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Dr. Fred Gaidies

Associate Professor, Department of Earth Sciences

 
 

 

High-resolution X-ray micro-computed tomography of Earth materials

Thanks to the financial support from the Canada Foundation for Innovation, the Ontario Research Fund, and the Faculty of Science at Carleton University I am happy to announce the successful set-up of Canada's first high-resolution X-ray micro-computed tomography (XR-µCT) laboratory for Earth material research. This laboratory allows me and my students to obtain quantitative microstructural and textural data that are essential to unravel fundamental atomic-scale processes that govern the formation of rocks.

Researchers interested to use XR-µCT are welcome in my laboratory. Please see here or contact me directly for more information (fred_gaidies.at.carleton.ca).

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The figure to the left is a virtual XR-µCT cross-section slice through a garnet mica schist from the Mazinaw Domain of the Grenville Province, SE Ontario. The different grey values correspond to different degrees of X-ray attenuation and allow to distinguish between garnet, biotite, ilmenite, muscovite, and quartz. Note that some muscovite grains pseudomorph staurolite which could be identified as tiny relict phase through EPMA.
Diameter of cross-section slice is ca. 3 cm, pixel size is ca. 15 µm.

Numerical simulation of metamorphic garnet growth with THERIA_G

THERIA_G (Gaidies et al., 2008a) is a numerical model that predicts the chemical composition of garnet and the mineral content of a rock during metamorphism considering Gibbs free energy minimization, chemical diffusion in garnet, and chemical fractionation associated with garnet crystallization. Since THERIA_G considers a nucleation history of garnet, earlier work that simulates the formation of compositional profiles in single garnet grains can now be extended to garnet populations. This offers the opportunity to compare garnet chemistries as well as garnet crystal size distributions, that are simulated for predefined conditions, with field observations. For the case where garnet crystallization is controlled by the rate of tectonothermal processes THERIA_G predicts a high rate of radial garnet growth at the beginning of garnet crystallization, slowing down with progressive growth and finally approaching a steady state. This is an important outcome because it directly impacts on the efficiency of chemical diffusion in garnet and the probability with which garnet chemical zoning is preserved during metamorphism.
THERIA_G is a platform-independent, free software and part of the Theriak/Domino program package. Experience with Theriak/Domino is required to successfully run THERIA_G. Please let me know if you are interested to experiment with THERIA_G and I can provide you with a copy.

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In the figure to the left you can see the compositional profile of a polyphase garnet crystal (from core to rim) that grew in a rock from the Eastern European Alps in response to changing pressure and temperature conditions during the Permian and the Cretaceous. Note that the squares reflect the observed garnet chemistry and that the lines correspond to the chemistry predicted through THERIA_G modelling. The X-ray maps of that garnet crystal and the pressure-temperature-time (P-T-t) path required to obtain this best fit between observed and predicted garnet chemistry are shown below. Many of the features of the chemical zoning observed in garnet from this rock could be reproduced with THERIA_G. This is an important result since it provides high-quality information on the P-T-t evolution within the Austroalpine continental crust during the Permian and the Cretaceous. Furthermore, it proves the great power of THERIA_G modelling for research in metamorphic and regional geology. For details on this project please refer to Gaidies et al. (2008b) or contact me directly.

 

 

 

 

 

 

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Distribution maps of Ca, Mg, Mn and Fe in garnet used for THERIA_G modelling (see above). The Ca-poor core grew during high-T/low-P metamorphism during the Permian, and the rim was formed along a Barrovian P-T path in the Cretaceous. The P-T-t path derived from this chemical pattern is shown below. For details on this project please refer to Gaidies et al. (2008b).

 

 

 

 

 

 

The figure below shows the model P-T path of metamorphism that was required to predict the observed garnet chemistry. Whereas THERIA_G predicts slow heating during the Permian (ca. 3ºC/Ma), a heating rate of more than 50ºC/Ma was required to model Eo-Alpine metamorphism in the Cretaceous. The lines (1) to (3) correspond to the P-T conditions at which garnet is predicted to become part of the thermodynamically stable mineral assemblage during heating which is often referred to as the garnet-in curve. Line (1) is the garnet-in before metamorphism in the Permian, line (2) reflects the conditions of incipient garnet growth at the onset of Eo-Alpine metamorphism in the Cretaceous, and line (3) is the garnet-in curve after garnet growth finished in the rock. The positions and shapes of the garnet-in curves were calculated with THERIA_G and the Theriak/Domino software. Note that progressive garnet crystallization shifts the garnet-in curve up-P/T so that relatively higher P-T conditions would be required for an additional garnet growth event. The grey field (4) in the figure below is the position of a mineral assemblage in P-T space that the rock had to develop in order to form the prominent grossular "shoulder" that is found in every Cretaceous garnet of this rock (this grossular "shoulder" can be seen in the compositional profile above).

 

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The kinetics of garnet nucleation during metamorphism

In collaboration with Dave Pattison (Calgary) and Christian de Capitani (Basel) I derived the first ab initio analysis of interface-controlled nucleation of garnet in metamorphic rocks (Gaidies et al., 2011). This is a major step in the understanding of rock formation as it discusses some of the most fundamental parameters and processes that impact on the crystallization of minerals in rocks. In this paper we present an approach that allows to quantify the relation between the departure from equilibrium required for a mineral reaction in a rock and interfacial energy. overstepYou can see this relationship in the figure to the left [for details see Gaidies et al. (2011)] calculated for the case of isobaric (3350 bar) nucleation of garnet in a metapelite from the aureole of the Nelson batholith (SE British Columbia). An important outcome of this study is that the rate of rock heating has a negligible influence on the departure from equilibrium required for interface-controlled nucleation (called "T-overstep" in the figure) compared to variations in interfacial energy ("sigma-prime"). In general, an increase in interfacial energy hinders nucleation, and the associated energy barrier can be overcome by an appropriate build-up of chemical energy through overstepping. Another interesting result is that there is an interfacial energy minimum above which nucleation of garnet is impossible regardless the departure from equilibrium. In the figure to the left, this minimum interfacial energy is ca. 0.04 J/m2.

sigma_maxThe figure to the right plots the relationship between the minimum interfacial energy above which nucleation of garnet is predicted not to happen in the metapelite from the Nelson aureole versus metamorphic pressure. As can be seen from this figure, the probability to nucleate garnet in this rock decreases with decreasing pressure. This is simply because the energy that would be released during nucleation (the chemical driving force for nucleation) is strongly pressure-dependent.

The figure below shows the P-T dependence of the chemical driving force for nucleation of garnet (Delta G_V) in the rock from the Nelson aureole [Fig. (b)], and how this relates to the chemical composition of a garnet nucleus [Figs. (c)-(f)]. Please note that the relationship outlined above is of paramount importance to metamorphic petrologists as its understanding allows not only to refine models of the thermal structure of Earth's crust and mantle but also opens the door to study rock texture formation from first principles. Our nucleation model provides the unique opportunity to compare predicted features of rock texture with observations in natural specimens. This approach bears tremendous potential to resolve the fundamental processes that control the formation of rocks on the basis of a detailed analysis of their texture and microstructure.

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