Accuracy of timescales retrieved from diffusion modeling in olivine: A 3D perspective

Shea, Thomas; Costa, Fidel; Krimer, Daniel; Hammer, J. E.

doi:10.2138/am-2015-5163

Cited by 93 publications

(72 citation statements)

References 61 publications

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“…Measuring the dimensions of crystals on a 2D section is problematic due to intersection effects. Sectioning even a single crystal of a given size and morphology can cause substantial variability in section dimensions (Shea et al, 2015a). As a result, tracking the transient growth of crystals with potentially complex morphologies in 2D likely leads to significant added uncertainty.…”

Section: Textural Analysesmentioning

confidence: 99%

Forming Olivine Phenocrysts in Basalt: A 3D Characterization of Growth Rates in Laboratory Experiments

Mourey

Shea

2019

Front. Earth Sci.

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Our current knowledge of the genesis, ascent, storage, and eruption of mafic magmas is intimately linked with olivine, its primary crystal cargo. Recent claims that phenocrystsize crystals can grow rapidly and non-concentrically are challenging our perception of what olivine zoning represents (e.g., controlled by growth and/or diffusion), and whether accurate magma crystallization and diffusion timescales can be retrieved. A series of cooling experiments using a dry basalt was carried out in order to quantify the kinetics of olivine growth as a function of the degree of undercooling, and to characterize morphological changes occurring with time. After a 24 h equilibration step at 1290 • C (10 • C above the olivine liquidus), experiments were rapidly cooled to final temperatures T f = 1270, 1255, 1240, or 1220 • C (imposing undercoolings of − T = 10, 25, 40, and 60 • C, respectively). Growth rates estimated via 3D microtomography renderings of experimental crystals attain 10 −7 m/s, and are found to be almost an order of magnitude higher than those calculated using 2D sections of the same experiments. We show that mm-sized crystals similar to those found in natural Kīlauea samples can be produced after a few hours under moderate undercooling conditions (25-60 • C). Growth rates decrease faintly with time, accompanying transitions between skeletal/hopper and more polyhedral morphologies. Growth rates generally increase until − T = 40 • C, and decrease slightly at − T = 60 • C as rates of nucleation likely increase. The − T = 40 • C vicinity may therefore represent a thermal "sweet spot" for the formation of phenocrysts in dry basalt. Olivine overgrowths on crystals that survived initial dissolution grow slower than homogeneously nucleated crystals, illustrating how new and old crystals in natural magmas likely respond differently to a thermal perturbation. We suggest that the main growth direction of natural olivine (a-or c-axis) may be a sensitive function of undercooling and the presence of a pre-existing growth substrate. Olivine grows faster along the a-axis under moderate to high undercooling conditions, while preferred development along the c-axis likely occurs under lower undercooling conditions and/or as rims grow around existing crystals. The early history of skeletal olivine crystals is controlled by diffusion in the melt (diffusion-controlled growth regime), while their long-term compositional zoning history is mainly controlled by diffusive re-equilibration.

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Section: Textural Analysesmentioning

confidence: 99%

Forming Olivine Phenocrysts in Basalt: A 3D Characterization of Growth Rates in Laboratory Experiments

Mourey

Shea

2019

Front. Earth Sci.

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“…Variable x is the distance along the c axis ([001] direction) and D c is the relevant diffusion coefficient of Cr (Ganguly et al, ). The effect of modeling a one‐dimensional profile extracted at approximately random from a three dimensional shape has been previously modeled (Shea et al, ) but is considered further below.…”

Section: Discussionmentioning

confidence: 99%

“…Despite the care taken in extract orthopyroxene crystals with simple geometries, and of similar sizes, there exists considerable variability in diffusive length scales and hence cooling rates. Three‐dimensional sectioning effects may lengthen profiles (e.g., Shea et al, ) or result in measured core (peak) temperatures being too low. Without knowing the exact geometry of each measured crystal and the location of the measured section, it is not possible to accurately determine the extent to which profiles have been enlongated by sectioning.…”

Section: Discussionmentioning

confidence: 99%

“…Without knowing the exact geometry of each measured crystal and the location of the measured section, it is not possible to accurately determine the extent to which profiles have been enlongated by sectioning. However, to estimate the potential uncertainty from sectioning effects alone on cooling rates, five 4‐mm‐long (along the c axis) crystals with various simplified geometries were modeled following Shea et al () and Krimer and Costa (; [a] an idiomorphic orthopyroxene crystal with [001], [010], [100], and [210] faces [modified from Krimer & Costa, 2017]; [b] as [a], but with rounded edges; [c] as [b], but considerably more rounded; [d] as [c], but more rounded such that there are no flat faces; [e] a sphere). These were passed through a reasonable cooling trajectory (log η = −17.5 K −1 ·s −1 ) with diffusion modeled using:

\frac{\partial C}{\partial t} = D_{x} ((), \frac{\partial^{2} C}{\partial x^{2}}) + D_{y} ((), \frac{\partial^{2} C}{\partial y^{2}}) + D_{z} ((), \frac{\partial^{2} C}{\partial z^{2}})

(the extension of (3) in three dimensions, where x , y , and z are the a , b , and c directions, respectively) then a plane was cut that includes a vector within ~15–20° of [001], and where the extracted core temperature is equal to the original temperature.…”

Section: Discussionmentioning

confidence: 99%

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Testing Orthopyroxene Diffusion Chronometry on Rocks From the Lanzo Massif (Italian Alps)

Jollands

Müntener

2019

JGR Solid Earth

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Rocks from the northern and central zones of the Lanzo peridotite massif contain large (>3 mm) orthopyroxene crystals, often within a fine‐grained matrix. The rocks have been decompressed and cooled from the spinel peridotite field, via plagioclase peridotite to near the ocean floor. Orthopyroxene preserves evidence of the early part of this cooling history in the form of Cr and Al (plus various trace elements) loss profiles. Independent geological constraints can be placed on the cooling rates by considerations of absolute age (slowest possible cooling rate) and thermal modeling (fastest possible cooling rate), allowing a test of cooling rates retrieved from orthopyroxene diffusion chronometry. Quantitative profiles (mostly along the crystallographic c axis) and qualitative maps were measured for a series of orthopyroxene crystals, and the cooling rate extracted by diffusion modeling. It is possible to successfully extract reliable cooling rates from frozen Cr diffusion profiles in orthopyroxene, suggesting that the available experimental data are applicable to natural orthopyroxene. However, there are caveats related to the diffusion mechanism, boundary conditions when passing through the spinel‐plagioclase peridotite transition, and the potential effect of ubiquitous clinopyroxene exsolution lamellae on diffusion pathways and element partitioning. The usual issues of extracting 2‐D or 1‐D data from a 3‐D system apply, in addition to issues relating to shearing of orthopyroxene grains leading to moving boundaries. Al diffusion in orthopyroxene may be a more useful tool than Cr for assessing cooling rates, but its diffusivity is currently unconstrained.

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“…Given the ease with which the BSE images of a large number of crystals can be gathered, it is possible to obtain a large statistical data set that can be used to characterize the deposits and the crystals. Numerical simulation of 2D crystal sections in thin section may allow understanding the 3D crystals and magma processes in a similar manner to the quantification of crystal size distribution studies (Higgins 1994;Morgan and Jerram 2006), olivine and pyroxene zoning patterns, and timescales (Pearce 1984;Shea et al 2015). However, such analysis for complexly zoned crystals like plagioclase is basically not available.…”

Section: Introductionmentioning

confidence: 99%

Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach

Cheng

Costa

Carniel

2017

American Mineralogist

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Many plagioclase phenocrysts from volcanic and plutonic rocks display quite complex chemical and textural zoning patterns. Understanding the zoning patterns and variety of crystal populations holds clues to the processes and timescales that lead to the formation of the igneous rocks. However, in addition to a "true" natural complexity of the crystal population, the large variety of plagioclase types can be partly artifacts of the use of two-dimensional (2D) petrographic thin sections and random cuts of three-dimensional (3D) plagioclase crystals. Thus, the identification of the true number of plagioclase populations, and the decision of which are "representative" crystal sections to be used for detailed trace element and isotope analysis is not obvious and tends to be subjective.Here we approach this problem with a series of numerical simulations and statistical analyses of a variety of plagioclase crystals zoned in 3D. We analyze the effect of increasing complexity of zoning based on 2D chemical maps (e.g., backscattered electron images, BSE). We first analyze the random sections of single crystals, and then study the effect of mixing of different crystal populations in the samples. By quantifying the similarity of the compositional histogram of about a hundred 2D plagioclase sections it is possible to identify the so-called reference and ideal sections that are representative of the real 3D crystal populations. These section types allow filtering out the random-cut effects and explain more than 90% of the plagioclase compositional data of a given sample. Our method allows the identification of the main crystal populations and representative crystals that can then be used for a more robust interpretation of magmatic processes and timescales.

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Accuracy of timescales retrieved from diffusion modeling in olivine: A 3D perspective

Cited by 93 publications

References 61 publications

Forming Olivine Phenocrysts in Basalt: A 3D Characterization of Growth Rates in Laboratory Experiments

Forming Olivine Phenocrysts in Basalt: A 3D Characterization of Growth Rates in Laboratory Experiments

Testing Orthopyroxene Diffusion Chronometry on Rocks From the Lanzo Massif (Italian Alps)

Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach

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