A new approach to crystallographic orientation measurement for apatite fission track analysis: Effects of crystal morphology and implications for automation

Peternell, Mark; Kohlmann, Fabian; Wilson, Christopher J.L.; Seiler, Christian; Gleadow, A. J. W.

doi:10.1016/j.chemgeo.2009.05.021

Cited by 43 publications

(49 citation statements)

References 17 publications

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“…Data at the periphery of a pole figure (projection onto a thin section plane) are of low quality and thus partly excluded from the population in display and LPO data processing, leading to the described bias. The automatic fabric analysers used here calculate the extinction angle, where no light gets through the system, by fitting the light amplitude values for each step of the polarizers to a sinusoid curve [73,74]. The low-quality effect of c -axes in a plane normal to the observation axes is caused by the G20 instrument often being unable to resolve the quadrant pair of the azimuth of these orientations.…”

Section: Results and Datamentioning

confidence: 99%

Physical analysis of an Antarctic ice core—towards an integration of micro- and macrodynamics of polar ice

Weikusat

Jansen

Binder

et al. 2017

Phil. Trans. R. Soc. A.

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Microstructures from deep ice cores reflect the dynamic conditions of the drill location as well as the thermodynamic history of the drill site and catchment area in great detail. Ice core parameters (crystal lattice-preferred orientation (LPO), grain size, grain shape), mesostructures (visual stratigraphy) as well as borehole deformation were measured in a deep ice core drilled at Kohnen Station, Dronning Maud Land (DML), Antarctica. These observations are used to characterize the local dynamic setting and its rheological as well as microstructural effects at the EDML ice core drilling site (European Project for Ice Coring in Antarctica in DML). The results suggest a division of the core into five distinct sections, interpreted as the effects of changing deformation boundary conditions from triaxial deformation with horizontal extension to bedrock-parallel shear. Region 1 (uppermost approx. 450 m depth) with still small macroscopic strain is dominated by compression of bubbles and strong strain and recrystallization localization. Region 2 (approx. 450–1700 m depth) shows a girdle-type LPO with the girdle plane being perpendicular to grain elongations, which indicates triaxial deformation with dominating horizontal extension. In this region (approx. 1000 m depth), the first subtle traces of shear deformation are observed in the shape-preferred orientation (SPO) by inclination of the grain elongation. Region 3 (approx. 1700–2030 m depth) represents a transitional regime between triaxial deformation and dominance of shear, which becomes apparent in the progression of the girdle to a single maximum LPO and increasing obliqueness of grain elongations. The fully developed single maximum LPO in region 4 (approx. 2030–2385 m depth) is an indicator of shear dominance. Region 5 (below approx. 2385 m depth) is marked by signs of strong shear, such as strong SPO values of grain elongation and strong kink folding of visual layers. The details of structural observations are compared with results from a numerical ice sheet model (PISM, isotropic) for comparison of strain rate trends predicted from the large-scale geometry of the ice sheet and borehole logging data. This comparison confirms the segmentation into these depth regions and in turn provides a wider view of the ice sheet.This article is part of the themed issue ‘Microdynamics of ice’.

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Section: Results and Datamentioning

confidence: 99%

Physical analysis of an Antarctic ice core—towards an integration of micro- and macrodynamics of polar ice

Weikusat

Jansen

Binder

et al. 2017

Phil. Trans. R. Soc. A.

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“…Wilson et al, 2003;Peternell et al, 2009) with an automatic fabric analyser from Russell-Head Instruments (models G20 and G50 for EDML and G50 for KCC). For each identified ice crystal in the thin section the measurement provides the orientation of the crystallographic c axis c by two spherical coordinates, azimuth ϑ in the interval (0,2π ) and colatitude ϕ in the interval (0,π/2), with respect to the vertical ice-core axis that we define to coincide with the z axis of the global coordinate system (Fig.…”

Section: Laboratory Ice Fabric Measurementsmentioning

confidence: 99%

Deriving micro- to macro-scale seismic velocities from ice-core <i>c</i> axis orientations

et al. 2018

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Abstract. One of the great challenges in glaciology is the ability to estimate the bulk ice anisotropy in ice sheets and glaciers, which is needed to improve our understanding of ice-sheet dynamics. We investigate the effect of crystal anisotropy on seismic velocities in glacier ice and revisit the framework which is based on fabric eigenvalues to derive approximate seismic velocities by exploiting the assumed symmetry. In contrast to previous studies, we calculate the seismic velocities using the exact c axis angles describing the orientations of the crystal ensemble in an icecore sample. We apply this approach to fabric data sets from an alpine and a polar ice core. Our results provide a quantitative evaluation of the earlier approximative eigenvalue framework. For near-vertical incidence our results differ by up to 135 m s −1 for P-wave and 200 m s −1 for S-wave velocity compared to the earlier framework (estimated 1 % difference in average P-wave velocity at the bedrock for the short alpine ice core). We quantify the influence of shearwave splitting at the bedrock as 45 m s −1 for the alpine ice core and 59 m s −1 for the polar ice core. At non-vertical incidence we obtain differences of up to 185 m s −1 for P-wave and 280 m s −1 for S-wave velocities. Additionally, our findings highlight the variation in seismic velocity at non-vertical incidence as a function of the horizontal azimuth of the seismic plane, which can be significant for non-symmetric orientation distributions and results in a strong azimuth-dependent shear-wave splitting of max. 281 m s −1 at some depths. For a given incidence angle and depth we estimated changes in phase velocity of almost 200 m s −1 for P wave and more than 200 m s −1 for S wave and shear-wave splitting under a rotating seismic plane. We assess for the first time the change in seismic anisotropy that can be expected on a short spatial (vertical) scale in a glacier due to strong variability in crystalorientation fabric (±50 m s −1 per 10 cm). Our investigation of seismic anisotropy based on ice-core data contributes to advancing the interpretation of seismic data, with respect to extracting bulk information about crystal anisotropy, without having to drill an ice core and with special regard to future applications employing ultrasonic sounding.

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“…The fabric analyser is an automated optical polarising microscope that determines the c ‐axis orientations of uniaxial materials at each pixel in the field of view with a spatial resolution of 5

μ

m pixel −1 (Wilson et al ., ; Peternell et al . , ; Wilson & Peternell, ). In addition to c ‐axis orientation maps retardation images are generated.…”

Section: Instrumentationmentioning

confidence: 99%

Reconstruction of 3D grain boundaries from rock thin sections, using an advanced polarised‐light microscopy method

Hammes¹,

Peternell²

2017

Journal of Microscopy

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Summary Grain boundaries play a significant role in materials by initiating reactions and collecting impurities. Here we present FAGO (Fabric Analyser Grain boundary recOnstruction), a first step towards the automatic determination of three‐dimensional (3D) grain boundary geometry using polarised light. The trace of the grain boundaries from 2D rock thin sections are determined primarily from data acquired using an automatic fabric analyser microscope and the FAME software (fabric analyser‐based microstructure evaluation; Peternell and colleagues and Hammes and Peternell). Based on the Fabric Analyser G50's unique arrangement of nine differently oriented light sources the retardation can be determined independently for each light direction and at each pixel in the field of view. FAGO combines these retardation datasets for each individual pixel together with retardation profiles across grain boundaries, to determine the orientations of the boundaries. The grain boundary traces are then broken up into segments of equal orientation, using the profile‐obtained orientation data. Finally, a 3D grain boundary model is reconstructed. The data processing is almost fully automatic using the MATLAB® environment. Only minor manual inputs are required.

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A new approach to crystallographic orientation measurement for apatite fission track analysis: Effects of crystal morphology and implications for automation

Cited by 43 publications

References 17 publications

Physical analysis of an Antarctic ice core—towards an integration of micro- and macrodynamics of polar ice

Physical analysis of an Antarctic ice core—towards an integration of micro- and macrodynamics of polar ice

Deriving micro- to macro-scale seismic velocities from ice-core <i>c</i> axis orientations

Reconstruction of 3D grain boundaries from rock thin sections, using an advanced polarised‐light microscopy method

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A new approach to crystallographic orientation measurement for apatite fission track analysis: Effects of crystal morphology and implications for automation

Cited by 43 publications

References 17 publications

Physical analysis of an Antarctic ice core—towards an integration of micro- and macrodynamics of polar ice

Physical analysis of an Antarctic ice core—towards an integration of micro- and macrodynamics of polar ice

Deriving micro- to macro-scale seismic velocities from ice-core &lt;i&gt;c&lt;/i&gt; axis orientations

Reconstruction of 3D grain boundaries from rock thin sections, using an advanced polarised‐light microscopy method

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Deriving micro- to macro-scale seismic velocities from ice-core <i>c</i> axis orientations