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Atomistic Models of OH Defects in Nominally Anhydrous Minerals

Nanochemistry Research Institute, Curtin University of Technology, GPO Box 1987, Perth, Western Australia 6845, Australia, e-mail: kate@ivec.org

The first 20% of the full text of this article appears below.

	INTRODUCTION

 
The Earth’s upper mantle may contain substantial amounts of water dissolved in nominally anhydrous minerals (NAMs) such as the Mg₂SiO₄ polymorphs, pyroxenes and garnets. This water, incorporated into the crystal lattice as hydrogen defects, can have a profound influence on the physical properties of the mantle, even when present at low concentrations. An understanding of these defects at the atomic level is therefore of fundamental importance for the development of models of the evolution and dynamics of the Earth’s mantle.

The incorporation of hydrogen and its influence on the properties of NAMs has been an active area of research for almost three decades. High pressure synthesis of hydrous phases, analyzed using a range of spectroscopic techniques (see Kohn 2006; Libowitzky and Beran 2006; Rossman 2006), have yielded a wealth of information that allow us to determine the concentration of hydrogen that can be accommodated by various NAMs, and provide information on the mechanisms of uptake. However, these data are often complex, and difficult to interpret unambiguously. Computer simulation methods can offer real insights at the atomic level, often not accessible by experiment, and provide an alternative way to explore hydrogen defects in minerals.

The past 20 years have seen an explosion in the use of computational modeling to study a range of phenomena in minerals. These include the high-pressure behavior of mantle (Oganov and Price 2005) and core (Vocadlo et al. 2003) phases, diffusion (Walker et al. 2003), dislocation structures (Walker et al. 2005), and mineral surface reactivity (Kerisit et al. 2005). A broad introduction to the methods and applications to the geosciences is given in the recent MSA volume edited by Cygan and Kubicki (2001). In this chapter we explore the contribution of computational . . . [Full Text of this Article]

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