Modeling the morphological evolution of mineral surface upon (bio)alteration : Implications for the concept of biosignatures

Defining the imprints left by microorganisms on the surface of altered minerals upon bioalteration appears to be a prerequisite for the search of life in the geological record on Earth and beyond. Nowadays, the description of the changes in mineral surface morphology associated with microbially-mediated mineral dissolution is limited to the misleading concept of etching features resembling “in size, shape and distribution” to bacteria. In the present project, we propose to revisit this concept by adopting an independent theoretical modeling perspective. Building upon our current numerical developments, we suggest simulating the morphological evolution of a mineral surface based on a stochastic approach whereby atom detachment is scaled to the probability of breaking the bonds that connect it to the surface. Such bond-breaking probabilities are known to depend on the chemical bonding structure of the parent phase and on the nature of the reactant (e.g., protons, water, siderophores). Consequently, distinct morphological patterns may be anticipated when biomolecules are involved. To test this hypothesis, the work will consist in (i) refining existing kinetic Monte Carlo codes that we have developed over the past few years to simulate various mineral structures ; (ii) running sensitivity tests to explore the impact of various reactants ; and (iii) defining invariant descriptors that can relate the outputs of the simulations (i.e., the simulated surface morphology) to the input parameters (i.e., bond strength and reactant), to pave the way to the definition of biosignatures of mineral alteration based on first principles. The work will mainly take place at ISTerre in Grenoble, with several visits to ITES (Strasbourg) covered by the project expected over the course of the internship. To lead this project, the candidate must have programming skills (Fortran, Matlab, or Python). Additional knowledge in crystallography and/or statistics would be a plus. This internship is intended to be continued by a PhD thesis funded by the ERC project Mobidic (2021-2026).