41 1·66 0·35 0·40 Elongation index bubbles 0·03 0·09 0·10 0·05 0·10 0·04 0·08 timt 0·06 0·06 0·07 0·06 0·02 0·04 0·04 Isotropy index bubbles 0·73 0·74 0·70 0·71 0·78 0·71 0·77 timt 0·93 0·88 0·89 0·90 0·90 0·90 0·89 Average aspect ratio is the ratio between the longest and the shortest segment passing through the centre of mass. Average sphericity is the ratio of the diameter of the maximum inscribed sphere in a blob and the diameter of the sphere with the same volume as the blob. Specific surface area is the ratio between the surface of the objects and their volume. For the integral of mean curvature, positive and negative values indicate the dominance of convex and concave objects (bubbles) respectively. Euler characteristic is an index of connectivity of the object network (bubbles), where positive and negative values are indicative of isolated versus connected or aggregated objects (bubbles). Connectivity density is the number of redundant connections normalized to the total volume, with negative and positive values indicative of low and high connection respectively. Elongation index measures the preferred orientation of a fabric, varying between zero (no preferred orientation) and unity (perfect preferred orientation). Isotropy index measures the similarity of fabric to a uniform distribution, changing between zero (fully anisotropic) and unity (perfect isotropy). VOIs having size larger than the determined REVs were extracted and then filtered to remove noise and preserve edges using an ‘anisotropic diffusion filter’ (Weickert, 1998). The next step was the segmentation of the images to obtain binary volumes containing the different classes of the phases of interest. Thresholding was performed using the automatic MultiOtsu method (Otsu, 1979). For each sample, we extracted two binary datasets corresponding to bubbles and timt, the least and most dense phases with respect to the DK groundmass. Segmented images were then processed applying various cycles of erosion and dilation to remove noise and background objects <3–5 voxels (Serra, 1982). Because samples show bubbles and timt in contact with the border of the VOIs, analyses were performed on two datasets: (1) VOIs containing all the objects to quantify their total amount; (2) VOIs in which the objects touching the image margins were suppressed, considering only the morphometric values of un-truncated objects. We applied the Basic Analysis module of the Pore3D software (Zandomeneghi et al., 2010) to obtain bubble and timt density (number of voxels of each phase versus the total number of voxels), specific surface area (surface area of all the phases divided by the total VOI), integral of mean curvature (an index of the abundance of convex versus concave shapes; Russ & DeHoff, 1986) and Euler characteristic (index scaling with the network connectivity of a given phase; Odgaard & Gundersen, 1993; Ohser & Mücklich, 2000). The results are reported in Table 3. All bubbles and timt crystals, identified using the concept of maximal inscribed spheres (Hildebrand & Rüegsegger, 1997; Baker et al., 2012), were then labelled and analysed, calculating the number of elements, volume, sphericity, aspect ratio and diameter of the maximal inscribed sphere. The spatial relations of the objects within the samples were then investigated calculating the values of isotropic distribution (I) and preferential orientation (E) of bubbles and timt crystals. The connectivity of bubble networks was investigated by a skeletonization approach (Lindquist & Lee, 1996). The skeleton can describe the connectivity and tortuosity of the bubble network, as it can be intuitively considered as the 1D representation of the ‘spine’ of a 3D object. Owing to hardware-related computational limits, the skeletonization was performed on sub-VOIs with a size of 500 × 500 × 500 voxels, still having REV characteristics. Among the skeletonization algorithms available in Pore3D we selected the LKC skeletonization function (Lee et al., 1994), which is particularly suitable for those volcanic samples characterized by limited connectivity of the bubble network. Two cycles of 3D median filtering were run on the segmented images of bubbles to smooth their borders before the computation. After skeletonization, an iterative pruning of all branches with sizes <20 voxels was applied. The application of smoothing and pruning procedures allowed removal of unnecessary branches and nodes, which, after visual inspection by the operator, are found to be not representative of the real connectivity frames. Once obtained, skeletons were used to calculate the connectivity density (CD), defined as a scalar value representing the number of redundant connections normalized to the total volume V and computed as CD=(1–XV)/V where ΧV = (n – b), n being the number of bubbles and b the number of bubble-to-bubble branches of the skeleton (Brun et al., 2010). Negative CD values indicate scarce connection, whereas positive values are typical of highly connected networks (Brun et al., 2010; Zandomeneghi et al., 2010). A graphical summary of the most important 3D image processing and analysis steps adopted is illustrated in Fig. 3. Fig. 3. Open in new tabDownload slide Example of the Pore3D image analysis protocol applied to sample DK2. (a) Portion of a reconstructed axial slice; (b) filtered image with an ‘anisotropic diffusion filter’; (c) threshold bubbles and (d) timt by 3D MultiOtsu filtering. Fig. 3. Open in new tabDownload slide Example of the Pore3D image analysis protocol applied to sample DK2. (a) Portion of a reconstructed axial slice; (b) filtered image with an ‘anisotropic diffusion filter’; (c) threshold bubbles and (d) timt by 3D MultiOtsu filtering. RESULTS The 2D textural features of phases are summarized in Fig. 4 and detailed information is reported in the Supplementary Data (Fig. S1–S7). From dyke rim (DK1) to core (DK7), the most important characteristics are as follows: (1) bubble size (long axis of equal-area ellipse) is >0·1 mm and crystal size is <0·1 mm for most of the minerals (only a few crystals have size exceeding 0·2 mm); (2) bubbles show heterogeneous distributions, shapes, and orientations that contrast with the high homogeneity of crystals; (3) the glass matrix is absent or possibly corresponds to only a few area per cent around plg rims (Fig. 4; Supplementary Data Fig. S1–S7). Fig. 4. Open in new tabDownload slide Original and segmented textural features of DK samples at variable scales. First, second, third and fourth rows from top to down show: (1) mesoscopic attributes on polished rock surfaces (∼103 mm2); (2) HRS images of the polished thin sections (∼102 mm2); (3) TOM segmented images at 2·5× (∼101 mm2); (4) BS-SEM segmented pictures (∼10–1 to 10–2 mm2). Bubbles have sizes >0·1 mm (red in second and third rows), whereas crystals (fourth row) have sizes ≤0·2 mm. Red, plg; yellow, cpx; cyan, ol; blue, timt. The short and long edges of thin sections (second row) are coaxial with z and x directions (see Fig. 1). Further details are reported in Supplementary Data Fig. S1–S7. Fig. 4. Open in new tabDownload slide Original and segmented textural features of DK samples at variable scales. First, second, third and fourth rows from top to down show: (1) mesoscopic attributes on polished rock surfaces (∼103 mm2); (2) HRS images of the polished thin sections (∼102 mm2); (3) TOM segmented images at 2·5× (∼101 mm2); (4) BS-SEM segmented pictures (∼10–1 to 10–2 mm2). Bubbles have sizes >0·1 mm (red in second and third rows), whereas crystals (fourth row) have sizes ≤0·2 mm. Red, plg; yellow, cpx; cyan, ol; blue, timt. The short and long edges of thin sections (second row) are coaxial with z and x directions (see Fig. 1). Further details are reported in Supplementary Data Fig. S1–S7. Area per cent, size, number density, shape, and orientation of bubbles do not follow any monotonic trend (see Fig. 4, and Supplementary Data Fig. S1–S7). At the macroscopic scale, DK1 is the only sample containing a great number of sub-millimetric (size >0·1 and <1 mm) bubbles, whereas other samples are mostly characterized by larger bubbles (size >1 mm). Bubbles with smaller dimensions appear more equant than larger ones. Bubbles in DK5 and DK7 have low aspect ratios and ellipsoid shapes. DK2 displays bubbles with highly anisotropic and irregular shapes, whereas intermediate shapes are observed in DK1, DK3, DK4 and DK6. The fabric of bubbles is oriented nearly coaxial to the vertical z direction (see Fig. 1) in DK2, DK4, DK5, and DK6, at 30/60° from z for DK3, and along x for DK6 (Fig. 4; Supplementary Data Fig. S1–S7). These observations from digital scanned images reflect those on the field and polished rock samples. The texture and fabric of minerals display weak variations from dyke rim to core, in contrast to the texture of the bubbles (Fig. 4; Supplementary Data Fig. S1–S7). Plg is by far the most abundant phase and occurs mainly as attached crystals along their longest directions. Cpx is the second most abundant mineral, with prismatic contours and only a minor degree of attachment to itself. The amount of timt is low, with only large crystals (maximum size of about 100 µm) exhibiting slight irregular boundaries, probably resulting from the attachment of tiny crystals (maximum size of a few micrometres). Ol occurs invariably as small equant and faceted crystals (Fig. 4; Supplementary Data Fig. S1–S7). The area per cent values of phases observed by HRS, TOM, and BS-SEM analyses conducted at different magnifications are summarized in Table 1 and plotted in Fig. 5a where the area per cent values of minerals are calculated on a bubble-free basis. The abundance of bubbles from dyke rim to core shows an irregular non-monotonic trend (Fig. 5a). Bubbles with size >1 mm are infrequent (0·1 area %) in DK1, whereas bubbles with size >0·1 mm and ≤1 mm are infrequent (<2 area %) in the inner dyke portions (DK5, DK6, and DK7) and more abundant (9·1–12·8 area %) in DK1, DK2, and DK4 (Table 1). Fig. 5. Open in new tabDownload slide Quantitative 2D textural features of DK rocks from rim to core. (a) Abundance of bubbles, plg, cpx, ol and timt calculated on a vesicle-free basis; (b) number of single bubbles or minerals per unit area (no. mm–2). Fig. 5. Open in new tabDownload slide Quantitative 2D textural features of DK rocks from rim to core. (a) Abundance of bubbles, plg, cpx, ol and timt calculated on a vesicle-free basis; (b) number of single bubbles or minerals per unit area (no. mm–2). The values of plg area per cent show slight variation along the dyke profile similar to what is observed for cpx (Fig. 5a). The number density of cpx strongly decreases from DK1 to all other dyke samples (Table 1 and Fig. 5b). Ol has a low abundance and a crystal length of a few tens of micrometres (Table 1; Fig. 4; Supplementary Data Fig. S1–S7). The 3D bubble textural parameters are reported in Table 3 and are graphically represented in Fig. 6a and b. The volumetric abundance of bubbles follows a complex heterogeneous trend (Fig. 7a) similar to that determined by the 2D analysis (Fig. 5a). Samples DK1 and DK6 have the lowest bubble contents (∼11 vol. %), whereas sample DK5 has the highest bubble amount (∼23 vol. %). The abundance of bubbles obtained by 3D analysis is comparable with the 2D data for samples DK1, DK2, DK3, DK6 and DK7. In contrast, the 2D and 3D data show differences for samples DK4 and DK5 (see discussion below). The overall trend depicted by the number of bubbles per unit volume in three dimensions is similar to that measured in two dimensions (Figs 5b and 7b). Fig. 6. Open in new tabDownload slide (a) Top row: renderings of the imaged volumes for the investigated samples. Middle row: reconstructed axial slices. Bottom row: the same slices as reported in the middle row where bubbles (red) and timt (blue) not connected with the borders have been segmented. (b) Renderings of 500 × 500 × 500 voxels sub-volumes of selected samples. Top row: isosurface renderings of the bubble phase. Middle row: skeletons of the bubble network (green, node-to-node connections; red, end-to-end branches). Bottom row: isosurface rendering of the timt phase. Fig. 6. Open in new tabDownload slide (a) Top row: renderings of the imaged volumes for the investigated samples. Middle row: reconstructed axial slices. Bottom row: the same slices as reported in the middle row where bubbles (red) and timt (blue) not connected with the borders have been segmented. (b) Renderings of 500 × 500 × 500 voxels sub-volumes of selected samples. Top row: isosurface renderings of the bubble phase. Middle row: skeletons of the bubble network (green, node-to-node connections; red, end-to-end branches). Bottom row: isosurface rendering of the timt phase. Fig. 7. Open in new tabDownload slide Quantitative 3D textural features of dyke rocks from rim to core. (a) Abundance of bubbles and timt. (b) Number of bubbles and timt per unit volume (no. mm–3). Fig. 7. Open in new tabDownload slide Quantitative 3D textural features of dyke rocks from rim to core. (a) Abundance of bubbles and timt. (b) Number of bubbles and timt per unit volume (no. mm–3). The 3D measurements show that the abundance (2·4–2·9 vol. %) of timt remains practically constant from dyke rim to core (Table 3), whereas the 2D data point to a larger variation from 3 area % (DK7) to 7 area % (DK3). However, the remaining samples (DK1, DK2, DK4, DK5 and DK6) have timt very close to 4 area % (Table 1). From DK1 to DK7, the amount and number density of timt are low, showing modest variations for both 2D (3·9–7·7 area % and 400–1100 no. mm–2) and 3D methods (2·48–2·89 vol. % and 52–112 no. mm–3) (see Tables 1 and 3; Figs 4–8; Supplementary Data Fig. S1–S7). The distribution of timt is almost homogeneous in the samples (I ≥ 0·88). Preferential crystal orientations (E ≤ 0·06) are not observed owing to the isotropic shape of the minerals (Table 3). Consequently, the timt texture does not change from the outermost to innermost portions of the dyke. Fig. 8. Open in new tabDownload slide Abundances of bubbles determined by 2D (area %) and 3D (vol. %) image analyses. The dashed line corresponds to the 1:1 relation. Fig. 8. Open in new tabDownload slide Abundances of bubbles determined by 2D (area %) and 3D (vol. %) image analyses. The dashed line corresponds to the 1:1 relation. Bubbles Amount and number per area and per volume The abundances of bubbles determined by 2D and 3D analyses are similar (Fig. 8). DK1 shows a minimum discrepancy of ∼1%. DK2, DK3, DK6, and DK7 show moderate differences, lower than ∼3%. Conversely, discrepancies up to ∼12% and 6% are observed for DK4 and DK5, respectively (Tables 1 and 2, Fig. 8) and can be ascribed to the heterogeneous distribution of bubbles in the different portions of the samples (Figs 4 and 9; Supplementary Data Figs S4 and S5). The X-ray μCT analysis was in fact focused mostly on the volumetric portions of DK4 and DK5 that are enriched in bubbles, whereas the 2D data from thin sections refer to bubble-rich and bubble-poor areas (Fig. 4; Supplementary Data Fig. S4 and S5). This interpretation is corroborated by the very close values observed for 2D (11·2 area %) and 3D data (10·9 vol. %) measured for the most homogeneous sample DK1, showing a high number of small bubbles at the scale of several 102 mm2 and 103 mm3 (Tables 1 and 3). In contrast, DK4 is strongly heterogeneous in terms of the distribution and size of bubbles, with the coexistence of bubble-rich and bubble-poor areas of the order of several 103 mm2 (Figs 4 and 9; Supplementary Data Fig. S4). A similar conclusion holds for the number of bubbles per area and per volume determined from dyke rim to core (Figs 5b and 7b). Fig. 9. Open in new tabDownload slide Surface of the DK4 polished rock with an area of about 8 × 103 mm2. This shows the coexistence of patches with marked variation in amount, size, and shape (aspect ratio) of bubbles. Fig. 9. Open in new tabDownload slide Surface of the DK4 polished rock with an area of about 8 × 103 mm2. This shows the coexistence of patches with marked variation in amount, size, and shape (aspect ratio) of bubbles. Size and shape The majority of bubbles have lengths of several millimetres, with the exception of DK1, which contains bubbles invariably <1–2 mm (Fig. 4; Supplementary Data Fig. S1–S7). On average, 2D projected equal-area ellipses of a random distributed population of objects correspond to the intermediate and short sizes of 3D equant to prismatic solids, in agreement with stereology (Higgins, 2000, 2006). Following Higgins (2000), the mode of ratios of short and long axes of equal-area ellipses should be close to the ratio of the actual short (S) and intermediate (I) 3D solids, whereas the 3D long (L) size can be computed using the statistical parameters of such a distribution. Unfortunately, this stereological approach yielded inaccurate values for the S, I and L bubbles. Therefore, we decided to use ratios of the axes of 2D equal-area ellipses, according to the model proposed by Morgan & Jerram (2006), which also provides confidence of the attained results. The computed 3D axes from 2D ellipses of bubbles are shown in Fig. 10. With the exception of DK6, the samples provide moderate to highly accurate results. DK1, DK2 and DK3 correspond to ellipses with 3D axes close to 1:0·4/0·3:0·3/0·2, whereas DK4, DK5 and DK7 approximate to 1:0·9/0·7:0·7/0·6 (Fig. 10). Fig. 10. Open in new tabDownload slide Variation of the intermediate (I) and short (S) axis ratios normalized to long axis L of bubbles from dyke rim to core. (See text for details) Fig. 10. Open in new tabDownload slide Variation of the intermediate (I) and short (S) axis ratios normalized to long axis L of bubbles from dyke rim to core. (See text for details) Within the limits of the selected spatial resolution (of the order of 10 µm) X-ray μCT reveals that DK7 and DK1 have the largest (0·22 mm3) and smallest (0·002 mm3) bubble volumes, respectively. The other samples show variable bubble volumes of the order of 10–1 or 10–2 mm3. The maximum length measures the longest segment passing from the centre of mass of each bubble. The actual 3D maximum and minimum lengths are invariably lower than 1–2 mm and higher than 0·02 mm for DK1 and DK5 (Fig. 11). For these samples, bubbles with maximum length sizes <0·1 mm were not detected by the 2D data (see above). The other DK samples have maximum lengths ranging from 0·05 mm up to several millimetres (Fig. 11). The sphericity describes the largest voluminous sphere inscribed in a bubble. It is noteworthy that sphericity does not discriminate prolate (L ≫ I ∼ S) from oblate (L ∼ I ≫ S) bubbles. The 3D quantified sphericity ranges between 0·2 and 1, but frequently it is higher than 0·5 (Fig. 11). Diagrammatically, the sphericity of bubbles appears to crudely decrease as a function of the maximum length, but there is no analytical correlation between these parameters (Fig. 11). Furthermore, the maximum length and sphericity of bubbles do not follow any specific trend within a single DK sample, or from DK1 to DK7 (Fig. 11). The variation of bubble shape as a function of size (as obtained by X-ray µCT) indicates that a significant number of small bubbles (especially in DK1 and DK5) are undetected by 2D image analysis. At the same time, bubbles with an extreme low sphericity, such as tubular or extremely stretched ones, are never recognized in 3D (Fig. 11) or 2D images (Fig. 4; Supplementary Data Fig. S1–S7). Fig. 11. Open in new tabDownload slide Maximum length of bubbles vs sphericity (left side) and frequency distribution of sphericity (right side). Fig. 11. Open in new tabDownload slide Maximum length of bubbles vs sphericity (left side) and frequency distribution of sphericity (right side). Distribution and orientation The isotropy (I) and elongation (E) indices, evidencing the tendency to develop (or not) a fabric (Table 3), were extracted considering only the bubbles not touching the edges of the VOIs; that is, those preserving their real shape and volume. The index I represents the similarity of a fabric to a uniform distribution (Benn, 1994). In dyke samples, bubbles exhibit a high isotropic distribution (I = 0·70–0·78) (Table 3), in agreement with the presence of bubble-rich and bubble-poor areas (Fig. 4; Supplementary Data Fig. S1–S7). The preferred orientation of bubbles is quantified by the elongation, which is invariably low (E = 0·03–0·10), from dyke rim to core. This is apparently in contrast to some 2D images (Fig. 4; Supplementary Data Fig. S1–S7), where bubbles may appear arranged along several preferred directions. However, 2D bubble orientations are sub-fabrics only in thin rock portions, and disappear in a 3D rock volume. This finding suggests that, in the case of DK samples, 3D upshots represent the best method to outline the lack of a homogeneous bubble distribution and preferential bubble alignments. Connection and coalescence The connectivity density (CD) is a proxy for determining the amount of connected and unconnected bubbles in dyke samples. DK1 shows the lowest CD value (Table 3), in agreement with the highest amount of unconnected channels (Fig. 11). However, for all the samples, the CD is always near zero, indicating that bubbles are scarcely connected. Bubbles are not perfectly equally distributed within the rocks, allowing us to identify different sub-volumes for each VOI and to perform LKC skeletonization. The minimum (–10·4) and maximum (1·7) values of connectivity density are obtained for sub-volumes from DK1 and DK5, respectively. This suggests that, with respect to the dyke margin (DK1), the scarce amounts of connected bubbles in the inner portions of the dyke (from DK2 to DK7) were formed at an early stage of the magmatic intrusion. Moreover, coalescence attributes were estimated by the integral of the mean curvature (Mv), resolving the dominance of convex or concave structures. Positive Mv values for all the samples indicate the dominance of convex surfaces owing to the abundance of isolated bubbles, especially in DK1, which shows the highest number of bubbles (Table 3). DISCUSSION The 2D and 3D data for bubbles allow us to reconstruct the solidification and emplacement conditions of the dyke, in concert with fluid-dynamics effects. DK1 is radically different from the other dyke samples, owing to the fact that it contains a great number of small bubbles, whereas large bubbles are virtually absent. This indicates that, at the early stage of solidification, a significant rapid cooling rate developed only at the contact with the country-rocks (in a layer a few decimetres thick; Mollo et al., 2011). At the same time, it is important to stress that the amount of bubbles is between 10 and 30 area % (and/or vol. %), whereas the textures of minerals are variable (Table 1, Figs 5 and 7). High degrees of bubble deformation and textural change are not observed from dyke rim to core (Figs 6,10 and 11). Obviously, most of the bubbles nucleated before the mineral phases, to grow partially in parallel with the crystals. Solidification process Minerals show only minor variations of their textural attributes in concert with moderate and almost linear changes in the composition of plg, cpx, and timt from DK1 to DK7 (Fig. 1; Mollo et al., 2011; Scarlato et al., 2014). Conversely, the abundance of plg and cpx, as well as the number per area of cpx do not change linearly (Tables 1 and 3; Figs 4–7; Supplementary Data Fig. S1–S7). The texture of the crystalline phases strongly contrasts with irregular variations in the amount, size, shape, distribution, and orientation of bubbles (Tables 1 and 3; Figs 4–7, 10 and 11; Supplementary Data Fig. S1–S7). In the shallow portions of the Mt Etna feeding system, H2O strongly controls magma solidification and rheology (Mollo et al., 2015b; Perinelli et al., 2016), being the most important dissolved volatile species and the most abundant gas in bubbles (Del Gaudio et al., 2010; Giacomoni et al., 2014; Fiege et al., 2015; Vetere et al., 2015a). Most of the observed bubbles, especially those of large dimensions, formed before the crystallization of minerals, when the magma was in a liquid state. The aphyric character of the DK samples, the moderate to small size (<0·2 mm) of crystals, and the high average number of crystals per area or volume suggest an initial crystal-poor magmatic intrusion. Hence the magma was injected into the host-rocks under superheated conditions or close to its liquidus temperature. In turn, crystals mostly nucleated and grew during the ascent of the DK magma by both decompression-induced degassing (Hammer, 2008; Fiege et al., 2015; and references therein) and cooling (Iezzi et al., 2008, 2011; Mollo et al., 2011; Vetere et al., 2013, 2015a) processes. At the time of emplacement, the sampled dyke level was located at 100–300 m depth (Mollo et al., 2011). Indeed, large bubbles nucleated below this level, whereas tiny bubbles resulted from a second minor event of H2O exsolution (Figs 10 and 11), which occurred close to this shallow level. The volatile liberation also induced the onset of plg and cpx nucleation. All these processes contributed to the rise of the viscosity of the magma, as well as decelerating and/or halting the intrusion. The solubility and exsolution of H2O are strongly dependent on pressure, whereas temperature changes control the thermal regimes favouring crystal nucleation and growth (e.g. Hammer, 2008; Iezzi et al., 2008, 2011; Vetere et al., 2013, 2015b; Fiege et al., 2015). Plg nucleation was initially driven by decompression-induced degassing, at a moderate to high degree of undercooling, forming tiny grains with a high number per area, and frequent self-aggregation of crystals (Figs 4 and 5; Supplementary Data Fig. S1–S7). A similar process holds for cpx. If the initial nucleation of plg and cpx was induced only by cooling, the number of crystals per area should be very high at the dyke rim and progressively decrease towards the core, as expected owing to the effect of a variable cooling rate condition (Cashmann, 1992; Hammer, 2008; Vetere et al., 2013, 2015a). The decreasing trends of the number per area of bubbles and cpx, as well as the formation of tiny bubbles in DK1, are indicative of the significant effect of cooling only in proximity of the dyke margin in contact with the host-rock (Figs 4–7). Fluid-dynamic mechanism A first important characteristic of the dyke is the irregular distribution of exsolved H2O (i.e. bubbles). Both 2D and 3D textural and fabric analyses clearly evidence the irregular pattern of bubbles from the dyke rim to the core (Figs 5 and 7). The 2D data reveal variable bubble orientations (especially of the larger ones), whereas the 3D data suggest the absence of preferred bubble orientations. The imaged bubbles, in either two or three dimensions, never show features indicative of a high finite rate of strain, such as high aspect-ratios, tube shapes, extreme stretching, breaking-up, narrow trails and/or right or left shearing. This excludes strain portioning, recently discovered to occur in SiO2-rich magmas (Wright & Weinberg, 2009). The size and shape of bubbles do not describe any clear trend from DK1 to DK7 (Figs 10 and 11). In contrast, bubbles are severely stretched at the margins and base of lava flows, developing high strain rates and slightly deformed features in the central and shallower portions (Polacci & Papale, 1997; Polacci et al., 1999; Rust et al., 2003; Clemente et al., 2007). A further significant aspect concerns the fact that all DK samples come from the same depth of magma emplacement; that is, all the rocks solidified at the same pressure along the x direction. These bubble characteristics can reflect movement and deformation, not only along the vertical direction z but also along x and y, suggesting that the emplacement of magma below and near the DK original level occurred by non-laminar behaviour owing to transitional and/or turbulent regimes. In a laminar flow, the maximum length of bubbles must orient in the direction of transport, translating to the z axis for the studied dyke (Fig. 1). In parallel, the anisotropy of bubbles must increase from the central to outer fluid portions (Gonnerman & Manga, 2012; Mangan et al., 2014). These classical features of laminar flows are lacking in the dyke rocks. The textural and fabric characteristics observed for the majority of bubbles can be rationally explained by transitional and/or turbulent fluid conditions. This conclusion also validates the apparent discrepancies in 2D and 3D bubble contents measured for DK4 (Fig. 9). The polished surface of this sample displays, in an area of only 8 × 103 mm2, the coexistence of portions with bubbles having highly variable amounts, sizes, and shapes. In this surface, bubble shapes with high and low anisotropy can be explained by localized and variable strain rate; for instance, close to or far from vortices. It is also reasonable that the supposed transient and/or turbulent dynamics were limited or even lacking within a few tens of centimetres from the dyke margin, owing to the major effect of heat transport. The presence of transitional to turbulent regimes also limits temperature changes along the x and y dyke directions, at least during non-laminar dynamics (Spera, 1980; Huppert & Sparks, 1985; Spence & Turcotte, 1990; Carrigan, 2000). Physical constraints Thermometric estimates from dyke core to rim indicate that the early crystallization of plg and cpx occurred at 1119 ± 19°C and 1126 ± 26°C, respectively (Mollo et al., 2011). These comparable thermal conditions agree with the similar crystal dimensions (<0·2 mm) measured for plg and cpx across the dyke (Fig. 4; Supplementary Data Fig. S1–S7). Furthermore, the total H2O content dissolved in the magma has been estimated to be 1·6 ± 0·3 wt % at fO2 of NNO + 0·9 ± 0·9, where NNO is the nickel–nickel oxide buffer (Mollo et al., 2011). The emplacement pressures have been computed in this study by considering field observations (see the Supplementary Excel spreadsheets). Volcanic rocks at Mt Etna are trachybasalts emitted principally as dense lavas and secondarily as scoriae. We thus considered three densities of 2000, 2500, and 3000 kg m–3 to bracket the pressure conditions as a function of depth below the original dyke surface (100–300 m depth): P=ρ×d×g where ρ is the density (kg m–3) of the overlying rocks or dyke magma, d is the dyke width (x direction in Fig. 1), and g is the acceleration due to gravity (m s–2). The calculations envisage a maximum and conservative range of pressures between 2 MPa (ρ of 2000 kg m–3 at 100 m) and 9 MPa (ρ of 3000 kg m–3 at 300 m) (Fig. 12). Fig. 12. Open in new tabDownload slide Variation of physical parameters as a function of P. (Left) Calculated P as a function of estimated 100–300 m thick overlying rocks with variable density (ρrock). (Intermediate left) Modelled H2O solubility with SOLEX and H2O plagioclase saturation estimated with hygrometric model (Mollo et al., 2011). (Intermediate right) Modelled H2O vol. % exsolution in a closed system, at T = 1150°C and NNO + 1·8 using SOLEX and the range of measured bubbles (Tables 1 and 3). (Right) Estimated liquidus temperature by MELTS (Papale et al., 2006) between NNO and QFM + 3 (where QFM is quartz–fayalite–magnetite buffer) plus thermal ranges of the onset of crystallization (Mollo et al., 2011). The horizontal violet lines indicate the pressure range for the DK magma at its ancient depth below the ground. Fig. 12. Open in new tabDownload slide Variation of physical parameters as a function of P. (Left) Calculated P as a function of estimated 100–300 m thick overlying rocks with variable density (ρrock). (Intermediate left) Modelled H2O solubility with SOLEX and H2O plagioclase saturation estimated with hygrometric model (Mollo et al., 2011). (Intermediate right) Modelled H2O vol. % exsolution in a closed system, at T = 1150°C and NNO + 1·8 using SOLEX and the range of measured bubbles (Tables 1 and 3). (Right) Estimated liquidus temperature by MELTS (Papale et al., 2006) between NNO and QFM + 3 (where QFM is quartz–fayalite–magnetite buffer) plus thermal ranges of the onset of crystallization (Mollo et al., 2011). The horizontal violet lines indicate the pressure range for the DK magma at its ancient depth below the ground. The solubility of water in magma and the volume of exsolved gas phases have been computed using the models of Papale et al. (2006) and Solex (Whitam et al., 2012), assuming closed-system conditions. Three initial H2O amounts of 0·5, 1, and 2 wt % were considered together with 1000 ppm of CO2, 2000 ppm of S and 2000 ppm of Cl, typical for Etnean magmas (Spilliaert et al., 2006; Collins et al., 2009; Lanzafame et al., 2013). The results indicate that 0·5, 1, and 2 wt % H2O start to exsolve at about 10, 20, and 55 MPa, respectively (Fig. 12). To evaluate the rheological conditions plausible for dyke solidification and its fluid dynamics, the density change of magma has been simulated in a closed system as a function of P, 1 wt % H2O, 950–1150°C, and 0–40 wt % plg and 15 wt % cpx. The solubility model of Papale et al. (2006) was used to calculate the wt % and mol % of H2O dissolved and exsolved, whereas the density of magma was calculated using the Conflow program (Mastin, 2002). All these data were used as input parameters for the ideal gas law: V=R×n×T/P where V is volume (m3), n is moles (mol %), and R is the universal gas constant (see the Supplementary Excel spreadsheets). At 5·5 and 6·5 MPa, the gas phase is 10–30 vol. %, resembling the total amount of bubbles (Figs 12 and 13). This narrow range of P also corresponds to a rapid change in density, roughly from 1800 and 2400 kg m–3. It is worth noting that at P < 10 MPa the amount of gas is low or absent and the density of the magmatic suspension slightly changes by about 150 kg m–3 (the densities of plg, cpx, and melt are 2700, 3250, and 2600 kg m–3, respectively). In general, dykes intruding with a low overpressure can ascend by means of a density contrast between the magma and country-rocks (Carrigan, 2000; Jaupart, 2000; Gonnerman & Taisne, 2015). In the present case, if the magma was injected with a low overpressure, its ascent may be possible only for a wall-rock density >2400 kg m–3 (Fig. 13). Fig. 13. Open in new tabDownload slide Simulations of gas vs magmatic suspension ratio (left) and its density at relevant P (0–15 MPa), T (950–1150°C), H2O (1 wt % assuming a closed system), and amount of crystals (0–55% equals 40 wt % plg + 15 wt % cpx). The simulations were performed using the solubility model of Papale et al. (2006), which provides also gas–liquid partitioning and moles of exsolved H2O. These data were then used in the ideal gas law (see the text and Supplementary Excel spreadsheets). The density of the dyke magma is ≥2400 kg m–3 and rapidly decreases to 1800 kg m–3 to attain the measured range of bubbles. Fig. 13. Open in new tabDownload slide Simulations of gas vs magmatic suspension ratio (left) and its density at relevant P (0–15 MPa), T (950–1150°C), H2O (1 wt % assuming a closed system), and amount of crystals (0–55% equals 40 wt % plg + 15 wt % cpx). The simulations were performed using the solubility model of Papale et al. (2006), which provides also gas–liquid partitioning and moles of exsolved H2O. These data were then used in the ideal gas law (see the text and Supplementary Excel spreadsheets). The density of the dyke magma is ≥2400 kg m–3 and rapidly decreases to 1800 kg m–3 to attain the measured range of bubbles. A further calculation focused on the liquidus temperature considering 0, 1, and 2 wt % H2O, up to the limit of pressure required to retain water dissolved in the magma at fO2 of NNO + 1. This set of numerical results is compared with the saturation temperatures of plg and cpx (Mollo et al., 2011). Under anhydrous conditions the liquidus temperature corresponds to 1190–1200°C, whereas it decreases to 1130 and 1075°C at 1 and 2 wt % H2O, respectively. The computation with 2 wt % H2O does not match at all with the saturation temperatures of plg and cpx crystallization (Fig. 12). The computation with 1 wt % H2O produces up to 30 vol. % at 10–16 MPa, corresponding to a depth of 350–600 m for a 2500 kg m–3 density (i.e. below the dyke magma pressure level of 2–9 MPa). Also, 1 wt % H2O originally dissolved in magma means that 0·25–0·5 wt % H2O exsolved at pressure ≥2–9 MPa. Thus, the shallow magma contained only 0·5–0·75 wt % H2O (Fig. 12), in agreement with the water concentration estimated to be in equilibrium with the crystals at the onset of plg and cpx crystallization (Mollo et al., 2011). Up to 30 vol. % of bubbles formed before the magma attained pressures of 2–9 MPa (Fig. 12). In turn, transient to turbulent regimes recorded by most of the bubbles occurred when the magma was at pressures of between 9 and 16 MPa (Fig. 12). A non-laminar dynamic flow probably took place also at P < 16 MPa, but it is not detectable owing to the lack of phases at P ≥ 16 MPa. The computation with 0·5 wt % H2O produces similar results but at pressures lower than those determined using 1 wt % H2O. When the magma attained a pressure level between 2 and 9 MPa, 1 wt % H2O further exsolved (Fig. 12) accompanied by a temperature decrease owing to the contact with the cold wall-rock. Both decompression and cooling caused rapid and massive crystallization, with formation of new cpx and plg nuclei or overgrowths on early formed crystals by attachment processes (Iezzi et al., 2008, 2011, 2014). All these aspects favoured an abrupt increase of crystals in the magma, decelerating or even arresting the flow. The last step of crystallization occurred at T < 1100°C as recorded by plg and cpx crystal rims (Mollo et al., 2011). The retrieved magma densities have been used for the calculation of the Reynolds numbers, through the equation Re=ρ×d×v/η where ρ is density of the magma between 1800 kg m–3 (30 vol. % bubbles) and 2500 kg m–3 (free of crystals and with a few bubbles), d is the dyke width, v is the average ascent velocity and η is the melt viscosity. This last parameter was calculated using the equation of Giordano et al. (2008) at 0·5 and 1 wt % H2O and 1000–1200°C, whereas the effect of crystals on viscosity has been modelled using data from Vona et al. (2011), considering crystals with a 3:1 aspect ratio and a 0·1 s–1 strain rate. The progressive differentiation of the residual melt as a function of crystals and bubbles has not been considered, given that this strategy is clearly conservative owing to the fact that melt viscosity increases with increasing SiO2 of the melt (Gonnerman & Manga, 2012; Mangan et al., 2014). Viscosity paths are very similar, with only a weak downward shift at 0·5 wt % H2O (Fig. 14). Overall, the viscosity increases by about two orders of magnitude when the crystal content increases from 0 to 40 vol. %, but the most important changes are observed for crystallization up to 50 vol. % (Fig. 14). Fig. 14. Open in new tabDownload slide Bottom: simulations of viscosity for DK magmatic suspension with 1 wt % (left column) and 0·5 wt % (right column) of dissolved water, at 1200 and 1000°C at a moderate strain rate, for crystal contents between 0 and 50 vol. %. These calculated viscosities were used as input data to calculate the Reynolds number (top and middle row) for a dyke width of 4·3 m using two densities (ρ) of 1800 and 2500 kg m–3 (from Fig. 13) for four ascent velocities. The simulation path at 1000°C invariably attains a Reynolds number of only some tens to a few hundreds. The end of laminar regime is fixed at 1000, and a full turbulent regime is arbitrarily set above 2000 (see text). Fig. 14. Open in new tabDownload slide Bottom: simulations of viscosity for DK magmatic suspension with 1 wt % (left column) and 0·5 wt % (right column) of dissolved water, at 1200 and 1000°C at a moderate strain rate, for crystal contents between 0 and 50 vol. %. These calculated viscosities were used as input data to calculate the Reynolds number (top and middle row) for a dyke width of 4·3 m using two densities (ρ) of 1800 and 2500 kg m–3 (from Fig. 13) for four ascent velocities. The simulation path at 1000°C invariably attains a Reynolds number of only some tens to a few hundreds. The end of laminar regime is fixed at 1000, and a full turbulent regime is arbitrarily set above 2000 (see text). These viscosity values were translated to Re numbers at 1800 and 2500 kg m–3, considering five ascent velocities of 0·1, 1, 2·5, 5, and 10 m s–1 (Fig. 14), reproducing the ascent rates estimated for Etnean magmas (Mollo et al., 2015a). Critical Re numbers were set at 1000 and 2000 for shifting from laminar to transitional and from transitional to turbulent regimes, respectively (Huppert & Sparks, 1985; Emerman & Turcotte, 1986; Spence & Turcotte, 1990). Results show that, at T < 1200°C and density of 1800 kg m–3, an ascent velocity >2·5 m s–1 is sufficient to pierce the transitional field when the crystal content is <10 vol. % and H2O is 0·5–1 wt % (Fig. 14). At these conditions, a turbulent regime is triggered for an ascent velocity >5 m s–1 (Fig. 14). At lower values, non-laminar regimes are produced when the temperature decreases and the crystal content increases (Figs 13 and 14). These numerical results rationally support the transient and/or turbulent regimes deduced from the textural and fabric characteristics of bubbles (Table 3; Figs 4,6 and 9; Supplementary Data Fig. S1–S7). The complex history of the dyke magma proposed here has been summarized in Fig. 15, drawing attention to the most important interpreted steps occurred during its emplacement. Fig. 15. Open in new tabDownload slide Schematic illustration summarizing the most important steps that drive dyke emplacement. At P > 20 MPa the DK magma is free of crystals and bubbles, containing only 1 wt % of H2O. A non-laminar fluid flow develops (cyan arrows). Between 20 and 10 MPa, H2O begins to exsolve, forming up to 30 vol. % of bubbles (tiny circular to large oblate white bubbles) under a transitional to turbulent regime. Decompression-induced degassing leads to the formation of plg and cpx cores (tiny red and yellow crystals). The crystallization reduces the ascent rate of the magma and shifts the flow regime to laminar. Between 9 and 2 MPa, plg and cpx continue to grow under the effect of cooling rate. The crystal size increases to 0·2 mm, halting the flow of magma. Fig. 15. Open in new tabDownload slide Schematic illustration summarizing the most important steps that drive dyke emplacement. At P > 20 MPa the DK magma is free of crystals and bubbles, containing only 1 wt % of H2O. A non-laminar fluid flow develops (cyan arrows). Between 20 and 10 MPa, H2O begins to exsolve, forming up to 30 vol. % of bubbles (tiny circular to large oblate white bubbles) under a transitional to turbulent regime. Decompression-induced degassing leads to the formation of plg and cpx cores (tiny red and yellow crystals). The crystallization reduces the ascent rate of the magma and shifts the flow regime to laminar. Between 9 and 2 MPa, plg and cpx continue to grow under the effect of cooling rate. The crystal size increases to 0·2 mm, halting the flow of magma. CONCLUSIONS This study deals with the physicochemical conditions driving the solidification of a dyke at Mt Etna volcano. At P > 10 MPa, the original magma feeding the intrusion was virtually crystal-free, with a dissolved H2O content close to 1 wt %; at P < 10 MPa, abundant degassing-induced crystallization took place via H2O exsolution. Crystals continued to grow under the effect of an increasing cooling rate from the innermost dyke portion to the wall-rocks. The ascent velocity of magma was of the order of a few m s–1, with a transitional to turbulent regime before the growth of minerals. Thus, dyke emplacement occurred at conditions close to the liquidus surface of the magma. Under such circumstances, the transition to turbulent regimes determined a more uniform distribution of the ascent velocity and random variation of the strain rate. Comparison between the 2D and 3D data for bubbles indicates that common 2D textures give confident quantification of the amount and number per area of bubbles. Conversely, actual bubble orientations are identified only by 3D textures, despite the overall mathematical description of bubble shapes requiring both 2D and 3D quantitative approaches. The occurrence of non-laminar fluid-dynamic regimes is indicated by the following: (1) the presence of bubble-rich, -poor and-free patches with their irregular amounts through the dyke thickness; (2) the absence of any bubble size, shape and fabric relations moving from outer to inner DK portions; (3) the observations of eddies and vortices. Transitional to turbulent regimes have been possibly recorded owing to rapid change in viscosity, which has frozen in the early deformation of bubbles. Further analysis by phase-contrast synchrotron radiation X-ray microtomography will allow investigation of the 3D morphology and texture of plagioclase, clinopyroxene and olivine phases in the same dyke sample. It can be concluded that similar investigations on Etnean dykes may provide novel insights into the fluid dynamics, transport regimes, and ascent velocities of the magmas, with valuable ramifications for geophysical and hazard modelling. ACKNOWLEDGEMENTS The authors are grateful to M. D. Higgins, F. Arzilli and an anonymous reviewer for their valuable comments and suggestions, which improved the clarity and significance of this study. The editor M. Wilson is warmly acknowledged for her editorial handling. 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TI - Solidification and Turbulence (Non-laminar) during Magma Ascent: Insights from 2D and 3D Analyses of Bubbles and Minerals in an Etnean Dyke
JO - Journal of Petrology
DO - 10.1093/petrology/egx063
DA - 2017-08-01
UR - https://www.deepdyve.com/lp/oxford-university-press/solidification-and-turbulence-non-laminar-during-magma-ascent-insights-SJzIgNdN6n
SP - 1511
VL - 58
IS - 8
DP - DeepDyve
ER -