Investigation of a Monturaqui Impactite by Means of Bi-Modal X-Ray and Neutron Tomography

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Journal of Imaging

Article Investigation of a Monturaqui Impactite by Means of Bi-Modal X-ray and Neutron Tomography

Anna Fedrigo 1,2,3,* ID , Kasper Marstal 3,4, Christian Bender Koch 5, Vedrana Andersen Dahl 3, Anders Bjorholm Dahl 3, Mark Lyksborg 3, Carsten Gundlach 6, Frédéric Ott 7 and Markus Strobl 2,8,9 ID

1 Science and Technology Facility Council, ISIS Neutron Source, Didcot OX11 0QX, UK 2 European Spallation Source ESS ERIC, SE-221 00 Lund, Sweden; [email protected] 3 DTU Compute, DK-2800 Kgs Lyngby, Denmark; [email protected] (K.M.); [email protected] (V.A.D.); [email protected] (A.B.D.); [email protected] (M.L.) 4 ERASMUS MC, Biomedical Imaging Group, 3000 CA Rotterdam, The Netherlands 5 Department of Chemistry, University of Copenhagen, 2100 Copenhagen, Denmark; [email protected] 6 DTU Physics, 2800 Kgs Lyngby, Denmark; [email protected] 7 Laboratoire Léon Brillouin, CEA-CNRS, 91191 Gif-sur-Yvette CEDEX, France; [email protected] 8 Nano-Science Centre, Niels Bohr Institute, University of Copenhagen, 2100 Copenhagen, Denmark 9 Paul Scherrer Institut, 5232 Villigen, Sweden * Correspondence: [email protected]; Tel.: +44-123-544-5900

Received: 21 March 2018; Accepted: 12 May 2018; Published: 18 May 2018

Abstract: X-ray and neutron tomography are applied as a bi-modal approach for the 3D characterisation of a Monturaqui impactite formed by shock metamorphism during the impact of an iron meteorite with the target rocks in the Monturaqui crater (Chile). The particular impactite exhibits structural heterogeneities on many length scales: its composition is dominated by silicate-based glassy and crystalline materials with voids and Fe/Ni-metal and oxihydroxides particles generally smaller than 1 mm in diameter. The non-destructive investigation allowed us to apply a novel bi-modal imaging approach that provides a more detailed and quantitative understanding of the structural and chemical composition compared to standard single mode imaging methods, as X-ray and neutron interaction with matter results in different attenuation coefﬁcients with a non-linear relation. The X-ray and neutron data sets have been registered, and used for material segmentation, porosity and metallic content characterization. The bimodal data enabled the segmentation of a large number of different materials, their morphology as well as distribution in the specimen including the quantiﬁcation of volume fractions. The 3D data revealed an evaporite type of material in the impactite not noticed in previous studies. The present study is exemplary in demonstrating the potential for non-destructive characterisation of key features of complex multi-phase objects such as impactites.

Keywords: neutron imaging; X-ray imaging; multimodal imaging; bimodal imaging; computed tomography; impactite; Monturaqui

1. Introduction X-ray computed tomography (CT) has long demonstrated its potential as a non-destructive analysis and visualisation method in geoscience, with applications extending from palaeontology, to soil research, oil and gas production, among others [1–3]. X-ray CT has been complemented by neutron radiography and neutron tomography, expanding the range of applications to e.g., the study of denser materials and larger samples volumes, and to samples with light elements dispersed in

J. Imaging 2018, 4, 72; doi:10.3390/jimaging4050072 www.mdpi.com/journal/jimaging J. Imaging 2018, 4, 72 2 of 24 a matrix of heavy elements [4–7]. The application of multimodal imaging has gained in popularity in the recent years and researchers have come to realize that the complementary abilities of these two well-established imaging modalities could be exploited more efficiently by using them in tandem. This has even led to the implementation/design of simultaneous X-ray and neutron imaging instruments, such as ICON at the neutron spallation source SINQ (CH) [8], NeXT system at the NIST Centre for Neutron Research (USA) [9], and the NeXT-Grenoble at the ILL reactor in Grenoble (FR) [10]. The combined use of X-rays and neutrons provides additional element-dependent information since the physics of radiation interaction with the elements constituting the sample differs [11]: X-rays interact mainly with the electrons of an atom (the more electrons an atom has the higher the probability of interaction), whereas neutrons are electrically neutral particles that interact with the atomic nuclei. Neutrons are very sensitive to some light atoms, most notably hydrogen which has a scattering cross-section typically one order of magnitude larger than that of other atoms [11]. Therefore, water and hydroxyls associated with minerals show low contrast when using X-rays, but can readily be visualized by neutrons. Dense materials, including most metals, instead exhibit strong X-ray attenuation but are relatively transparent when using neutrons [11]. In favourable cases, neutron imaging helps even to differentiate between isotopes or neighbouring elements of the periodic table [11]. Here, we present a 3D imaging investigation of a weathered impactite rock from the Monturaqui meteorite impact crater in northern Chile. The impactite is a shock-metamorphosed rock resulting from the collision of an iron meteorite and terrestrial silicate rocks. Such collisions cause irreversible changes in the materials due to the formation and propagation of a shock wave in both the impactor and the target. For terrestrial planets, the impact can induce pressures up to several 100 GPa and temperatures up to thousands of degrees Celsius [12]. A frequently observed feature of impactites formed by iron meteorites is the incorporation of fragments and spherules of the meteorite into the impactite glass. Pores, vesicles and cracks are also a prominent characteristic of impactites. Both metallic spherules and vesicles typically range in size from µm to cm, therefore it is possible to resolve these objects at most sizes. Cracks and pores in the impactite may at later stages allow oxygen and water access to the metal, resulting in corrosion and the internal transport and precipitation of corrosion products in cracks and voids. Since weathering products typically contain hydrogen—or are associated with water adsorbed to surfaces—they will be particular distinct in neutron imaging. The resulting impactite rocks represent chemical disequilibrium products where vitreous phases are mixed with shocked and unshocked lithic fragments and vaporised/condensed metal deriving from the meteorite, forming vesiculated heterogeneous aggregates. While previous 2D studies [13] have identified most of the constituents in the impactite, major shortcomings exist concerning quantification of the constituents and their relative position within the impactite. This information is prerequisite in studies of the interactions of the constituents during impactite formation and weathering and would ultimately give a detailed understanding of the impactite formation processes. Unlike terrestrial matter, iron meteorites—and consequently the corresponding crater and its surrounding ejecta blanket—are relatively rich in platinum-group metals (e.g., Ir, Pt, Re) which are used as markers to identify terrestrial impact craters [14]. Iridium concentration anomalies show a strong correlation to meteoritic events [15,16], but they are not truly unequivocal factors. Instead, the co-occurrence of a vesiculated partly melted matrix (the impactite rock) and metallic projectile droplets of meteoric origin (FeNi micro-spherules) represent a peculiar feature specific to meteoritic events only [17]. The present case-study shows the extent of information that can be elicited through a non-invasive approach combining X-ray and neutron tomography. This work represents a novel example where these two techniques have been methodically correlated for analysis. The focus of this study is to quantify and differentiate the different lithologies. Since the theoretical X-ray and neutron attenuation coefficients of a mineral can be calculated, it is possible to make predictions concerning its visibility and detectability inside the reconstructed tomographic volumes. X-ray CT, with its relatively high J. Imaging 2018, 4, 72 3 of 24 resolution and contrast, was applied for morphological studies (e.g., porosity) and quantification of metallic spherules. Neutrons were used as they provide high contrast for hydrogen in metal oxides and for platinum-group and noble metals (e.g., Cu, Re, Ir, Pt, Au), which are originally present as trace elements in iron meteorites. Both techniques provide important 3D information on the internal structure of materials. Results obtained are compared to current literature and to results obtained from standard destructive analysis on analogous Monturaqui impactites. This study has a two-fold aim. First, it is well suited to exploit approaches of bi-modal visualisation and analyses to a detailed, multi-component object, as a model system for corresponding studies and strategies. Second, the study aims to investigate the full potential of non-destructive imaging applied to this class of geological samples, to help inform future studies and build an understanding of where and how far non-destructive imaging can replace destructive investigations.

2. Materials and Methods

2.1. Monturaqui Crater and Impactite Monturaqui is an old (663,000 ± 90,000 years [18]) small-sized crater (360–380 m across and 21–39 m deep) situated at an altitude of 3100 m in the Atacama Desert region of the Andes [19]. The region is currently one of the most arid in the world, with an annual precipitation of less than 1 mm [20], generally limiting the extent of water-based weathering. The target rocks of the impact comprise of granite rock, overlaid by a thin sheet of ignimbrite from adjacent volcanoes [19]. Ignimbrites are pyroclastic rocks containing angular clasts of ash and lapilli tuff ranging in size from a few cm to over 50 cm. The ash and tuff contain pumice clasts as well as crystals of plagioclase feldspar, quartz, and biotite [21]. The Monturaqui impact event has been modelled [22] estimating an impactor of ~14.92 m in diameter with a density of 6.31 g/cm3. The energy of the impact produced ~6.8 × 106 m3 of impact melt of ~2.63 g/cm3, material that was ejected as far as 11.49 km from the impact. While individual metallic fragments detached from the meteorite and deposited on the surface were almost completely transformed over the years into ﬁne grained iron (oxi)hydroxides (mainly goethite and maghemite), impactites host a small—but characteristic—volume of particles of metallic Fe-Ni (some having additional FeS) embedded in glass and thereby protected from corrosion [23]. Since the discovery of the crater in 1962, Monturaqui impactites have been extensively studied by destructive methods: petrography in particular, but also scanning electron microscope (SEM), electron microprobe (EMP) analysis, X-ray ﬂuorescence (XRF), inductively coupled plasma mass spectrometry (ICP-MS) analysis, and Mössbauer spectroscopy [18,23–28]. These analyses demonstrated the occurrence of FeNi spherules and related weathering oxides, and showed different structural components derived from the original target rocks. The glass component of the Monturaqui impactites is formed from the non-modal melting of granitic minerals, the melting of the ignimbrite, or a combination of the two [18], and possibly the addition of Fe and Ni from the meteorite. From the analysis of the melted minerals and of the planar deformation features of plagioclase and quartz grains, the impact temperatures were estimated to be <1700 ◦C and pressures ~45–55 GPa [29]. Monturaqui impactites are vesiculated and mainly of sub-rounded morphology, in part appearing as though formed by the cladding of different materials, but also exhibiting evidence of explosive disruption (part of vesicles constituting the exterior surfaces, see Figure1). They are heterogeneous in colour and texture. For this study we have selected a piece of Monturaqui impactite (collected by Dr. V.F. Buchwald) of approximately 5 × 3 × 3 cm3 (see Figure1). This piece of impactite exhibits the characteristic vesicles, oxides, and metallic inclusions. The metallic spheres are generally scattered in the impactite glass and can range in size from less than 1 µm to more than 2 mm diameter. A previous study [30] from a CT reconstruction of a piece of impact melt estimated the volume occupied by the spherules to ~4.6% of the total. The spherules have a higher Ni content compared to the bulk composition of the iron meteorite [23,25], but the composition J. Imaging 2018, 4, 72 4 of 24 varies. The ratio of Ni to Fe ranges from 5–10% Ni (as kamacite), up to 20–74% Ni (as taenite) [25,28]. Ni-rich spherules are more resistant to corrosion [31]. The spherules are also enriched in Co with J.respect Imaging to2018 the, 4, x meteorite FOR PEER REVIEW [15]. Co is ~3% of Ni or higher [30], 2 to 10 times more than the original4 of 23 meteorite [25]. In addition, spherules can also contain varying amounts of sulphur, in the form of forminterstitial of interstitial troilite (FeS)troilite and (FeS) pyrrhotite and pyrrhotite (Fe(1−x) (FeS).(1 This−x)S). sulphurThis sulphur is very is very likely likely originating originating from from the themeteorite meteorite as the as targetthe target rocks rocks are essentiallyare essentially sulphide-free sulphide-free [23]. [23].

Figure 1. The weathered Monturaqui impactite used in this study, similar to the material described in [23]. [23].

2.2. X-ray and Neutron Computed Tomography (CT)(CT) The combinationcombination of of neutron neutron and and X-ray X-ray computed computed tomography tomography is used is asused a non-destructive as a non-destructive method methodof studying of studying the structural the structural details and details the compositionand the composition of the impactites. of the impactites. When a a heterogeneous heterogeneous sample sample is irradiated is irradiated by X-rays by X-rays or neutrons, or neutrons, the incident the beam incident is attenuated beam is accordingattenuated to according the attenuation to the attenuationproperties and properties the thickn andess the of the thickness materials of theit transverses materials it[11]. transverses For a mono- [11]. energeticFor a mono-energetic beam and a beamsample and containing a sample containingi (homogenous)i (homogenous) materials, materials,the attenuation the attenuation follows the follows Beer- Lambertthe Beer-Lambert law: law: −∑ µ d I = I e − μdi i = 0  ii , (1) IIe0 (1) , −1 where I is the transmitted intensity, I0 is the intensity of the incident beam, µi (cm ) is the linear −1 whereattenuation I is the coefficient transmitted of every intensity, material I0 isi beingthe intensity traversed, of the and incidentdi (cm) isbeam, the thickness, μi (cm ) i.e.,is the the linear path attenuationlength of the coefficient radiation of through every material ii .being The linear traversed, attenuation and di (cm) coefficient is the µthickness,i is a material-specific i.e., the path quantitylength of andthe isradiation proportional through toits material density: i. The linear attenuation coefficient μi is a material-specific quantity and is proportional to its density: ρi NA µi = ρ N σi, (2) μσ= iAM iii , (2) Mi 3 23 −2 where ρi is the mass density (g/cm ), NA is the Avogadro constant (6.022 × 10 mol ), Mi is the where ρi is the mass density (g/cm3), NA is the Avogadro−24 2 constant (6.022 × 1023 mol−2), Mi is the atomic atomic mass (g), and σi is the total cross-section (10 cm ) of the material i and accounts for absorption mass (g), and σi is the total cross-section (10−24 cm2) of the material i and accounts for absorption and and scattering. For X-rays σi includes the effects of photoelectric attenuation and incoherent Compton scattering. For X-rays σi includes the effects of photoelectric attenuation and incoherent Compton scattering (and coherent Rayleigh scattering), while for neutrons σi includes absorption and coherent scattering (and coherent Rayleigh scattering), while for neutrons σi includes absorption and coherent and incoherent scattering. For both X-rays and neutrons, σi depends on the energy of the radiation and incoherent scattering. For both X-rays and neutrons, σi depends on the energy of the radiation and on the atomic number Z. and on the atomic number Z. For silica-dominated geological samples measured using standard X-ray laboratory sources, the For silica-dominated geological samples measured using standard X-ray laboratory sources, the dominant attenuation process of X-rays below 50–60 keV is photoelectric absorption (∝ Z4–5)[32,33], dominant attenuation process of X-rays below 50–60 keV is photoelectric absorption (∝ Z4–5) [32,33], whereas at higher energy Compton scattering predominates (∝ Z, or to first order ∝ ρ). This means whereas at higher energy Compton scattering predominates (∝ Z, or to first order ∝ ρ). This means that low-energy X-rays are more sensitive to differences in composition (e.g., for materials with similar that low-energy X-rays are more sensitive to differences in composition (e.g., for materials with similar mass density) than high-energy X-rays [34]. However, the former are also more easily attenuated, mass density) than high-energy X-rays [34]. However, the former are also more easily attenuated, limiting the thickness of high-density material that can be penetrated. limiting the thickness of high-density material that can be penetrated. Neutrons, having no charge, interact directly with atomic nuclei and can therefore travel deep into Neutrons, having no charge, interact directly with atomic nuclei and can therefore travel deep matter [11]; they can either be scattered in billiard-ball-like collisions or absorbed, changing the target into matter [11]; they can either be scattered in billiard-ball-like collisions or absorbed, changing the target atom into a different isotope. The most important processes for cold and thermal neutrons are nuclear absorption and elastic scattering [11]. Interaction with high-energy neutrons will not be considered further here as it is less well suited to this specific case study. The neutron attenuation coefficients have no systematic relation to the atomic number of the material of interaction; neighbouring elements in the periodic system or even isotopes of the same element can exhibit large

J. Imaging 2018, 4, 72 5 of 24 atom into a different isotope. The most important processes for cold and thermal neutrons are nuclear absorption and elastic scattering [11]. Interaction with high-energy neutrons will not be considered further here as it is less well suited to this specific case study. The neutron attenuation coefficients have no systematic relation to the atomic number of the material of interaction; neighbouring elements in the periodic system or even isotopes of the same element can exhibit large differences in neutron attenuation [11]. This irregular behaviour can help achieve contrast where X-rays provide similar absorption properties. The principle of computed tomography, for both X-rays and neutrons, is that by measuring the attenuation of radiation traversing a sample at different angles, it is possible to compute volumetric data, in which an attenuation coefficient is calculated and assigned for every point in the volume. Projections are recorded over 360◦ by flat 2D CCD based detectors coupled with a scintillator material which converts the transmitted radiation into visible light. The most common volume reconstruction algorithms are independent of the radiation used and are well documented [35–37]. X-ray CT was carried out at the 3D Imaging Centre, DTU Lyngby (DK), using a Nikon XT H 225 scanner with tungsten target and applying an acceleration voltage of 200 kVp (479 µA current). White beam neutron tomography was carried out at the IMAGINE beamline [38], the cold neutron imaging facility at the Laboratoire Léon Brillouin CEA/CNRS (FR). The respective values for the instrumental set-ups are reported in Table1. Although meteoritic iron contains cobalt as a major element, the neutron investigation caused no significant activation of the sample, and the radiation intensity fell below the safety thresholds in about 1 week. In fact, the naturally occurring Co isotope, 59 Co, is characterised by a very high neutron absorption cross section σabs (σabs ≈ 82.7 barns for neutrons of 4 Å); by neutron capture 59Co transforms into radioactive 60Co, which decays to 60Ni with a half-life of T 1 = 5.2714 years. 2 X-ray CT volume reconstruction was performed using the X-TEK 3D CT Pro developed by Nikon Metrology, while neutron projections were processed using the Octopus software package [39]. The reconstruction method is based on the filtered back-projection algorithm [40], considering cone-beam and parallel-beam geometry for X-ray and neutron tomography, respectively. The stacks of images obtained represent three-dimensional arrays of the linear attenuation coefficients for X-rays and neutrons. During reconstruction, the X-ray attenuation coefficients were rescaled using a linear transformation so as to correspond to mass density values, similar to the Hounsfield units commonly used in medical imaging. This calibration was possible because above 60 keV we assume that X-rays interact only by Compton scattering, which depends on electron density Ne (Ne is roughly ∝ Z). Having scaled to mass density values it is possible to identify the lithic phases and compare the attenuation coefficients to their theoretical density values. The applied scaling was verified using the iron rod sample holder, giving a mean X-rays attenuation value of 7.9 ± 0.8 g/cm3, compared with the iron density of 7.87 g/cm3. The relatively large error is partly the result of noisy projections due to scattering and the use of a polychromatic source. The same scaling procedure could not be applied to the neutron data as there is no proportionality between the neutron attenuation coefficients and the atomic number of the materials. X-ray laboratory sources, and polychromatic neutron imaging instruments, produce beams with a continuous energy spectrum. Energy-dependent attenuations mean less energetic X-rays are more likely attenuated, or even fully absorbed, when traveling through dense materials, producing so-called beam hardening (BH) effects. These were reduced by using an aluminium filter during acquisition and by applying a BH correction pre-set provided by the reconstruction software (X-TEK 3D CT Pro). J. Imaging 2018, 4, 72 6 of 24

Table 1. Instrumental parameters set-ups for X-ray and neutron measurements.

Imaging Set-up X-ray Neutron Pixel size (µm) 33.1 75.0 Projections (n◦) 3143 360 Magniﬁcation 1.32 1 CCD size (pixels) 2048 × 2048 2560 × 2160 Field of view (mm) 150 × 150 100 × 100 Source spectrum 200 kVp (479 µA current) cold neutrons (peaked at ~4 Å) Filter Al, 0.250 mm thick none ◦ J. Imaging 2018Rotating, 4, x FORangle PEER (REVIEW) 0–360 0–360 6 of 23

2.3. Image Processing X-ray CT CT contrast contrast between between high high and low and Z-dominate low Z-dominatedd materials materials provided provideddetail on the detail morphology on the morphologyof the impactite. of theThis impactite. data-set was This used data-set to define was vesicles used toand deﬁne metallic vesicles spherules and metallicand perform spherules a size andvariability perform analysis a size of variability these objects. analysis Neutron of these imag objects.ing provided Neutron complementary imaging provided attenuation complementary information attenuationof the material information matrix and of inclusions. the material The matrix combinat andion inclusions. of the two The data-sets combination was used of the for two thedata-sets material wassegmentation, used for the which material was segmentation,performed in Matlab. which was performed in Matlab.

2.3.1. Image Registration When a single imaging method cannot provide sufficientsufficient contrast to resolve the composition of the imaged object object from from its its histogram, histogram, it itis ispossible possible to totake take advantage advantage of the of the spatial spatial correlations correlations of the of theintensity intensity distributions distributions from from multiple multiple registered registered data-sets data-sets under under different different modalities. modalities. Plotting Plotting thethe attenuation coefficients coefficients given given by by the the two two modalities modalities in in a abivariate bivariate histogram histogram may may aid aid in inthe the separation separation of ofphases phases with with distinct distinct compositions, compositions, forming forming ‘clusters’ ‘clusters’ of intensity of intensity within within the bivariate the bivariate histogram histogram plot. plot. To achieveachieve this,this, wewe havehave manuallymanually pre-aligned thethe two data sets (through rotations and reslice functions) in in FIJI FIJI [41] [41] and and registered registered them them (sca (scaledled and and aligned aligned on on a common a common coordinate coordinate system) system) in inthe the Statistical Statistical Parametric Parametric Mapping Mapping SPM8 SPM8 software software package package [42] [42 ]using using a a rigid rigid transform transform and the normalised mutual information similarity metric [[43,44].43,44]. Rigid Rigid body registration only allows for rotations and translations, and therefore does not deform the objects. Normalised mutual information is one one of of the the most most common common image image similarity similarity metrics metrics for for multi-modal multi-modal registration registration [45]. [ 45The]. X-ray The X-ray data dataset was set used was as used fixed as volume fixed volume (Reference (Reference Image) Image) to which to the which neutron the neutron volume volume(Float Image) (Float was Image) co- wasregistered. co-registered. An example An example slice from slice fromthe two the twodatasets datasets is shown is shown in inFigure Figure 2,2 ,before before and and afterafter thethe registration transformation.transformation. While the transformation appliedapplied toto the Float Image does not deform the object, the difference in the appearance of the slicesslices from the Float and thethe Co-RegisteredCo-Registered images is due to the fact that the transformation isis appliedapplied inin 3D.3D.

Figure 2. Example of X-ray (Reference Image) and neutron slices before (Float Image) and after (Co- Figure 2. Example of X-ray (Reference Image) and neutron slices before (Float Image) and after Registered Image) rigid body registration of the 3D volumes. (Co-Registered Image) rigid body registration of the 3D volumes.

Because of the higher resolution achieved in the X-ray scan (see Table 1), the neutron volume (float image) was up-sampled in order to match the voxel dimensions of the X-ray volume (reference image). Although this process may introduce errors (e.g., in the material segmentation), it preserves the morphological details of the sample. The resulting volume dimensions are 1072 × 1610 × 1061 voxels of 33.1 µm size, for a total volume of 3.54 × 5.33 × 3.51 cm3. The registration process allowed for voxel-wise comparison between the two data sets. In addition, in order to simultaneously visualise both attenuation coefficients, we converted the grey scale values by merging them into false colour images, using JET and RGB colour models.

2.3.2. Materials Segmentation Image segmentation was performed by classifying the voxels in different material classes depending on their bi-modal grey scale values. In order to focus the segmentation on the impactite only, we used the X-ray volume (see Figure 3a) to exclude air and vesicles by grouping them into the

J. Imaging 2018, 4, x FOR PEER REVIEW 7 of 23

background. In doing so, all vesicles smaller than the achieved resolution contribute to a density J.reduction Imaging 2018 of, 4, the 72 material in consideration. The background mask thus created was used to estimate7 of 24 porosity in the object (see Section 3.3.1). X-ray imaging for lithic samples generally provides a high contrast between an object and voids. However,Because the of occurrence the higher resolutionof voxels, representing achieved in thehighly-vesiculated X-ray scan (see Tablesilicate-dominated1), the neutron volumes volume of (ﬂoatmaterials image) with was a up-sampledlow average in density order to(see match light the grey voxel areas dimensions in Figure of3a the showing X-ray volumethe negative (reference of the image).attenuation, Although where this white process corresponds may introduce to no attenuation errors (e.g., and in the black material to high segmentation), attenuation), did it preserves not allow thethe morphological use of a simple details threshold. of the The sample. low-density, The resulting highly-vesiculated volume dimensions phase is are in 1072fact characterised× 1610 × 1061 by 3 voxelsthe same of 33.1 greyscaleµm size, values for a totalof some volume of the of 3.54edge× voxels5.33 × (gradient3.51 cm .between The registration the object process and the allowed empty forpores) voxel-wise and inner comparison vesicles. between the two data sets. InThe addition, impactite in order mask to was simultaneously created through visualise dual both intensity attenuation thresholding coefﬁcients, (see we Figure converted 3b), with the greythresholding scale values values by merging computed them by intominimising false colour the intrac images,lass using variance JET and[46]. RGB Figure colour 3c shows, models. in white, the voxels below the first threshold representing the air (background), in black, the foreground object 2.3.2. Materials Segmentation representing the voxels above the second threshold, and in grey the unassigned voxels with values in between.Image The segmentation unassigned voxels was performed were treated by separa classifyingtely by theapplying voxels morphological in different transformations material classes to dependingenhance the on image their bi-modal contrast grey(top-hat scale filter), values. which In order acted to like focus a high-pass the segmentation filter to onextract the impactitethe bright only,areas we of used the theimage. X-ray This volume approach (see Figureallowed3a) us to excludeto assign air inner and vesiclesvesicles byand grouping edge voxels them to into the thebackground background. representing In doing so, air, all while vesicles keeping smaller the than low-density the achieved phases resolution in the contributeforeground to object. a density The reductionresulting ofmask the materialis shown in in consideration. Figure 3d, where The background the impactite mask is thusvisualised created in was black used and to estimatethe air is porosityrepresented in the in object white. (see Section 3.3.1).

(a) (b)

FigureFigure 3. 3.(a )(a Corresponding) Corresponding slices slices (z = 673)(z = from673) X-rayfrom volumeX-ray volume used as used a starting as a pointstarting for thepoint impactite for the maskimpactite creation; mask (b) Histogramcreation; ( ofb) theHistogram X-ray volume of the with X-ray the twovolume thresholds with usedthe two for segmenting thresholds theused solid for materialsegmenting (foreground) the solid from material air (background); (foreground) (c )from Dual air intensity (background); thresholding (c) Dual model intensity with background thresholding in white,model low-density with background material in and white, edges low-density (unassigned mate voxels)rial inand grey, edges and (unassigned foreground objectvoxels) (representing in grey, and theforeground voxels above object the second(representing threshold) the invoxels black; above (d) Final the masksecond in blackthreshold) selecting in black; impactite (d) (foreground).Final mask in X-rayblack attenuation selecting impactite values above (foreground). 7.9 have been X-ray truncated attenuation for visualizationvalues above purposes. 7.9 have been truncated for visualization purposes. X-ray imaging for lithic samples generally provides a high contrast between an object and voids.

However, the occurrence of voxels, representing highly-vesiculated silicate-dominated volumes of materials with a low average density (see light grey areas in Figure3a showing the negative of the attenuation, where white corresponds to no attenuation and black to high attenuation), did not allow J. Imaging 2018, 4, 72 8 of 24 the use of a simple threshold. The low-density, highly-vesiculated phase is in fact characterised by the same greyscale values of some of the edge voxels (gradient between the object and the empty pores) and inner vesicles. The impactite mask was created through dual intensity thresholding (see Figure3b), with thresholding values computed by minimising the intraclass variance [46]. Figure3c shows, in white, the voxels below the first threshold representing the air (background), in black, the foreground object representing the voxels above the second threshold, and in grey the unassigned voxels with values in between. The unassigned voxels were treated separately by applying morphological transformations to enhance the image contrast (top-hat filter), which acted like a high-pass filter to extract the bright areas of the image. This approach allowed us to assign inner vesicles and edge voxels to the background representing air, while keeping the low-density phases in the foreground J.object. Imaging The 2018 resulting, 4, x FOR PEER mask REVIEW is shown in Figure3d, where the impactite is visualised in black and the8 of air 23 is represented in white. AsAs the impactite is is dominated by by silicate-rich glasses, glasses, most most of of its its voxels voxels lie lie within within a a narrow narrow neutronneutron and X-rayX-ray attenuationattenuation range. range. Minor Minor phases phases could could be be identified identified by by the the presence presence of clusters of clusters that thatcan becan visualised be visualised as local as local maxima maxima by plotting by plotting the voxel the voxel counts counts in a logarithmic in a logarithmic scale, asscale, shown as shown below belowin Figure in 4Figure. 4.

FigureFigure 4. Bi-modal histogram histogram of of neut neutronron attenuation attenuation coefficient coefficient μµ versusversus density, density, with voxel counts per bin bin in in logarithmic logarithmic scale: scale: the the plot plot is compared is compared to the to respective the respective X-rayX-ray (orange) (orange) and neutron and neutron (blue) histograms.(blue) histograms. Only impactite Only impactite voxels selected voxels through selected the through aforementioned the aforementioned mask are shown mask (see are Section shown 2.3.2). (see Section 2.3.2). Intensity-based segmentations are very effective when the object is constituted by few materials with Intensity-basedwell separated peaks segmentations in the bivariate are very histogra effectivem. whenHowever, the objectoverlap is constitutedin distributions by few may materials lead to noisywith wellsegmentation. separated peaksThe noise in the can bivariate be alleviated histogram. by considering However, contextual overlap in information, distributions utilizing may lead the to factnoisy that segmentation. short-range regions The noise are can often be homogeneous. alleviated by considering In the present contextual analysis information, we performed utilizing a Markov the randomfact that field short-range (MRF) segmentation regions are often [47], homogeneous. a probabilistic Inmodel the present that takes analysis into account we performed the likelihood a Markov of assigningrandom field each (MRF) voxel segmentationto a specific label, [47], not a probabilistic only depending model on that its takesgrey scale into accountvalue, but the also likelihood on the labelof assigning assigned each to the voxel neighbouring to a specific voxels. label, not only depending on its grey scale value, but also on the label assigned to the neighbouring voxels. 2.3.3. Morphology 2.3.3. Morphology Following segmentation, a binary mask was defined for the metallic spherules (designated class 8, see TableFollowing 2 for defining segmentation, parameters) a binary and mask another was fo definedr the vesicles for the derived metallic from spherules the background (designated mask class described8, see Table above2 for (see defining white parameters)area represented and in another Figure for3d). the Using vesicles the two derived binary from masks the we background performed amask connected described components above (see analysis white areato evaluate represented the distribution in Figure3d). and Using size thevariability two binary of the masks metallic we spherulesperformed and a connected vesicles. Connected components components analysis to analysis evaluate is used the distribution to label voxels and pertaining size variability to the ofsame the objectmetallic (or spherules region of and space), vesicles. as defined Connected by the components mask. Due analysisto the achieved is used tospatial label voxelsresolution, pertaining we only to considered objects larger than 2 voxels (≈7.2 × 104 µm3). In order to calculate the size of the objects, we analysed the connected components of the two masks considering a 3D neighbourhood of 6 voxels. Since these objects are far from perfect spheres, especially the larger ones, we estimated their volume simply by the number of constituent voxels.

3. Results

J. Imaging 2018, 4, 72 9 of 24 the same object (or region of space), as deﬁned by the mask. Due to the achieved spatial resolution, we only considered objects larger than 2 voxels (≈7.2 × 104 µm3). In order to calculate the size of the objects, we analysed the connected components of the two masks considering a 3D neighbourhood of 6 voxels. Since these objects are far from perfect spheres, especially the larger ones, we estimated their volume simply by the number of constituent voxels.

3. Results

3.1. Visualisation Impactite X-ray and neutron volumes are plotted in a bivariate histogram (see Figure4) showing voxel-wise comparison of the attenuation values between the two modalities. This plot aids in the identiﬁcation phases of deﬁned composition. This in turn can help us consider the heterogeneity of theJ. Imaging sample. 2018, 4, x FOR PEER REVIEW 9 of 23 Corresponding slices from the registered X-ray and neutron tomography volumes are shown in FigureCorresponding5 for direct comparison, slices from together the registered with the X-ray voxel-to-voxel and neutron correspondence tomography volumes plotted are in shown a bi-modal in histogram.Figure 5 for Fordirect a better comparison, visualization together withof the the slices voxel- weto-voxel use acorrespondence colour scheme plotted where in high a bi-modal intensity histogram. For a better visualization of the slices we use a colour scheme where high intensity (in bright) (in bright) correspond to low attenuation. X-ray imaging provides high contrast for the metallic correspond to low attenuation. X-ray imaging provides high contrast for the metallic spherules (in black), spherules (in black), while neutrons highlights both the spherules (mainly due to Fe, Ni and Co) and while neutrons highlights both the spherules (mainly due to Fe, Ni and Co) and their hydrogen- their hydrogen-containing oxidic corrosion products (mainly due to the presence of hydrogen). containing oxidic corrosion products (mainly due to the presence of hydrogen).

(a) (b)

(c)

Figure 5. Corresponding slices (z = 913) from a reconstructed volume of the Monteraqui impactite Figure 5. Corresponding slices (z = 913) from a reconstructed volume of the Monteraqui impactite using using (a) X-ray and (b) neutrons. High intensity (bright) correspond to low attenuation coefficients. (a) X-ray and (b) neutrons. High intensity (bright) correspond to low attenuation coefﬁcients. The areas The areas of lowest absorption correspond to voids in the impactite; (c) Bi-modal histogram relative to the of lowest absorption correspond to voids in the impactite; (c) Bi-modal histogram relative to the selected selected slice. X-ray attenuation values above 7.9 g/cm3 have been truncated for visualization purposes. slice. X-ray attenuation values above 7.9 g/cm3 have been truncated for visualization purposes. False colour images are an effective way of simultaneously visualizing images from multiple modalities; some of the possible combinations obtained using JET and RGB colour models are shown in Figure 6, alongside the respective colour map. These colour schemes provided the best combination for this particular dataset. The false colour images were used to visually identify features of interest in the impactite, such as corrosion areas (highly attenuating for neutrons but not for X-rays) surrounding some of the Fe-Ni spherules (high attenuation in both datasets). All X-ray attenuation values above 7.9 have been truncated for visualization purposes. J. Imaging 2018, 4, 72 10 of 24

False colour images are an effective way of simultaneously visualizing images from multiple modalities; some of the possible combinations obtained using JET and RGB colour models are shown in Figure6, alongside the respective colour map. These colour schemes provided the best combination for this particular dataset. The false colour images were used to visually identify features of interest in the impactite, such as corrosion areas (highly attenuating for neutrons but not for X-rays) surrounding some of the Fe-Ni spherules (high attenuation in both datasets). All X-ray attenuation values above 7.9 have been truncated for visualization purposes. J. Imaging 2018, 4, x FOR PEER REVIEW 10 of 23

(a) (b)

FigureFigure 6.6. ((aa)) RGBRGB colourmap and and (b (b) )corresponding corresponding RGB RGB false false colour colour representation representation of slice of slice z = 913; z = 913; (c) JET colourmap and (d) corresponding JET false colour representation of slice z = 913. (c) JET colourmap and (d) corresponding JET false colour representation of slice z = 913.

3.2. Materials Segmentation 3.2. Materials Segmentation Considering the expected mineralogical composition (based on literature, see Section 2.1) of the impactiteConsidering and the theclustering expected of the mineralogical voxels as plotte compositiond in the bivariate (based on histograms literature, in see Figures Section 4 and 2.1 )5c, of the impactitewe grouped and the the minerals clustering in 8 ofmaterials the voxels classes, as plotted according in theto which bivariate we performed histograms the in segmentation. Figures4 and 5c, weTable grouped A1 in the the Appendix minerals A in reports 8 materials the mean classes, attenuat accordingion values to which for each we class performed used as starting the segmentation. values Tablefor the A1 MRF in the segmentation. AppendixA reports the mean attenuation values for each class used as starting values for theThe MRF X-ray segmentation. and neutron attenuation ranges that the material classes cover are visualised in Figure 7. ComparisonsThe X-ray to and the neutron theoretical attenuation density and ranges neutron that lin theear material attenuation classes values cover of aresome visualised of the expected in Figure 7. Comparisonsminerals are reported to the theoretical Table 2. As density porosity and contri neutronbutes linear to density attenuation reduction, values the of theoretical some of the density expected mineralsand neutron are reported attenuation Table of2 .most As porosity phases contributesare higher tothan density the experimental reduction, the ones. theoretical Because density of the and neutronmultiple attenuation and complex of mostmineralogy phases of are the higher lithic thanfragments, the experimental we did not ones.calculate Because their oftheoretical the multiple density ρ and neutron linear attenuation values μ.

J. Imaging 2018, 4, x FOR PEER REVIEW 11 of 23 J. Imaging 2018, 4, x FOR PEER REVIEW 11 of 23 J. Imaging 2018, 4, x FOR PEER REVIEW 11 of 23 J. Imaging 2018, 4, x FOR PEER REVIEW 11 of 23

J. Imaging 2018, 4, x FOR PEER REVIEW 11 of 23 J. Imaging 2018, 4, x FOR PEER REVIEW 11 of 23

J. Imaging 2018, 4, 72 11 of 24

and complex mineralogy of the lithic fragments, we did not calculate their theoretical density ρ and neutronJ. Imaging linear 2018, attenuation4, x FOR PEER REVIEW values µ . 11 of 23

) 1 −

11 of 23 11 of

(cm

Figure 7. X-ray and neutron attenuation ranges for the different material classes identified in the μ

Figure 7. X-ray and neutron attenuation Neutron ranges for the different material classes identified in the Figure 7. X-ray and neutron attenuation ranges for the different material classes identified in the

impactite. )

impactite. 3 Figure 7. X-rayimpactite. and neutron attenuation ranges for the different material classes identified in the

3 −1 impactite. Table 2. Theoretical density ρ (g/cm3) and linear neutron attenuation μ (cm−1, for 4 Å neutrons) values

X-ray

Table 2. Theoretical density ρ (g/cm ) and (g/cm linear neutron attenuation μ (cm , for 4 Å neutrons) values Figure 7. X-ray and neutron attenuation ranges 3for the different material classes identified−1 in the ofTable selected 2. Theoretical minerals density (non-porous) ρ (g/cm expected) andρ linear in theneutron impactite attenuation [23] and μ (cm corresponding, for 4 Å neutrons) segmentation values impactite.Figure 7. X-rayof selectedand neutron minerals attenuation (non-porous) ranges expected for the different in the impactite material [23]classes and identified corresponding in the segmentation Tableimpactite. 2. Theoretical materialof selected density class minerals and ρ (g/cm attenuation (non-porous)3) and linear ranges. neutronexpected attenuation in the impactite μ (cm− 1,[23] for 4and Å neutrons) corresponding values segmentation Figurematerial 7. X-ray class and and neutron attenuation attenuation ranges. ranges for the different material classes identified in the ofimpactite. selectedFigure mineralsmaterial 7. X-ray (non-porous) class and and neutron attenuation expected attenuation ranges. in the ranges impactite for the different[23] and material corresponding classes identiﬁed segmentation in Table 2. Theoreticalimpactite. density ρ (g/cm3) and linear neutron attenuation μ (cm−1, for 4 Å neutrons) values

3 4 Å neutrons) values , for −1

the impactite. Chemical ρ μ (4 Å) Class Material X-ray Neutron Table 2. Theoretical density ρ (g/cm )1 and linear neutron attenuation μ (cm , for 4 Å neutrons) values material classMineral and attenuation Chemical ranges. − ρ μ (4 Å) Class Material X-ray Neutron of selected mineralsMineral (non-porous)Chemical expected3 ρ in 3 the impactiteμ (4 −Å)1 [23]Class and corresponding −1 Material segmentation X-ray 3 Neutron−1 0.83 ) Formula (g/cm ) (cm ) Colour Class ρ (g/cm ) μ (cm ) n ofTable selected 2. Theoretical mineralsMineralTable 2. Theoretical density (non-porous)Formula ρ density (g/cm ρ expected )(g/cm and(g/cm3 )linear and in linear3 ) theneutron neutronimpactite(cm attenuation−1 attenuation) [23]Colour and μ μ (cm (cm corresponding −1, for, for 4 Å 4 neutrons) ÅClass neutrons) segmentation values valuesρ (g/cm 3) μ (cm−1) 3 3 −1 −1 3 −1 μ (cm materialof selected classTable mineralsQuartzChemical and 2. Theoretical attenuation (non-porous) Formula densitySiO ranges.ρ 2 ρ (g/cm expected μ )(4(g/cm and2.65 Å) in linear )the neutronimpactiteClass (cm0.293 attenuation) [23]Colour and■µMaterial (cm corresponding , for 4Matrix Å neutrons)ClassX-ray segmentationglass values Neutronρ1.2–2.5 (g/cm ) 0.04–0.60μ (cm ) material classof andselected attenuation minerals (non-porous) ranges.μ expected in the impactite [23] and corresponding segmentation 2 Material ■ Mineral Quartz SiO 3 2.65−1 0.293 Matrix glass3 1.2–2.5−1 0.04–0.60 of selected minerals (non-porous)2 expected in the impactite Iron oxides Iron oxides [23 Iron oxides 2.5–5.2 ] and 0.08–0.75 ■ 2.5–5.2 0.08–0.75 corresponding 2.5–5.2 0.08–0.75 segmentation material classMagnetitematerialQuartzFormula and attenuation class and attenuation(g/cmFeSiO ranges.3O4 ) ranges. (cm5.172.65 ) Colour0.9260.293Matrix glass 1.2–2.5 0.04–0.60 ■ Class MatrixIronρ oxides (g/cm glass ) μ (cm 2.5–5.21.2–2.5) 0.08–0.750.04–0.60 Fe-Ni + troilite troilite Fe-Ni + 4.4–6.7 0.32–1.60 Fe-Ni + troilite troilite Fe-Ni + 4.4–6.7 0.32–1.60 Magnetite Fe3O4 5.17 0.926 ■ Iron oxides 2.5–5.2 0.08–0.75 2.90 /Z) Chemical μ (4 Å) Class Material Fe-Ni spherules Fe-Ni spherules 6.4–12.3 0.33–1.68 Fe-Ni spherules 6.4–12.3 0.33–1.68 X-ray 6.4–12.3 0.33–1.68 Neutron material class and attenuation3ρ 4 ranges. ■ Quartz MagnetiteChemicalSiO2 Fe2.652ρO 3 μ0.293 (45.17 Å) Class0.926■ Matrix■Material glass Iron oxides 1.2–2.5X-ray 0.04–0.60Neutron 2.5–5.2 0.08–0.75 ρ Mineral Hematite Fe O 5.24 0.936 Iron oxihydroxides 2.2–5.1 0.58–1.45 Iron oxides 2.5–5.2 0.08–0.75 Mineral Chemical2 33 ρ −1μ (4 Å) Class ■Material X-ray Neutron3 −1 MineralHematiteChemicalFormula (g/cmFeρO 3 ) μ(cm (45.24 −Å)1) ColourClass0.936 MaterialClass Ironρ oxides X-ray(g/cm 3) Neutronμ (cm 2.5–5.2−1) 0.08–0.75 Magnetite HematiteIlmeniteFormulaFe3O4 FeTiO(g/cmFe5.172O3 3 ) 3(cm0.9264.795.24) −1 Colour0.8980.936■ Iron■ Class oxides Ironρ oxides 2.5–5.2 (g/cm3 ) − 0.08–0.751μ (cm 2.5–5.2) 0.08–0.75 Mineral ChemicalFormula (g/cm ) µ (4(cm Å) ) ClassColour ■Class X-rayρ (g/cmρ )Neutron μ (cmµ) Quartz MineralIlmeniteSiO2 FeTiO2.65ρ (g/cm 33 3) 0.2934.79−1 0.898■ MaterialMatrix Class glass Iron oxides 1.2–2.5 3 0.04–0.60 2.5–5.2−1 0.08–0.75

Formula (g/cmin the material classes identified different ) (cm )− Colour Class ρ (g/cm−) μ (cm ) HematiteQuartz QuartzGoethiteIlmeniteFeSiO2 O23 FormulaSiOFeO(OH)FeTiO2 5.242.65 3 2.65 0.9360.293(cm 4.134.790.293 1 ) Colour 3.0380.898■ ■ MatrixIron■ oxides glass glass Iron (g/cmIron oxihydroxides 1.2–2.53) oxides 2.5–5.21.2–2.5 (cm 0.04–0.60 1) 0.08–0.750.04–0.60 2.2–5.12.5–5.2 0.58–1.450.08–0.75 Goethite FeO(OH) 4.13 3.038 ■ Iron oxihydroxides 2.2–5.1 as impactite of the volume solid of the on 0.58–1.45

3 4 ■ MagnetiteQuartz MagnetiteFeSiOO 2 Fe3O4 5.172.65 5.17 0.9260.2930.926 ■ ■ MatrixIronIron■ oxides oxides glass 2.5–5.2 2.5–5.21.2–2.5 0.08–0.75 0.08–0.750.04–0.60 Magnetite GoethiteFe3O4 3 FeO(OH)5.17 0.926 4.13 3.038■ Iron oxidesIron oxihydroxides 2.5–5.2 neutron slices and X-ray where individual 8, re 0.08–0.75 2.2–5.1 0.58–1.45 ■ ■ ■ ■ ■ Ilmenite QuartzTroiliteFeTiO SiO2 FeS4.79 2.650.898 4.61 0.293 0.616■ ■ ■ Matrix■ Iron■ glass oxides Fe-Ni 1.2–2.5 + 2.5–5.2 troilite 0.04–0.60 0.08–0.75 4.4–6.7 0.32–1.60 HematiteTroilite2 3 Fe2O3 FeS 5.24 4.610.936 0.616■ ■ Iron■ oxides Fe-Ni 2.5–5.2 + troilite 0.08–0.75 4.4–6.7 0.32–1.60

Hematite Fe O 5.24 0.936 Class Iron oxides 2.5–5.2 0.08–0.75 Magnetite MagnetiteFe23O34 Fe3O4 5.17 5.170.926 0.926 ■ IronIron■ oxides oxides 2.5–5.2 2.5–5.2 0.08–0.75 0.08–0.75 HematiteGoethite PyrrhotiteTroiliteFeO(OH)Fe O FeFeS5.24 4.13(1−x) S 3.0380.9364.61 Colour 0.616■ IronIron ■oxihydroxides oxides Fe-Ni + 2.5–5.22.2–5.1 troilite 0.58–1.450.08–0.75 4.4–6.7 0.32–1.60 Ilmenite HematitePyrrhotiteIlmeniteFeTiO 3 FeFeTiO2O3 Fe34.79 (1−x)S 5.24 4.79 0.8984.61 0.9360.898 0.616■ ■ IronIronIron■ oxides oxides oxides Fe-Ni 2.5–5.2 2.5–5.2 + 2.5–5.2 troilite 0.08–0.75 0.08–0.75 0.08–0.75 4.4–6.7 0.32–1.60 Hematite PyrrhotiteFe2O33 Fe5.24(1−x)S 0.9364.61 0.616■ Iron■ oxides Fe-Ni + 2.5–5.2 troilite 0.08–0.75 4.4–6.7 0.32–1.60 Ilmenite FeTiO 0.94.79 0.1 0.898 segmentation corresponding and [23] impactite the ■ Iron■ oxides 2.5–5.2 0.08–0.75 Troilite IlmeniteGoethiteKamaciteFeS FeTiOFeO(OH)3Fe 4.61 Ni 4.79 4.13 0.6167.9 0.898 3.038 1.576■ IronIronFe-Ni oxihydroxides oxides + troiliteFe-Ni 2.5–5.2 2.2–5.1 spherules 4.4–6.7 0.08–0.75 0.58–1.45 0.32–1.60 6.4–12.3 0.33–1.68 Goethite KamaciteFeO(OH) Fe0.9 4.13Ni 0.1 3.0387.9 1.576■ Iron ■oxihydroxides Fe-Ni spherules 2.2–5.1 0.58–1.45 6.4–12.3 0.33–1.68 Matrix glass 78.14 Ilmenite GoethiteFeTiO3 FeO(OH)0.94.79 0.1 4.130.898 3.038 ■ Iron oxihydroxidesIron■ oxides 2.2–5.1 2.5–5.2 0.58–1.45 0.08–0.75 Goethite KamaciteFeO(OH)(1−x) Fe 4.13Ni 3.0387.9 ) 1.576■ Iron oxihydroxidesFe-Ni spherules 2.2–5.1 0.58–1.45 6.4–12.3 0.33–1.68 Pyrrhotite TroiliteTaeniteFe S FeSFe 0.84.61Ni 0.2 4.61 0.6168.010.616 1.672 ■ Fe-Ni■ + +troilite troilite Fe-Ni 4.4–6.7 spherules 4.4–6.7 0.32–1.60 0.32–1.60 6.4–12.3 0.33–1.68 spherules Fe-Ni 0.12 Lithic fragments fragments Lithic 13.78 1 Troilite TroiliteTaeniteFeS FeSFe0.8 4.61Ni 0.2 4.61 0.6168.01 0.616 − 1.672■ Fe-NiFe-Ni +■ troilite + troiliteFe-Ni 4.4–6.7 spherules 4.4–6.7 0.32–1.60 0.32–1.60 6.4–12.3 0.33–1.68 KamaciteGoethiteTroilite PyrrhotiteTaeniteFerriteFeO(OH)Fe0.9FeSNi 0.1 Fe(1Fe−x)S0.8 4.614.13Fe7.9Ni 0.2 4.61 1.5760.616 3.0387.898.010.616 1.4691.672■ ■ IronFe-NiFe-Ni ■oxihydroxides +spherules +troilite troilite Fe-Ni 4.4–6.7 spherules 6.4–12.3 4.4–6.72.2–5.1 0.32–1.60 0.32–1.600.33–1.680.58–1.45 6.4–12.3 0.33–1.68 Pyrrhotite Fe − S 4.61 0.616 Fe-Ni + troilite 4.4–6.7 0.32–1.60 Ferrite(1−x) (1 x) Fe 7.89 (4 Å) 1.469■ ■ Fe-Ni spherules 6.4–12.3 0.33–1.68 Pyrrhotite KamaciteFe S Fe0.9Ni0.14.61 7.9 0.6161.576 (cm ■ Fe-NiFe-Ni spherules + troilite 6.4–12.3 4.4–6.7 0.33–1.68 0.32–1.60 Troilite FeS(1−x) 4.61 0.616 μ ■ Fe-Ni■ + troilite 4.4–6.7 0.32–1.60 PyrrhotiteTaenite KamaciteFerriteFeFe0.8Ni S0.2 Fe 0.9Ni0.1 8.014.61Fe 7.91.6720.6167.89 1.576 1.469■ Fe-NiFe-NiFe-Ni spherules spherules + troiliteFe-Ni 6.4–12.3 spherules 6.4–12.3 4.4–6.7 0.33–1.68 0.32–1.600.33–1.68 6.4–12.3 0.33–1.68 (low fragments Lithic Kamacite TaeniteFe0.9 Ni0.1 Fe FeNi0.8Ni0.27.9 8.018.01 1.576 1.6721.672 ■ ■ Fe-NiFe-NiFe-Ni spherules spherules spherules 6.4–12.3 6.4–12.3 6.4–12.3 0.33–1.68 0.33–1.68 0.33–1.68 PyrrhotiteKamacite FeFe0.9(1Ni−x)S0.1 0.8 0.2 4.617.9 neutron attenuation ) and linear 1.5760.616 ■ Fe-NiFe-Ni spherules + troilite 6.4–12.3 4.4–6.7 0.33–1.680.32–1.60 Ferrite Fe 7.89 3 1.469 Fe-Ni spherules 6.4–12.3 0.33–1.68 FerriteFerriteAn example FeFe of the 7.89segmentation7.89 1.4691.469 is shown■ inFe-Ni FiguFe-Ni spherulesre spherules 8, where 6.4–12.3 individual 6.4–12.3 0.33–1.68 0.33–1.68 X-ray and neutron slices Taenite Fe0.8Ni0.2 8.01 1.672 ) ■ Fe-Ni spherules 6.4–12.3 0.33–1.68

An example of the segmentation is3 shown in Figure 8, where individual X-ray and neutron slices

0.9 0.1 ■ neutron attenuation (high Matrix KamaciteTaenite FeAn0.8 exampleNi0.2 of8.01 7.9the segmentation1.6721.576 is shown■ in FiguFe-Nire 8,spherules where individual 6.4–12.3 X-ray 0.33–1.68 and neutron slices maghemite) Iron oxides (dominantly 3.16 are compared. Matrix glass materials are ■shown in blue, lithic inclusions in shades of green, oxidic Ferrite Fe 7.89 1.469 ρ Fe-Ni spherules 6.4–12.3 0.33–1.68 TaeniteFerrite are compared.Fe0.8FeNi 0.2 Matrix7.898.01 glass materials1.4691.672 are ■shown inFe-Ni blue, spherules lithic inclusions 6.4–12.3 in shades 0.33–1.68 of green, oxidic goethite) (dominantly Iron oxihydroxides 0.89 An exampleare compared.An of example the segmentation of Matrix the segmentation glass is (g/cm shown materials is shown in Figu inare Figu reshownre 8, 8, where where in blue, individual lithic X-ray inclusions X-ray and andneutron inneutron shadesslices slices of green, oxidic

corrosion products in orange/pink,ρ and metallic phases in shades of red. In Table 3 the volume

An example of the segmentation is shown in Figure(g/cm 8, where individual X-ray and neutron slices Ferrite arecorrosion compared.Fe products Matrix glass7.89 in materialsorange/pink,1.469 are shown and in ■ metallicblue, lithic phasesFe-Ni inclusions spherules in in shades shades of 6.4–12.3of green, red. oxidicIn 0.33–1.68 Table 3 the volume troilite or containing spherules corroded Fe-Ni 0.19 are compared.arefractioncorrosion compared. Matrix of productsglass Matrixeach materialmaterials glass in materials orange/pink, class are shownis are reported. shown andin inblue, metallic blue, lithic lithic phases inclusions inclusions in inshades in shades shades of of green,red.of green, In oxidic Table oxidic 3 the volume An examplecorrosionfraction of theofproducts eachsegmentation materialin orange/pink, class is shown andis reported. metallic in Figu phases re 8, where in shades individual of red. In X-ray Table and3 the neutron volume slices corrosionAn example corrosionproductsfraction of products the inof eachorange/pink,segmentation in orange/pink,material class andis andshown metallicis metallic reported. in Figu phasesphases re 8, in wherein shades shades ofindividual red. of In red. Table X-rayIn3 the Table volumeand 3neutron fractionthe volume slices 7.9 1.576 1.576 7.9 1.672 8.01

are compared.fraction Matrix of each glass material materials class is arereported. shown in blue, lithic 0.898 4.79 inclusions in shades of green, oxidic 5.17 0.926 0.926 5.17 0.936 5.24 An example of the segmentation is shown in Figure 8, where3 individual X-ray and neutron slices 0.1 0.2 2.65 0.293 0.293 2.65 S 4.61 0.616 0.616 S 4.61 are compared. Matrix glass materials are shown in blue, 4 lithic3 inclusions in shades of green, oxidic

fraction ofof each each material class class is reported.is reported. 2 x)

Table 3. Material classes and respective volume fraction of the solid volume of the impactite as O O − Ni Ni corrosionare compared. products MatrixTable in glass3.orange/pink, Material materials classes and are and metallicshown respective in phases blue, volume 3 lithicin2 shades fractiinclusionson of of red. the in Inshadessolid Table volume of 3 green, the of volumethe oxidic impactite as ■ ■ ■ ■ ■ ■ ■ ■ corrosion productsTableTable in 3. Material3.orange/pink, Material classes classes and and respective andmetallic respective volume phases fracti volumeon in of shadesthe fracti solidon volumeof of (1 red. the of Insolidthe Tableimpactite volume 3 asthe of volumethe impactite as resulted from the MRF segmentation. 0.9 0.8 fractioncorrosion of productseachTable materialresulted 3. Materialin orange/pink, fromclass classes theis reported. andMRF respective and segmentation. metallic volume fractionphases of thein solidshades volume of ofred. the impactite In Table as resulted 3 the volume fraction of each materialresulted from class the MRF is reported. segmentation. Formula Table 3. Materialresulted classes from and the MRFrespective segmentation. volumeChemical fraction of the solid volume of the impactite as fraction of eachfrom material the MRF# class segmentation.Class is Colourreported. Material Volume % , x FOR PEER REVIEW

resulted from the #MRF Class segmentation. Colour X-ray and neutron attenuation ranges for the Material Volume %

4 # Class Colour Material Volume % Material classes and respective volume fracti classes and respective Material Theoretical density Theoretical

, Table 3. Material classes# Class and Colour respective volume fraction of Materialthe solid volume of the impactiteVolume as % Table 3. Material classes1 ■and ■ respective volume fraction ofMatrix the solid glass volume of the impactite as 78.14 # Class Colour Material Volume % % Volume Material Colour Class # 6 7 8 1 2 5 4 #1 1 Class■ Colour Matrix glass MaterialMatrix glass 78.14 Volume % 78.14 3 resultedTable #3. fromMaterialClass the Colour MRF classes1 segmentation. and■ respective volumeMaterial fraction ofMatrix the solid glass volume ofVolume the impactite % as 78.14 2018 resulted from the1 2MRF 2 segmentation.■ ■ Matrix (highMatrix neutron (highMatrix attenuation neutron glass μ attenuationn) 0.83 μn78.14 ) 0.83 2 ■ Matrix (high neutron attenuation μn) 0.83 resulted1 from the2 ■ 3MRF 2 segmentation.■ ■ MatrixLithic (high fragments(highglass neutron neutron attenuation attenuationµn) 13.78 μ 78.14n 0.83 ) 0.83 of selected minerals (non-porous) expected in expected (non-porous) minerals of selected material class and attenuation ranges. attenuation material class and Figure 7. in Figu is shown the segmentation An example of Table 3. resulted from the MRF segmentation. 3 ■ impactite. Table 2. Lithic fragments 13.78

# Class Colour Material 1.469 VolumeFerrite Fe 7.89 % Quartz SiO Troilite FeS 4.61 0.616 0.616 FeS Troilite 4.61 3 ■ Lithic fragments Fe Taenite 13.78 Ilmenite FeTiO 3 Mineral Lithic fragments 13.78 # Class Colour4 ■ LithicMaterial fragments (low ρ/Z)Goethite FeO(OH) 4.13 3.038 Volume2.90 % Hematite Fe Hematite Kamacite Fe Magnetite Fe ■ ■ n Pyrrhotite Fe 2 4 43 ■ Matrix (high neutronLithicLithic fragments attenuationLithic fragments (low fragmentsρ/Z) μ(low) ρ/Z) 0.83 2.90 13.782.90 1# Class ■Colour5 4 ■ ■ Iron oxidesMatrixMaterial (dominantlyLithic glass fragments maghemite) (low ρ/Z) Volume 3.16 78.14 % 2.90 J. Imaging 1 Matrix glass 78.14 oxidic green, of shades in inclusions lithic shown in blue, are materials glass Matrix are compared. volume the 3 Table In red. of shades in phases metallic and in orange/pink, products corrosion material class is reported. of each fraction 3 5 ■ 54 ■ LithicIron oxides fragmentsoxidesLithic (dominantly fragments(dominantly maghemite) (low maghemite) ρ/Z) 13.78 3.16 2.90 3.16 21 6 ■6 5 ■ ■ MatrixIron (highoxihydroxidesIronIronMatrix neutron oxihydroxides oxides glass(dominantly attenuation (dominantly goethite) goethite)μn) maghemite) 0.89 78.14 0.83 0.89 3.16 2 ■ 5 ■ Matrix (highIron neutron oxides attenuation (dominantly μn) maghemite)0.83 3.16 4 7 ■7 6 ■ ■ Fe-NiLithic corrodedFe-NiIron fragments corroded spherulesoxihydroxides spherules (low or containing orρ containing/Z) (dominantly troilite troilite goethite) 0.19 2.90 0.19 0.89 32 8 ■ 6 ■ Matrix (highIronLithic neutron oxihydroxides fragmentsFe-Ni attenuation spherules (dominantly μn) goethite) 13.780.83 0.12 0.89 5 ■8 76 ■ ■ Iron oxidesFe-NiIron (dominantly corroded Fe-Nioxihydroxides spherules spherules maghemite) (dominantly or containing goethite) 0.12 troilite 3.16 0.890.19 43 ■ 7 ■ LithicFe-NiLithic fragments corroded fragments (low spherules ρ/Z) or containing 13.78troilite2.90 0.19 6 ■ 87 ■Iron oxihydroxidesFe-Ni corroded (dominantly Fe-Nispherules spherules goethite) or containing troilite 0.89 0.120.19 54 ■ 8 ■ Iron oxidesLithic fragments(dominantly (lowFe-Ni maghemite) ρ /Z)spherules 3.162.90 0.12 75 ■ 8 Fe-Ni■ Iron corroded oxides spherules (dominantly orFe-Ni containing maghemite) spherules troilite 3.160.19 0.12 65 ■ IronIron oxihydroxides oxides (dominantly (dominantly maghemite) goethite) 0.893.16 86 ■ Iron oxihydroxidesFe-Ni spherules (dominantly goethite) 0.890.12 76 ■ Fe-NiIron corroded oxihydroxides spherules (dominantly or containing goethite) troilite 0.190.89 7 ■ Fe-Ni corroded spherules or containing troilite 0.19 8 ■ Fe-Ni spherules 0.12 87 ■ Fe-Ni corroded Fe-Nispherules spherules or containing troilite 0.120.19

8 ■ Fe-Ni spherules 0.12

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(a)

(b) (c)

FigureFigure 8. 8. ((aa)) SegmentationSegmentation example with with the the 8 8 material material classes classes compared compared to to the the corresponding corresponding (b ()b X-) X-rayray and and (c ()c )neutron neutron slices slices (z (z = =415). 415).

3.3. Morphology 3.3. Morphology

3.3.1.3.3.1. VesiclesVesicles Analysis Analysis and and Quantification Quantification TheThe connectedconnected componentscomponents analysisanalysis detected 60,151 vesicles larger larger than than 2 2 voxels, voxels, making making up up ≈ ≈7.19%7.19% of of the the total total impactite impactite volume. volume. The The majority majority of of vesicles vesicles are are relatively relatively small small (median (median value value of of18 18voxels, voxels, which which corresponds corresponds to to6.5 6.5 × 10× −104 mm−4 mm3), but3), butthe thesize sizedistribution distribution is very is very broad, broad, ranging ranging up to up 8 toM 8 voxels M voxels (corresponding (corresponding to toa volume a volume of of 0.29 0.29 cm cm3).3 ).For For this this reason, reason, we we grouped grouped the vesiclesvesicles inin fivefive differentdifferent rangesranges ofof increasingincreasing size.size. TheThe classesclasses denselydensely covercover thethe lower-endlower-end ofof thethe sizesize distribution,distribution, withwith objects objects larger larger than than 5000 5000 voxels voxels grouped grouped in in the the last last category. category. The The inclusions inclusions that that fill fill some some vesicles vesicles areare not not accounted accounted for for in in the the volume volume quantification. quantification. AA 3D3D rendering rendering ofof the the thus-classified thus-classified vesiclesvesicles isis reportedreportedin in Figure Figure9 ,9, with with colour colour representing representing thethe fivefive differentdifferent vesiclevesicle size ranges as as subdivided subdivided according according to to the the legend. legend. As As can can be beseen seen from from the the3D 3Drendering rendering and and the thehorizontal horizontal cut in cut Figure in Figure 9, vesicles9, vesicles larger larger than than 5000 5000 voxels voxels (pale (pale green) green) make makeup most up mostof the of thevolume, volume, while while smaller smaller objects objects clearly clearly dominate dominate in in number. number. This This is moremore clearlyclearly representedrepresented byby thethe barbar plotsplots in in Figure Figure 10 10.. ThisThis confirmsconfirms that,that, whilewhile small-scaledsmall-scaled porespores areare moremore frequentfrequent (see (see Figure Figure 10 10a),a), almost almost 80% 80% of of the the volume volume of of the theimpactite impactite is is groupedgrouped in invesicles vesiclesconstituted constituted ofof moremore thanthan 50005000 voxels.voxels. FromFrom thethe sectionsection itit appearsappears thatthat thethe vesiclesvesicles areare ubiquitousubiquitous withinwithin thethe material,material, yet yet quite quite unevenly unevenly distributed distributed and and particularly particularly rare rare within within the the lithic lithic fragments. fragments.

J. Imaging 2018, 4, 72 13 of 24 J. Imaging 2018, 4, x FOR PEER REVIEW 13 of 23

J. Imaging 2018, 4, x FOR PEER REVIEW 13 of 23

Figure 9. Example of vesicles distribution in the impactite: ( (aboveabove)) 3D 3D rendering rendering of of the dense pore Figure 9. Example of vesicles distribution in the impactite: (above) 3D rendering of the dense pore structure created with Avizo software; ((below)) virtualvirtual cutcut (slice(slice z = 415), 415), with with colour colour representing representing the structure created with Avizo software; (below) virtual cut (slice z = 415), with colour representing the 5 different vesicle size ranges as subdivided according to the legend, with n the number of voxels per 5 different5 different vesicle vesicle size size ranges ranges as subdividedas subdivided according according toto the legend, legend, with with n nthethe number number of voxels of voxels per per vesicle. In black is outlined the edge of the impactite. Note that black lines inside the sample edge vesicle.vesicle. In black In black is outlined is outlined the the edge edge of of the the impactite. impactite. Note that that black black lines lines inside inside thethe sample sample edge edge representrepresent porosity porosity connected connected to theto the outside. outside.

(a) (b) Figure 10. Quantification(a) of vesicles analysis of Monturaqui impactite. (a) Vesicles(b) size distribution Figure 10. Quantiﬁcation of vesicles analysis of Monturaqui impactite. (a) Vesicles size distribution and (b) total volume distribution per class. Figureand (b) 10. total Quantification volume distribution of vesicles per analysis class. of Monturaqui impactite. (a) Vesicles size distribution and (b) total volume distribution per class.

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3.3.2.3.3.2. Spherules Spherules Analysis Analysis and andQuantification Quantiﬁcation The Theconnected connected components components analysis analysis detected detected 1412 Fe-Ni 1412 Fe-Nimetallic metallic spherules spherules (class 8 (class according 8 according to Tableto 2), Table representing2), representing ≈0.12% of≈ 0.12%the impactite of the impactitesolid volume. solid Volu volume.mes of Volumescorroded ofor partially corroded corroded or partially spherulescorroded (classes spherules 5–7 according (classes 5–7 to accordingTable 2) are to Tablenot included2) are not in included the analysis in the as analysis corrosion as causes corrosion volumecauses expansion volume expansionand the formation and the formation of porosity. of porosity. The spherules The spherules have a have median a median size of size 118 of voxels 118 voxels (which(which corresponds corresponds to 4.3 to × 4.310−3× mm10−3),3 withmm3 a), size with distribution a size distribution ranging rangingup to 27 upk voxels to 27 k(volume voxels (volumeof 9.7 × of 10−1 9.7mm×3).10 Similarly,−1 mm3 ).to Similarly, the vesicle to analysis, the vesicle we analysis, grouped we the grouped spherules the in spherules 5 size ranges. in 5 size Figure ranges. 11 shows Figure 11 the 3Dshows rendering the 3D of rendering the five ofspherule the ﬁve classes, spherule with classes, detail with of a detail transv ofersal a transversal slice. Size slice. distribution Size distribution and volumeand fraction volume fractionper class per of spherules class of spherules are shown are in shown Figure in 12. Figure 12.

FigureFigure 11. Example 11. Example of spherules of spherules distribution distribution in the in impactite: the impactite: (above (above) 3D )rendering 3D rendering of the of spherules; the spherules; (below(below) virtual) virtual cut (slice cut (slice z = 418), z = 418), with with colour colour represen representingting the 5 the different 5 different size sizeranges ranges as subdivided as subdivided accordingaccording to the to legend, the legend, with with n then numberthe number of voxels of voxels per spherule. per spherule. In black In black is outlined is outlined the edge the edge of the of the slice slicerepresented. represented. Note Note that thatblack black lines lines inside inside the edge the edge represent represent porosity porosity connected connected to the to outside. the outside. Monturaqui spherules in some studies [23,30] showed a correlation between compositional variation in Fe-Ni and size, with spherules smaller than 0.1 mm in diameter more enriched in Ni (and therefore Co) than larger ones. A diameter of approximately 0.1 mm corresponds to spherules in the ﬁrst size range, with a voxel number n ≤25. This elemental variation, called fractionation, was attributed to partitioning and diffusion of Fe from the spherules into the surrounding impact

J. Imaging 2018, 4, x FOR PEER REVIEW 15 of 23

J. Imaging 2018, 4, 72 15 of 24 glass and to selective oxidation of Fe [15,48], causing the formation of a Ni-rich rim in the spherule surrounded by a Fe-rich halo (Fe >30%) in the silicate melt [30]. Although the available resolution was not sufﬁcient to detect such detailed features, it was possible to distinguish such spherules by the differentJ. Imaging 2018 attenuation, 4, x FOR PEER values REVIEW depending on their size. 15 of 23

(a) (b)

Figure 12. Quantification of spherule analysis of Monturaqui impactite. (a) Spherules size distribution and (b) total volume distribution per class, where n is the number of voxels (33.1 µm size).

Monturaqui spherules in some studies [23,30] showed a correlation between compositional variation in Fe-Ni and size, with spherules smaller than 0.1 mm in diameter more enriched in Ni (and therefore Co) than larger ones. A diameter of approximately 0.1 mm corresponds to spherules in the first size range, with a voxel number n ≤25. This elemental variation, called fractionation, was attributed to partitioning(a )and diffusion of Fe from the spherules into the( surroundingb) impact glass and to selective oxidation of Fe [15,48], causing the formation of a Ni-rich rim in the spherule surroundedFigureFigure 12. 12. byQuantification Quantification a Fe-rich halo of ofspherule spherule(Fe >30%) analysis analysis in the of of Monturaquisilicate Monturaqui melt impactite. impactite. [30]. Although ( a(a)) Spherules Spherules the available size size distribution distribution resolution was andnotand (sufficient b(b)) total total volume volume to detect distribution distribution such detailed per per class, class, features, where wheren n isit is the wasthe number number possible of of voxels tovoxels distinguish (33.1 (33.1µ µmm size). suchsize). spherules by the different attenuation values depending on their size. Monturaqui spherules in some studies [23,30] showed a correlation between compositional TheThe meanmean X-rayX-ray andand neutronneutron attenuationattenuation valuesvalues are plottedplotted inin FigureFigure 1313 forfor thethe fivefive spherulesspherules variation in Fe-Ni and size, with spherules smaller than 0.1 mm in diameter more enriched in Ni (and sizesize classes.classes. This This indicates indicates an an unexpected unexpected correlation correlation between between size andsize attenuation, and attenuation, with larger with objectslarger therefore Co) than larger ones. A diameter of approximately 0.1 mm corresponds to spherules in the beingobjects more being attenuating more attenuating for both for X-rays both X-rays and neutrons. and neutrons. The presenceThe presence of a of higher a higher amount amount of Niof Ni in first size range, with a voxel number n ≤25. This elemental variation, called fractionation, was smallerin smaller spheres spheres would would in in fact fact increase increase their their density density and and neutron neutron attenuation attenuation coefficient coefficient (see(see valuesvalues attributed to partitioning and diffusion of Fe from the spherules into the surrounding impact glass forfor taenite,taenite, kamacitekamacite andand ferriteferrite inin TableTable2 2).). Clarification Clarification of of this this contradiction contradiction will will require require a a focussed focussed and to selective oxidation of Fe [15,48], causing the formation of a Ni-rich rim in the spherule futurefuture destructivedestructive analysesanalyses guidedguided byby thethe imagingimaging data.data. surrounded by a Fe-rich halo (Fe >30%) in the silicate melt [30]. Although the available resolution was not sufficient to detect such detailed features, it was possible to distinguish such spherules by the different attenuation values depending on their size. The mean X-ray and neutron attenuation values are plotted in Figure 13 for the five spherules size classes. This indicates an unexpected correlation between size and attenuation, with larger objects being more attenuating for both X-rays and neutrons. The presence of a higher amount of Ni in smaller spheres would in fact increase their density and neutron attenuation coefficient (see values for taenite, kamacite and ferrite in Table 2). Clarification of this contradiction will require a focussed future destructive analyses guided by the imaging data.

Figure 13. Mean X-ray and neutron attenuation values and standard error for the five spherules size Figure 13. Mean X-ray and neutron attenuation values and standard error for the ﬁve spherules size classes, where n is the number of voxels (33.1 µm size). classes, where n is the number of voxels (33.1 µm size).

Figure 13. Mean X-ray and neutron attenuation values and standard error for the five spherules size classes, where n is the number of voxels (33.1 µm size).

J.J. ImagingImaging 20182018,, 44,, 72x FOR PEER REVIEW 1616 of 2423 J. Imaging 2018, 4, x FOR PEER REVIEW 16 of 23 3.3.3. Morphological Details 3.3.3.3.3.3. Morphological Morphological Details Details Lithic fragments (see Figure 14) constitute common inclusions (≈16% in volume) in the matrix Lithic fragments (see Figure 14) constitute common inclusions (≈16% in volume) in the matrix and haveLithic a fragments heterogeneous (see Figure genesis 14) and constitute composition. common Further inclusions detailed (≈16% inspection in volume) of inthe the volume matrix data and and have a heterogeneous genesis and composition. Further detailed inspection of the volume data haveenabled a heterogeneous us to identify genesis otherwise and hidden composition. morphological Further detailed features, inspection such as the of presence the volume of datashocked enabled and enabled us to identify otherwise hidden morphological features, such as the presence of shocked and usunshocked to identify lithic otherwise fragments, hidden layers morphological of corrosion features, covering such some as the of presence the vesicles, of shocked and evaporites and unshocked (see unshocked lithic fragments, layers of corrosion covering some of the vesicles, and evaporites (see lithicFigure fragments, 15d,e). layers of corrosion covering some of the vesicles, and evaporites (see Figure 15d,e). Figure 15d,e). EvaporitesEvaporites are mineralmineral aggregatesaggregates formed by thethe evaporationevaporation ofof water.water. TheyThey appearappear asas partialpartial Evaporites are mineral aggregates formed by the evaporation of water. They appear as partial andand similarly orientedoriented infillinginfilling ofof somesome ofof the larger vesicles by angular salt crystals (see green framed and similarly oriented infilling of some of the larger vesicles by angular salt crystals (see green framed insertsinserts inin Figure Figure 15 15).). These These precipitation precipitation salts salts have have escaped escaped unnoticed unnoticed in past in studies, past studies, possibly possibly because inserts in Figure 15). These precipitation salts have escaped unnoticed in past studies, possibly thebecause salts werethe salts removed were during removed sample during preparations. sample prep Layersarations. of oxidic Layers corrosion of oxidic products corrosion covering products inner because the salts were removed during sample preparations. Layers of oxidic corrosion products vesiclescovering (see inner red vesicles framed (see inserts red in framed Figure inserts15) are in also Figure a result 15) of are the also presence a result of of water the presence (weathering) of water and covering inner vesicles (see red framed inserts in Figure 15) are also a result of the presence of water are(weathering) most likely and due are to most the alteration likely due of to metallic the alterati spheruleson of metallic associated spherules with the associated surface ofwith some the vesicles. surface (weathering) and are most likely due to the alteration of metallic spherules associated with the surface Thisof some hypothesis vesicles. is This corroborated hypothesis by is the corroborated presence of by corroded the presence iron spherules of corroded in some iron poresspherules showing in some this of some vesicles. This hypothesis is corroborated by the presence of corroded iron spherules in some alterationpores showing layer (seethis Figurealteration 15b). layer This finding(see Figure indicates 15b). that, This although finding waterindicates overall that, is although scarce, it makeswater pores showing this alteration layer (see Figure 15b). This finding indicates that, although water aoverall significant is scarce, and lastingit makes imprint a significan on a localt andscale. lasting imprint on a local scale. overall is scarce, it makes a significant and lasting imprint on a local scale.

(a) (b) (c) (a) (b) (c) Figure 14. (a) Slice of the X-ray volume of the impactite showing inclusions of lithic fragments; (b) FigureFigure 14. 14.(a )(a Slice) Slice of theof the X-ray X-ray volume volume of the of impactite the impactite showing showing inclusions inclusions of lithic of fragments; lithic fragments; (b) detail (b) detail of the central part of the impactite showing a highly vesiculated fragment↑ (), next to an ofdetail the central of the part central of the part impactite of the showingimpactite ashowing highly vesiculated a highly vesiculated fragment ( fragment), next to an( unshocked), next to an unshocked↑↑ fragment (); (c) close-up of a shocked lithic fragment. fragmentunshocked ( );fragment (c) close-up ( of); a (c shocked) close-up lithic of a fragment. shocked lithic fragment.

(a) (b) (c) (a) (b) (c)

Figure 15. Cont.

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(d) (e)

Figure 15. (a) Slice of the X-ray volume of the impactite where the green frames highlight the presence Figure 15. (a) Slice of the X-ray volume of the impactite where the green frames highlight the presence of evaporites and in the red frames show corrosion layers covering inner vesicles; (b) detail of a large of evaporites and in the red frames show corrosion layers covering inner vesicles; (b) detail of a large vesicle covered by the corrosion layer and the residua of corroded iron spherules; (c) close-up detail vesicleof two coveredlarge and by three the small corrosion vesicles layer covered and the by residuathe corrosion of corroded layer; (d iron) close-up spherules; detail ( cof) close-upthe top- detail of tworight large evaporite; and three(e) close-up small detail vesicles of the covered evaporite by thefilling corrosion the large layer;central ( dvesicle.) close-up detail of the top-right evaporite; (e) close-up detail of the evaporite filling the large central vesicle. 4. Discussion and Conclusions 4. DiscussionX-ray and and neutron Conclusions tomography are applied in a bi-modal approach for an exemplary 3D characterisationX-ray and of neutron a Monturaqui tomography impactite. are The applied different in interactions a bi-modal of approachX-rays and forneutrons an exemplary with 3D matter allowed us to exploit the complementary information of both modalities. characterisation of a Monturaqui impactite. The different interactions of X-rays and neutrons with The two separate data sets have been registered successfully and allowed for the identification matter allowed us to exploit the complementary information of both modalities. of a rich variety of phases in the sample in accordance with the literature. False colour visualisation approachesThe two proved separate their data efficiency sets have for visualisation been registered and inspection successfully of the and bi-modal allowed volume for thedata. identification of a richMRF variety segmentation of phases of the in volume, the sample using in attenuat accordanceion information with the literature.from both modalities, False colour allowed visualisation approachesthe identification proved and their separation efficiency in particular for visualisation of materials and which inspection showed similar of the bi-modalattenuation volume levels in data. singleMRF modalities. segmentation The efficiency of the volume,of the bi-modal usingattenuation approach is informationdemonstrated from e.g., bothin the modalities, distinction allowed thebetween identification oxide and andoxyhydroxides, separation and in particularthe detection of of materials a low-density which phase showed in the matrix similar characterised attenuation levels inby single high neutron modalities. attenuation. The efficiency of the bi-modal approach is demonstrated e.g., in the distinction betweenMost oxide of the and object oxyhydroxides, is found to be andcomposed the detection of low-density of a low-density phases with phase overlapping in the matrixattenuation characterised distributions. Yet some classification uncertainty remains as materials listed as general “silica matrix” by high neutron attenuation. and “lithic fragments” could not be further classified. Despite the complementary radiation utilized, Most of the object is found to be composed of low-density phases with overlapping attenuation sub-resolution porosity cannot be analysed. Identical grey levels could either be associated with distributions.differences in porosity Yet some or differences classification in composition, uncertainty but this remains cannot be as distinguished materials listed by the as bi-modal general “silica matrix”data. and “lithic fragments” could not be further classified. Despite the complementary radiation utilized,The sub-resolutionmetallic content was porosity quantified cannot as 0.12% be analysed. of the volume, Identical distributed grey levels among could 1412 eitherspherules— be associated witha much differences lower amount in porosity than reported or differences in the literature in composition, (~4.6%) [30]. butThis thiscould cannot be partly be due distinguished to the fact by the bi-modalthat we excluded data. the partially corroded particles and the related corrosion products as they generally involveThe volume metallic expansion. content was By quantifiedincluding these, as 0.12% the oftotal the metal volume, phases distributed accounts among for 4.36% 1412 ofspherules—a the muchvolume, lower in line amount with values than from reported the literature in the literature [30]. (~4.6%) [30]. This could be partly due to the fact Analyses resulted in detailed data on the morphology of the impactite, and on the distribution that we excluded the partially corroded particles and the related corrosion products as they generally and size variability of vesicles. We identified 60,151 vesicles, constituting ≈7.2% of the total impactite involve volume expansion. By including these, the total metal phases accounts for 4.36% of the volume, volume. The porosity size range is very large, and small sized structures (below 25 voxels, 9.07 × 10−4 mm3) inare line dominant with values in number, from but the not literature in volume. [30]. AnalysesIn comparison resulted to previous in detailed investigations data on the using morphology polished sections of the impactite, [23], the numbers and on theof different distribution and sizetypes variability of objects of identified vesicles. (e.g., We identified 60,151 vesicles 60,151 and vesicles, 1412 metal constituting spherules)≈7.2% are orders of the of total magnitudes impactite volume. Thehigher, porosity increasing size range the trustworthiness is very large, of and trends small in sizedthe data. structures (below 25 voxels, 9.07 × 10−4 mm3) are dominantHydrogen in number, containing but notphases, in volume. such as iron corrosion products from the weathering of metallic spherules,In comparison could be toclearly previous identi investigationsfied. However, usingextensive polished alterati sectionson of the [23 metallic], the numbers parts (and of different types of objects identified (e.g., 60,151 vesicles and 1412 metal spherules) are orders of magnitudes higher, increasing the trustworthiness of trends in the data. J. Imaging 2018, 4, x FOR PEER REVIEW 18 of 23 J. Imaging 2018, 4, 72 18 of 24 therefore the high, incoherent scattering due to hydrogen) hindered the identification of variations of trace elements such as Cu, Re, Ir, Pt, Au, and Co, which in principle provide high contrast in neutronHydrogen imaging. containing These trace phases, elements such asmay iron be corrosion better detected products in from non-altered the weathering (hydrogen-free) of metallic impactitespherules, samples. could be clearly identified. However, extensive alteration of the metallic parts (and therefore the high,Contrary incoherent to results scattering reported due in past to hydrogen) studies [23, hindered30], the attempted the identification identification of variations of kamacite of trace (5– 10%elements Ni) and such taenite as Cu, (20–74% Re, Ir, Pt, Ni) Au, appeared and Co, to which reveal in th principleat larger provide spherules high are contrast characterised in neutron by a imaging. higher NiThese content. trace This elements could may be due be better to Ni-rich detected spherule in non-altereds being more (hydrogen-free) resistant to impactitecorrosion samples.and therefore remainingContrary larger. to resultsAlternatively, reported the in results past studiesmight be [23 biased,30], the by attemptedimage artefacts identification due to the of depletion kamacite of(5–10% radiation Ni) andacross taenite larger (20–74% particles, Ni) especially appeared toin revealthe case that of larger X-rays—though spherules are less characterised for neutrons. by Clarificationa higher Ni content.of this discrepancy This could might be due require to Ni-rich a focussed spherules destructive being more investigation resistant to guided corrosion by andthe presentedtherefore remainingdata. larger. Alternatively, the results might be biased by image artefacts due to the depletionRare, ofmicron radiation sized across precipitation larger particles, of salt especiallycrystals in in miniaturized the case of X-rays—though structures akin less to for evaporites neutrons. haveClarification been detected. of this These discrepancy weathering might products require have a focussed escaped destructive unnoticed in investigation previous studies, guided possibly by the becausepresented the data. salts were removed during sample preparations. WeRare, conclude micron that sized bi-modal precipitation imaging of can salt provide crystals a inwealth miniaturized of information structures on multi-phase akin to evaporites objects, suchhave as been impactites, detected. non-destructively These weathering and products is hence have highly escaped suited unnoticed in particular in previous for initial studies, studies possibly which preservebecause thethe saltsspecimen were removedfor further during potentially sample destruc preparations.tive studies, if still required. The rich imaging data canWe also conclude guide that further bi-modal studies imaging in order can to k provideeep destruction a wealth to of a information minimum and on multi-phasemaximise focussed objects, informationsuch as impactites, extraction. non-destructively A wide range and of isexemplary hence highly analytical suited inand particular visualisation for initial tools studies have whichbeen demonstratedpreserve the specimen successfully for for further use in potentially such volumetric destructive studies. studies, if still required. The rich imaging data can also guide further studies in order to keep destruction to a minimum and maximise focussed Authorinformation Contributions: extraction. C.B.K., A A.B.D. wide rangeand M.S. of conceived exemplary and analytical supervised and the visualisationproject; A.F., M.S., tools F.O. have and beenC.G. acquireddemonstrated the imaging successfully data; A.F. for perf useormed in such tomography volumetric reconstruction, studies. volume registration (with contribution from K.M. and M.L.), data analysis, and created figures; V.A.D. wrote the segmentation algorithm and helped improvingAuthor Contributions: figures; A.F. wroteC.B.K., the A.B.D. original and manuscript M.S. conceived and curated and supervised review and the editing project; with A.F., inputs M.S., from F.O. the and other C.G. acquired the imaging data; A.F. performed tomography reconstruction, volume registration (with contribution authors. from K.M. and M.L.), data analysis, and created figures; V.A.D. wrote the segmentation algorithm and helped Acknowledgments:improving figures; A.F.Camilla wrote H. theTrinderup original and manuscript Knut Conradsen and curated from reviewthe Technical and editing University with of inputs Denmark from are the other authors. gratefully acknowledged for the useful discussion. The authors wish to thank V.F. Buchwald for providing the sample.Acknowledgments: The 3D ImagingCamilla Centre H. Trinderupat the Technical and Knut Universi Conradsenty of Denmark from the is Technical also gratefully University acknowledged. of Denmark This are projectgratefully receives acknowledged funding from for thethe usefulEuropean discussion. Union’s The Horizon authors 2020 wish research to thank and V.F. innovation Buchwald programme for providing under the sample. The 3D Imaging Centre at the Technical University of Denmark is also gratefully acknowledged. This grant agreement No. 654000. This work has been partially financed by the Interreg project “ESS & MAX IV: Cross project receives funding from the European Union’s Horizon 2020 research and innovation programme under Bordergrant agreementScience and No. Society”. 654000. Constructive This work has comments been partially from the financed reviewers by thehelped Interreg to significantly project “ESS improve & MAX the IV: manuscript.Cross Border Science and Society”. Constructive comments from the reviewers helped to significantly improve the manuscript. Conflicts of Interest: The authors declare no conflict of interest. The founding sponsors had no role in the design ofConflicts the study; of Interest:in the collection,The authors analys declarees, or no interpretation conflict of interest. of data; The in founding the writing sponsors of the hadmanuscript, no role in and the designin the of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results. decision to publish the results.

AppendixAppendix A A SliceSlice z = z 415. = 415.

(a) (b)

Figure A1. Cont.

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J. Imaging 2018, 4, x FOR PEER REVIEW 19 of 23

(e) (f) (e) (f)

(g()g )

FigureFigureFigure A1. A1. A1. ImpactiteImpactite Impactite corresponding corresponding corresponding slices slicesslices for for z zz = == 415. 415. 415. ((aa ()a) )X-rayX-ray X-ray volume; volume; ((bb ()b) neutron )neutron neutron volume; volume; volume; (c ()c (RGB)c )RGB RGB falsefalsefalse colour colour colour representation; representation; representation; ( d ((d)d ))JET JETJET false falsefalse colourcolour representation;representation; representation; ((ee ())e )maskmask mask selectingselecting selecting the the the impactite impactite impactite (foreground);(foreground);(foreground); (f ()f ( )MRFf MRF) MRF segmentation; segmentation; segmentation; ( g((gg) ))vesicle vesiclevesicle distribution distribution of of the the impactite.impactite. impactite.

SliceSlice z = z 673. = 673. Slice z = 673.

(a) (b) (a) (b) Figure A2. Cont.

J. Imaging 2018, 4, 72 20 of 24 J. J.Imaging Imaging 2018 2018, 4, ,4 x, xFOR FOR PEER PEER REVIEW REVIEW 2020 of of 23 23

(c()c ) (d(d) )

(e()e ) (f()f )

(g(g) )

FigureFigure A2. A2. Impactite Impactite corresponding corresponding slices slices for for z z= =673. 673. ( a()a )X-ray X-ray volume; volume; ( b(b) )neutron neutron volume; volume; ( c()c )RGB RGB Figure A2. Impactite corresponding slices for z = 673. (a) X-ray volume; (b) neutron volume; (c) RGB falsefalse colour colour representation; representation; ( d(d) )JET JET false false colour colour representation; representation; ( e()e )mask mask selecting selecting the the impactite impactite false colour representation; (d) JET false colour representation; (e) mask selecting the impactite (foreground);(foreground); ( f()f )MRF MRF segmentation; segmentation; ( g()g )vesicle vesicle distribution distribution of of the the impactite. impactite. (foreground); (f) MRF segmentation; (g) vesicle distribution of the impactite. SliceSlice z z= =913. 913. Slice z = 913.

(a()a ) (b(b) )

Figure A3. Cont.

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J.J. Imaging Imaging 2018,, 4,, x 72 FOR PEER REVIEW 2121 of of 23 24

Figure 7. X-ray and neutron attenuation ranges for the different material classes identified in the Figure 7. X-ray and neutron attenuation ranges for the different material classes identified in the impactite.Figure 7. X-ray and neutron attenuation ranges for the different material classes identified in the J. Imaging 2018, 4, x FOR PEER REVIEW impactite. 11 of 23 J. Imaging 2018, 4, x FOR PEER REVIEW impactite. 11 of 23

3 −1 Table 2. Theoretical density ρ (g/cm3) and linear neutron attenuation μ (cm−1, for 4 Å neutrons) values Table 2. Theoretical density ρ (g/cm3) and linear neutron attenuation μ (cm−1, for 4 Å neutrons) values J. Imaging 2018, 4, x FOR PEER REVIEW ofTable selected 2. Theoretical minerals density (non-porous) ρ (g/cm expected) and linear in theneutron impactite attenuation 11[23] of 23and μ (cm corresponding, for 4 Å neutrons) segmentation values of selected minerals (non-porous) expected in the impactite [23] and corresponding segmentation materialof selected class minerals and attenuation (non-porous) ranges. expected in the impactite [23] and corresponding segmentation material class and attenuation ranges. material class and attenuation ranges. Chemical ρ μ (4 Å) Class Material X-ray Neutron Mineral Chemical ρ μ (4 Å) Class Material X-ray Neutron Chemical ρ 3 μ (4 −Å)1 Class Material X-ray 3 Neutron−1 Mineral Formula (g/cm3) (cm−1) Colour Class ρ (g/cm3) μ (cm−1) Mineral Formula (g/cm3) (cm−1) Colour Class ρ (g/cm3) μ (cm−1) Quartz FormulaSiO2 (g/cm2.65 ) (cm0.293) Colour■ MatrixClass glass ρ1.2–2.5 (g/cm ) 0.04–0.60μ (cm ) Quartz SiO2 2.65 0.293 ■ Matrix glass 1.2–2.5 0.04–0.60 MagnetiteQuartz FeSiO3O24 (e) 5.172.65 0.9260.293 ■ MatrixIron oxides( fglass) 2.5–5.21.2–2.5 0.08–0.750.04–0.60 Magnetite Fe3O4 5.17 0.926 ■ Iron oxides 2.5–5.2 0.08–0.75 MagnetiteHematite Fe23O34 5.245.17 0.9360.926 ■ Iron oxides 2.5–5.2 0.08–0.75 Hematite Fe2O3 5.24 0.936 ■ Iron oxides 2.5–5.2 0.08–0.75 HematiteIlmenite FeTiOFe2O33 4.795.24 0.8980.936 ■ Iron oxides 2.5–5.2 0.08–0.75 Ilmenite FeTiO3 4.79 0.898 ■ Iron oxides 2.5–5.2 0.08–0.75 GoethiteIlmenite FeO(OH)FeTiO3 4.134.79 3.0380.898 ■ IronIron oxihydroxides oxides 2.2–5.12.5–5.2 0.58–1.450.08–0.75 Goethite FeO(OH) 4.13 3.038 ■ Iron oxihydroxides 2.2–5.1 0.58–1.45 Goethite FeO(OH) 4.13 3.038 ■ Iron oxihydroxides 2.2–5.1 0.58–1.45 Troilite FeS 4.61 0.616 ■ Fe-Ni + troilite 4.4–6.7 0.32–1.60

Troilite FeS 4.61 0.616 Fe-Ni + troilite 4.4–6.7 0.32–1.60 Troilite ) FeS 4.61 0.616 ■ Fe-Ni + troilite 4.4–6.7 0.32–1.60 Pyrrhotite Fe1 (1−x)S 4.61 0.616 ■ Fe-Ni + troilite 4.4–6.7 0.32–1.60 Pyrrhotite Fe− (1−x)S 4.61 0.616 ■ Fe-Ni + troilite 4.4–6.7 0.32–1.60

11 of 23 11 of PyrrhotiteKamacite FeFe0.9(1Ni−x)S0.1 4.617.9 1.5760.616 ■ Fe-NiFe-Ni spherules + troilite 6.4–12.3 4.4–6.7 0.33–1.680.32–1.60 Kamacite Fe0.9Ni0.1 7.9 1.576 ■ Fe-Ni spherules 6.4–12.3 0.33–1.68 (cm Kamacite Fe0.80.9Ni0.20.1 7.9 1.576 ■ Fe-Ni spherules 6.4–12.3 0.33–1.68

Taenite Feμ Ni 8.01 1.672 Fe-Ni spherules 6.4–12.3 0.33–1.68 Taenite Neutron Fe0.8Ni0.2 8.01 1.672 ■ Fe-Ni spherules 6.4–12.3 0.33–1.68

Taenite Fe 0.8Ni0.2 8.01 1.672 ■ Fe-Ni spherules 6.4–12.3 0.33–1.68 Ferrite ) Fe 7.89 1.469 Fe-Ni spherules 6.4–12.3 0.33–1.68 Ferrite 3 Fe 7.89 1.469 ■ Fe-Ni spherules 6.4–12.3 0.33–1.68 Figure 7. X-ray and neutron attenuationFerrite ranges for Fethe different 7.89material classes1.469 identified■ in the Fe-Ni spherules 6.4–12.3 0.33–1.68 impactite.

An exampleX-ray of the segmentation is shown in Figu re 8, where individual X-ray and neutron slices An example of (g/cm the segmentation is shown in Figure 8, where individual X-ray and neutron slices ρ (g) Figure 7. X-ray and neutron attenuationare compared.An example ranges Matrix for of the glass differentsegmentation materials material is are shownclasses shown inidentified Figuin blue,re 8,in lithic wherethe inclusions individual in X-ray shades and of neutron green, oxidic slices Table 2. Theoretical density ρ (g/cmare 3compared.) and linear neutronMatrix attenuationglass materials μ (cm −are1, for shown 4 Å neutrons) in blue, values lithic inclusions in shades of green, oxidic impactite. corrosionare compared. productsFigure Matrix A3. inImpactite glassorange/pink, correspondingmaterials and are slices metallicshown for z = in913. phases blue, (a) X-ray lithic in volume; shades inclusions (b )of neutron red. in volume;Inshades Table (c )of RGB3 green, the volume oxidic of selected minerals (non-porous)corrosion expected products Figurein the A3.impactite inImpactite orange/pink, [23] corresponding and corresponding and slices metallic for z = segmentation 913.phases (a) X-ray in volume;shades (b )of neutron red. volume;In Table (c) RGB3 the volume corrosion productsfalsefalse colour in representation; orange/pink, ( (dd)) andJET JET false metallic colour phasesrepresentation; in shades ( (ee)) mask of selecting red. In the Table impactite 3 the volume fraction 4 Å neutrons) values , for of each material class is reported. Figure 7. X-ray and neutron attenuation ranges for the different material classes identified in the 3 1 −1 Tablematerial 2. Theoreticalclass and attenuation density ρ (g/cm ranges.fraction3)− and of linear each(foreground); neutron material attenuation(f) MRFclass segmentation; is reported. μ (cm−1, (forg ) vesicle 4 Å neutrons) distribution values of the impactite. Table 2. Theoretical density ρ (g/cmfraction) and of linear each(foreground); neutron material attenuation (f) MRFclass segmentation; is reported. μ (cm , (forg ) vesicle 4 Å neutrons) distribution values of the impactite. 0.83 ) impactite. n of selected minerals (non-porous) expected in the impactite [23] and corresponding segmentation μ (cm of selected mineralsChemical (non-porous) ρ expectedTableμ (4 Å)3. in Material the impactiteClass classes [23] and and 3Materialrespective corresponding volumeX-ray segmentation fracti onNeutron of the −1 solid volume of the impactite as

μ Table A1. Density ρ (g/cm3) and linear neutron attenuation μ (cm−1) values of the materials classes Table 3. MaterialMaterial classes and respective volume fraction of the solid volume of the impactite as Mineralmaterial class and attenuation ranges.3 −1Table A1. Density ρ (g/cm ) and linear neutron attenuation3 µ (cm−1 ) values of the materials classes Iron oxides Iron oxides Iron oxides 2.5–5.2 0.08–0.75 2.5–5.2 0.08–0.75 3 Table 3. Material classes and Iron oxides respective 2.5–5.2 0.08–0.75 −1 volume fraction of the solid volume of the impactite as materialTable 2. TheoreticalclassFormula and attenuation density (g/cmρ (g/cm ranges.) ) resultedand (cm linearused) from neutron for Colourthe the MRFMatrix glass MRF attenuation segmentation.segmentation. 1.2–2.5 0.04–0.60 μClass (cm The , for values 4 Å neutrons)ρwere (g/cm defined) valuesμ by (cm selecting ) representative areas in the Fe-Ni + troilite troilite Fe-Ni + 4.4–6.7 0.32–1.60 Fe-Ni + troilite troilite Fe-Ni + 4.4–6.7 0.32–1.60 used for the MRF segmentation. The values were deﬁned by selecting representative areas in 2.90 /Z) the Fe-Ni spherules Fe-Ni spherules Fe-Ni spherules 6.4–12.3 0.33–1.68 6.4–12.3 0.33–1.68 resulted from the MRF segmentation. Fe-Ni spherules 6.4–12.3 0.33–1.68

Quartz SiO2 2.65 resulted0.293 from the■ MRF segmentation.Matrix glass 1.2–2.5 0.04–0.60 ρ of selected mineralsChemical (non-porous) ρ expectedμ (4 Å) volumein the andClassimpactite calculating [23] the andIron oxihydroxides Materialcorresponding 2.2–5.1 corresponding 0.58–1.45 meanX-ray X-raysegmentation and Neutron neutron attenuation values. Mineral Chemical ρ μ (4 #Å) volume Class andClass Colour calculating theMaterial corresponding meanX-rayMaterial X-ray and Neutron neutron attenuation values. Volume % MagnetiteMineral Fe3O4 5.17 3 0.926#−1 Class ■Colour Iron oxides 2.5–5.2Material3 0.08–0.75 −1 Volume % material classFormula and attenuation (g/cm ranges.3) (cm#−1 ) ClassClassColour Colour X-ray ρ ClassNeutron μ ρ Material(g/cm3) μ (cm−1) Volume % 2 3 in the material classes identified different #1 ■ 3 Matrix −glass1 Material 78.14 Hematite Fe O 5.24 0.936# Class Colour X-ray3Ironρ [g/cm oxides]−1 Neutron 2.5–5.2µ [cm ] 0.08–0.75 Material Quartz SiO2 2.65 0.2931 Colour■ [g/cmMatrix] [cmglass] Matrix 1.2–2.5 glass 0.04–0.60 as impactite of the volume solid of the on 78.14

Quartz SiO2 2.65 0.2931 ■ Matrix glass Matrix 1.2–2.5 glass 0.04–0.60 78.14 Chemical3 ρ μ (4 Å) Class■ Material X-ray neutron slices and X-ray where individual 8, re Neutron n ■ ■ ■ ■ ■ ■ ■ ■ Ilmenite FeTiO 4.79 0.89821 ■ Iron■ 1.6Matrix oxides (high neutron 2.5–5.2 0.27 attenuation 0.08–0.75 μ ) Matrix glass 0.83 Magnetite Fe3O4 5.17 0.926 ■ ■ Iron oxides 2.5–5.2 0.08–0.75 n MagnetiteMineral Fe3O4 5.17 3 0.92612− 1 ■ 1.6 IronMatrix oxides0.27 (high neutron 2.5–5.23 attenuation 0.08–0.75−1 Matrix μ glass) 0.83 Formula (g/cm ) (cm22 ) Class Colour■ 1.5ClassMatrix (highρ neutron (g/cm 0.73) attenuationμ (cm Matrix) (high μn) neutron attenuation0.83µ n) Goethite FeO(OH) 4.13 3.038 Colour ■ Iron oxihydroxides 2.2–5.1 0.58–1.45 Hematite Fe2O3 5.24 0.9363 ■ ■ Iron oxides Lithic 2.5–5.2 fragments 0.08–0.75 13.78n Hematite Fe2O3 5.24 0.93623 3 ■ 1.5 Iron1.0 oxides 0.73 Lithic 2.5–5.2 0.19 fragments Matrix 0.08–0.75 (high neutron Lithic attenuation fragments 13.78 μ ) 2 ■ TroiliteQuartz SiOFeS 4.612.65 0.6160.293 segmentation corresponding and [23] impactite the 3 ■ Fe-NiMatrix + troiliteglass Lithic 4.4–6.71.2–2.5 fragments 0.32–1.600.04–0.60 13.78 3 44 ■ ■ 0.65Lithic fragments 0.18 (low ρ/Z) Lithic fragments (low ρ/Z)2.90

Ilmenite FeTiO 4.79 0.8983 1.0 Iron oxides0.19 2.5–5.2 0.08–0.75 Lithic fragments Matrix glass 78.14 3 ■ Ilmenite FeTiO3 4 4.79 0.89845 ■ Iron3.5 oxidesLithic fragments 2.5–5.2 0.36 0.08–0.75(low ρ Iron/Z) oxides (dominantly maghemite)2.90

Magnetite Fe(1−Ox) 5.17 0.926 ) ■ Iron oxides 2.5–5.2 0.08–0.75 Pyrrhotite Fe S 4.61 0.616 ■ Fe-Ni + troilite 4.4–6.7 0.32–1.60 spherules Fe-Ni 0.12

4 Lithic fragments (low ρ/Z) 2.90 fragments Lithic 13.78 Goethite FeO(OH) 4.13 3.0384 1 ■ ■ 0.65Iron oxihydroxides0.18 2.2–5.1 0.58–1.45 Lithic fragments (low ρ/Z) Goethite FeO(OH) 4.13 3.03856 − ■ Iron oxihydroxides3.15Iron oxides (dominantly 2.2–5.1 1.20 0.58–1.45 maghemite) Iron oxihydroxides (dominantly 3.16 goethite) Hematite Fe0.92O30.1 5.24 0.9365 ■ IronIron oxides oxides (dominantly 2.5–5.2 0.08–0.75 maghemite) 3.16 Kamacite Fe Ni 7.9 1.57655 7 ■ ■ 3.5Fe-Ni 5.2 Ironspherules 0.36 oxides (dominantly 6.4–12.3 0.80 Iron 0.33–1.68 oxidesFe-Ni maghemite) corroded(dominantly spherules maghemite) or containing 3.16 troilite Troilite FeS 4.61 0.6166 (4 Å) ■ Fe-NiIron + oxihydroxidestroilite 4.4–6.7 (dominantly 0.32–1.60 goethite) 0.89 Troilite FeS 4.61 0.616 (cm Fe-Ni + troilite 4.4–6.7 0.32–1.60 3 6 μ ■ Iron oxihydroxides (dominantly goethite) 0.89 IlmeniteTaenite FeFeTiO0.8Ni0.2 8.014.79 1.6720.8988 ■ Fe-NiIron7.8 spherules oxides 6.4–12.3 2.5–5.2 0.82 0.33–1.680.08–0.75 Fe-Ni spherules (low fragments Lithic Pyrrhotite Fe(1−x)S 4.61 0.61666 ■ ■ 3.15Fe-Ni Iron + oxihydroxidestroilite 1.20 4.4–6.7 Iron(dominantly oxihydroxides 0.32–1.60 goethite) (dominantly goethite) 0.89 Pyrrhotite Fe(1−x)S 4.61 0.6167 ■ Fe-NiFe-Ni +corroded troilite spherules 4.4–6.7 or 0.32–1.60 containing troilite 0.19 Goethite FeO(OH) 4.13 neutron attenuation ) and linear 3.038 ■ Iron oxihydroxides 2.2–5.1 0.58–1.45 Ferrite Fe 7.89 3 1.4697 ■ Fe-NiFe-Ni spherules corroded spherules 6.4–12.3 or 0.33–1.68 containing troilite 0.19 Kamacite Fe0.9Ni0.1 7.9 1.57677 ■ 5.2Fe-NiFe-Ni spherules corroded 0.80 spherules 6.4–12.3 Fe-Ni corroded or 0.33–1.68 containing spherules troilite or containing 0.19 troilite Kamacite Fe0.9Ni0.1 7.9 1.576 ) ■ Fe-Ni spherules 6.4–12.3 0.33–1.68 8 3 Fe-Ni spherules 0.12 Matrix (high neutron attenuation neutron attenuation (high Matrix Troilite FeS 4.61 0.61688 ■ ■ 7.8Fe-Ni + troilite0.82 Fe-Ni 4.4–6.7 spherules 0.32–1.60 Fe-Ni spherules 0.12 maghemite) Iron oxides (dominantly 3.16 0.8 0.2 ■ Taenite Fe0.8Ni0.2 8.01 1.6728 ■ Fe-Ni spherules Fe-Ni 6.4–12.3 spherules 0.33–1.68 0.12 Taenite Fe Ni 8.01 1.672 ρ Fe-Ni spherules 6.4–12.3 0.33–1.68 Pyrrhotite Fe(1−x)S 4.61 0.616 ■ Fe-Ni + troilite 4.4–6.7 0.32–1.60 goethite) (dominantly Iron oxihydroxides 0.89 FerriteAn example of Fethe segmentation7.89 is (g/cm shown1.469 in Figu■re 8, whereFe-Ni individual spherules X-ray 6.4–12.3 and neutron 0.33–1.68 slices ρ

(g/cm ■ Ferrite Fe 7.89 1.469 Fe-Ni spherules 6.4–12.3 0.33–1.68 troilite or containing spherules corroded Fe-Ni 0.19 0.9 0.1 ■ areKamacite compared. MatrixFe Ni glass materials7.9 are 1.576 shown in blue, lithic Fe-Niinclusions spherules in shades 6.4–12.3 of green, 0.33–1.68 oxidic Taenite Fe0.8Ni0.2 8.01 1.672 ■ Fe-Ni spherules 6.4–12.3 0.33–1.68 corrosionAn example products of thein orange/pink,segmentation andis shown metallic in Figu phasesre 8, wherein shades individual of red. X-rayIn Table and 3neutron the volume slices 1.576 7.9 1.672 8.01 FerriteAn example of Fethe segmentation7.89 is shown1.469 in Figu■re 8, where 0.898 4.79 Fe-Ni individual spherules X-ray 6.4–12.3 and neutron 0.33–1.68 slices 5.17 0.926 0.926 5.17 0.936 5.24 3

0.1 0.2 2.65 0.293 0.293 2.65 S 4.61 0.616 0.616 S 4.61 4 3 fraction of each material class is reported. 2 are compared. Matrix glass materials are shown in blue, lithic inclusionsx) in shades of green, oxidic

O O −

are compared. Matrix glass materials are shown in blue, lithic inclusions Ni in Ni shades of green, oxidic 3 2 ■ ■ ■ ■ ■ ■ ■ ■ (1 corrosionAn example products of thein orange/pink,segmentation and is shown metallic in Figu phasesre 8, wherein shades individual of red.0.9 X-ray0.8 In Table and 3neutron the volume slices Formula

Table 3. Material classes and respective volumeChemical fraction of the solid volume of the impactite as fractionare compared. of each Matrix material glass class materials is reported. are shown in blue, lithic inclusions in shades of green, oxidic , x FOR PEER REVIEW resulted from the MRF segmentation. X-ray and neutron attenuation ranges for the 4 Material classes and respective volume fracti classes and respective Material Theoretical density Theoretical , corrosion products in orange/pink, and metallic phases in shades of red. In Table 3 the volume # Class Colour Material Volume % % Volume Material Colour Class # 6 8 7 1 2 5 4 Table #3. MaterialClass Colour classes and respective volumeMaterial fraction of the solid volume ofVolume the impactite % as 3

2018 fraction of each material class is reported. resulted from the MRF segmentation. resulted1 from the■ MRF segmentation. Matrix glass 78.14 of selected minerals (non-porous) expected in expected (non-porous) minerals of selected ranges. attenuation material class and Figure 7. in Figu is shown the segmentation An example of Table 3. resulted from the MRF segmentation. impactite. impactite. Table 2. Ferrite Fe 7.89 1.469 1.469 Ferrite Fe 7.89 Quartz SiO Troilite FeS 4.61 0.616 0.616 FeS Troilite 4.61 Taenite Fe Taenite Ilmenite FeTiO Mineral Goethite FeO(OH) 4.13 3.038 Hematite Fe Hematite Kamacite Fe Magnetite Fe Table 3. Material■ classes and respective volume fraction of the solid nvolumePyrrhotite Fe of the impactite as 2# Class Colour Matrix (high neutronMaterial attenuation μ ) Volume0.83 % J. Imaging resulted from the■ MRF segmentation. oxidic green, of shades in inclusions lithic shown in blue, are materials glass Matrix are compared. volume the 3 Table In red. of shades in phases metallic and in orange/pink, products corrosion material class is reported. of each fraction 13 ■ LithicMatrix fragments glass 78.1413.78 24 ■ MatrixLithic (high fragments neutron attenuation(low ρ/Z) μn) 2.900.83 2# Class ■Colour Matrix (high neutronMaterial attenuation μn) Volume0.83 % 5 ■ Iron oxides (dominantly maghemite) 3.16 31 ■ LithicMatrix fragments glass 13.7878.14 46 ■ Iron oxihydroxidesLithic fragments (dominantly (low ρ/Z) goethite) 2.90 0.89 42 ■ MatrixLithic (high fragments neutron attenuation(low ρ/Z) μn) 2.900.83 7 ■ Fe-Ni corroded spherules or containing troilite 0.19 53 ■ Iron oxidesLithic (dominantly fragments maghemite) 13.78 3.16 8 ■ Fe-Ni spherules 0.12 64 ■ Iron oxihydroxidesLithic fragments (dominantly (low ρ/Z) goethite) 0.892.90 ■ 75 ■ Fe-NiIron corroded oxides spherules (dominantly or containing maghemite) troilite 0.193.16 ■ 86 ■ Iron oxihydroxidesFe-Ni spherules (dominantly goethite) 0.120.89 7 ■ Fe-Ni corroded spherules or containing troilite 0.19

8 ■ Fe-Ni spherules 0.12

J. Imaging 2018, 4, 72 22 of 24

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