American Mineralogist, Volume 93, pages 1816–1822, 2008

Timescales of spherulite crystallization in obsidian inferred from water concentration profiles

Jo n at h a n M. Ca s t r o ,1,* Pi e r r e Be c k ,2 Hu g h Tu f f e n ,3 Al e x a n d e r R.L. Ni c h o l s ,4 Do n a l d B. Di n g w e l l ,5 a n d Mi c h a e l C. Ma r t i n 6

1Department of Mineral Sciences, Smithsonian Institution, MRC-119, Washington, D.C. 20013, U.S.A. 2Laboratoire de Planetologie de Grenoble, 122 rue de la Piscine, Grenoble 38041, France 3Environmental Science Department, Lancaster University, Bailrigg, Lancaster LA1 4YW, U.K. 4Institute for Research on Earth Evolution (IFREE), Japan Agency for Marine Earth Science and Technology (JAMSTEC), 2-15 Nasushima-cho, Yokosuka, Kanagawa 237-0061, Japan 5Earth and Environmental Sciences, LMU-University of Munich, Theresienstrasse 41/III, 80333 Munich, Germany 6Advanced Light Source, Lawrence Berkeley National Laboratory, Berkeley, California 94720, U.S.A.

Ab s t r a c t We determined the kinetics of spherulite growth in obsidians from Krafla volcano, Iceland. We measured water concentration profiles around spherulites in obsidian by synchrotron Fourier transform infrared spectroscopy. The distribution of OH– groups surrounding spherulites decreases exponen- tially away from the spherulite-glass border, reflecting expulsion of water during crystallization of an

anhydrous paragenesis (plagioclase + SiO2 + clinopyroxene + magnetite). This pattern is controlled by a balance between the growth rate of the spherulites and the diffusivity of hydrous solute in the rhyolitic melt. We modeled advective and diffusive transport of the water away from the growing spherulites by numerically solving the diffusion equation with a moving boundary. Numerical models fit the natural data best when a small amount of post-growth diffusion is incorporated in the model. Comparisons between models and data constrain the average spherulite growth rates for different temperatures and highlight size-dependent growth among a small population of spherulites. Keywords: Spherulite, diffusion, obsidian, crystallization

In t r o d u c t i o n analyzing chemical gradients within crystals (Costa and Dungan The rates and timescales of magmatic processes exert 2005) and glasses (Castro et al. 2005) combined with diffusion first-order control over the behavior of magmatic systems. For modeling of the elemental distributions. Here, we build on these example, the rate of decompression during magma ascent may studies by determining the crystallization timescales of small dictate the manner in which volatiles are released from the melt, spherical crystal aggregates in obsidian, known as spherulites ultimately influencing degassing and the explosivity (e.g., Gon- (Fig. 1). We present synchrotron Fourier transform infrared nermann and Manga 2007). Similarly, crystallization in volcanic spectroscopic (SFTIR) measurements of water concentration conduits and lava flows may generate excess volatile pressure, profiles around spherulites in obsidian. We then model the leading to nonlinear extrusion and endogenous dome explosions concentration profiles by numerically solving the advection- (e.g., Sparks 1997). Clearly, our ability to model magmatic diffusion equation for a range of temperatures to yield model processes depends on accurate determinations of timescales of crystallization timescales. processes such as crystallization and bubble growth. Ge o l o g i c a l b a c k g r o u n d Direct measurement of the timing and duration of magmatic phase changes (e.g., crystallization) is challenging due to the Spherulites are radiating, commonly concentrically arranged extreme inaccessibility of magmatic environments; efforts to do aggregates of one or more anhydrous minerals set in a glassy so have been relegated to analyzing natural crystal chronometers matrix (Fig. 1). They occur in obsidian domes, large-volume in quenched rocks. Crystal-size distribution (CSD) analysis, vitrophyric ash-flow tuffs (e.g., Smith et al. 2001), and in shal- for example, has provided estimates of crystal growth rates in low volcanic conduits (e.g., Stasiuk et al. 1996). magmatic systems (e.g., Cashman 1988). However, temporal Spherulites are inferred to have nucleated and grown in information based on CSD interpretations may be subject to response to large undercoolings (>200 °C) rapidly imposed large errors, owing to the uncertainties of the underlying laws on the magma by its degassing and quenching (e.g., Swanson governing crystal growth, including assumptions that the growth et al. 1989). As dictated by the thermal profile of the magma rates of all crystals was the same. body (Manley 1992), spherulitic obsidian develops in spatially Advances in timescale determinations have been made by restricted zones (e.g., Manley and Fink 1987; Stevenson et al. 1994), comprising a transitional facies that separates the rapidly * E-mail: [email protected] quenched, outermost vitrophyric rhyolite from a devitrified

0003-004X/08/1112–1816$05.00/DOI: 10.2138/am.2008.2904 1816