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Licensed Unlicensed Requires Authentication Published by De Gruyter April 3, 2017

Thermo-elastic behavior of grossular garnet at high pressures and temperatures

  • Sula Milani EMAIL logo , Ross J. Angel , Lorenzo Scandolo , Mattia L. Mazzucchelli , Tiziana Boffa Ballaran , Stephan Klemme , Maria C. Domeneghetti , Ronald Miletich , Katharina S. Scheidl , Mariana Derzsi , Kamil Tokár , Mauro Prencipe , Matteo Alvaro and Fabrizio Nestola
From the journal American Mineralogist


The thermo-elastic behavior of synthetic single crystals of grossular garnet (Ca3Al2Si3O12) has been studied in situ as a function of pressure and temperature separately. The same data collection protocol has been adopted to collect both the pressure-volume (P-V) and temperature-volume (T-V) data sets to make the measurements consistent with one another. The consistency between the two data sets allows simultaneous fitting to a single pressure-volume-temperature Equation of State (EoS), which was performed with a new fitting utility implemented in the latest version of the program EoSFit7c. The new utility performs fully weighted simultaneous fits of the P-V-T and P-K-T data using a thermal pressure EoS combined with any P-V EoS. Simultaneous refinement of our P-V-T data combined with that of KT as a function of T allowed us to produce a single P-V-T-KT equation of state with the following coefficients:

V0=1664.46(5)A˚3,KTO=166.57(17)GPa andK=4.96(7)α(300K,1bar)=2.09(2)×105K1

with a refined Einstein temperature (θE) of 512 K for a Holland-Powell-type thermal pressure model and a Tait third-order EoS. Additionally, thermodynamic properties of grossular have been calculated for the first time from crystal Helmholtz and Gibbs energies, including the contribution from phonons, using density functional theory within the framework of the quasi-harmonic approximation.


This work has been supported by the ERC Starting Grant (no. 307322) to F. Nestola. M.A. has been supported by the SIR-MIUR grant MILE DEEp (no. RBSI140351) to M. Alvaro. M.D. acknowledges computational grant G62-24 at Interdisciplinary Centre for Mathematical and Computational Modeling (ICM) of the University of Warsaw. R.M. and K.S.S. acknowledge support through grant BE532003 of the University of Vienna. We thank Tom Duffy (Princeton) for advice and discussions. We also thank R. Carampin (IGGCNR, Padova) for help with the electron microprobe analyses. We thank Andrea D’Alpaos and Mario Putti (University of Padova) for advice on least-squares minimization. We thank two anonymous reviewers for helpful comments.

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Received: 2016-5-16
Accepted: 2016-11-21
Published Online: 2017-4-3
Published in Print: 2017-4-1

© 2017 by Walter de Gruyter Berlin/Boston

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