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Thermoelasticity of tremolite amphibole: Geophysical implications

  • Ye Peng EMAIL logo and Mainak Mookherjee
Published/Copyright: June 4, 2020
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Abstract

We investigated the structure, equation of state, thermodynamics, and elastic properties of tremolite amphibole [Ca2Mg5Si8O22(OH)2] up to 10 GPa and 2000 K, using first principles simulations based on density functional perturbation theory. We found that at 300 K, the pressure-volume results can be adequately described by a third-order Birch-Murnaghan equation of state with bulk moduli K0 of 78.5 and 66.3 GPa based on local density approximation (LDA) and generalized gradient approximation (GGA), respectively. We also derived its coefficients of the elastic tensor based on LDA and GGA and found that the LDA result is in good agreement with the experimental results. At 300 K, the shear modulus G0 is 58.0 GPa based on LDA. The pressure derivative of the bulk modulus K′ is 5.9, while that of the shear modulus G′ is 1.3. The second Grüneisen parameter, or δT= [–1/(αKT)](∂KT/∂T)P, is 3.3 based on LDA. We found that at ambient conditions, tremolite is elastically anisotropic with the compressional wave velocity anisotropy AVP being 34.6% and the shear wave velocity anisotropy AVS being 27.5%. At higher pressure corresponding to the thermodynamic stability of tremolite, i.e., ~3 GPa, the AVP reduces to 29.5%, whereas AVS increases to 30.8%. To evaluate whether the presence of hydrous phases such as amphibole and phlogopite could account for the observed shear wave velocity (VS) anomaly at the mid-lithospheric discontinuity (MLD), we used the thermoelasticities of tremolite (as a proxy for other amphiboles), phlogopite, and major mantle minerals to construct synthetic velocity profiles. We noted that at depths corresponding to the mid-lithosphere, the presence of 25 vol% amphibole and 1 vol% phlogopite could account for a VS reduction of 2.3%. Thus based on our thermoelasticity results on tremolite amphibole, it seems that mantle metasomatism could partly explain the MLD.

Acknowledgments

The authors thank two anonymous reviewers and the Associate Editor Sergio Speziale for their thorough reviews and constructive comments that enhanced the clarity of the manuscript. The authors acknowledge Aaron Ashley and Suraj Bajgain for their comments, which improved the manuscript.

  1. Funding

    This work is supported by the U.S. National Science Foundation grant EAR 1763215 and EAR 1753125. The authors acknowledge computing resources from the High Performance Computing, Research Computing Center, Florida State University and from the NSF Extreme Science and Engineering Discovery Environment (XSEDE) (TG-GEO170003).

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Received: 2019-07-02
Accepted: 2020-01-11
Published Online: 2020-06-04
Published in Print: 2020-06-25

© 2020 Walter de Gruyter GmbH, Berlin/Boston

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  18. Book Review
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