Water softens the host silicates, enhances their electrical conductivity, and changes deformation patterns and the resulting textures under stress. In extreme cases hydrogen can induce melting.
We plan to explore the mechanism (and associated coefficients) for hydrogen diffusion within the two most abundant phases of the upper mantle - (Mg,Fe)2SiO4 and (Mg,Fe)SiO3 at realistic conditions of temperature, pressure, and stress. We will investigate the most efficient diffusion pathways: dislocation lines and stacking fault planes as we employ molecular dynamics (MD) simulations based on both ab initio (AI) and reactive force fields (FF).
We will compare our theoretical results with experimental data via collaborations with the University of Montpellier.
Then we will use the diffusion information to adjust the mantle flow models to constrain rates of water transfer from subducting slabs into the surrounding mantle, via both solid diffusion and transport via melt pockets. This will help us predict patterns of water storage in the mantle, and evaluate the influence of water on overall mantle dynamics.
Requirements
- MSc in physics, geophysics, material science, or related field.
- Candidates with documented experience in computational geophysics, molecular dynamics, ab initio simulations, and experience from machine learning will be prioritized.
Supervisors
Professor Clinton Phillips Conrad
Call 1: Project start autumn 2021
This project is in call 1, starting autumn 2021. Read about how to apply