An evolutive basin-scale reactive transport model for depicting the genesis of lithium deposits

Lithium (Li) is a lightweight alkali metal with a high electrochemical potential, making it a critical element in the energy transition. However, its demand is projected to increase 42-fold by 2040, positioning Li as a resource under significant criticality. Li originates from highly differentiated magmas and is distributed across subsurface plutonic rocks, surface volcanic deposits, and volatile phases. This primary Li can be leached by circulating low-temperature or hydrothermal fluids, partitioning Li among primary solid phases, alteration-derived mineral phases, and fluids. The nature of these alteration phases depends on various factors, including the temperature of fluid-rock interactions, fluid typology, primary Li content, Li-bearing minerals, and the structural positioning of Li. As such, reaction mechanisms play a critical role in the genesis of lithium deposits, which are closely linked to the evolution of fluid circulation and temperature over geological time. In this PhD thesis, we propose to model the genesis of lithium deposits throughout the evolution of sedimentary basins by tracing the migration of Li from source to deposit. Published data containing information on Li partitioning between liquid and solid phases will be used to derive simplified chemical laws through machine learning techniques for integration into the ArcTem basin simulator. These developments will enable the modelling of mineral reactivity processes within an evolving thermo-hydro-chemical model and will be applied to a well-documented case study.

Keywords: Geochemical cycle of lithium, basin modelling, digital geology, AI

• Academic supervisor    Prof Pauline COLLON, GeoRessources, ORCID : 0000-0001-8505-4961
• Doctoral School    ED607-SIReNa, Université de Lorraine
• IFPEN supervisor    Dr Nathalie COLLARD, nathalie.collard@ifpen.fr
• PhD location    IFPEN, Rueil-Malmaison, France
• Duration and start date    3 years, starting in the fourth quarter 2024 (Novembre 4)
• Employer    IFPEN
• Academic requirements    University Master degree in Earth sciences or Chemical sciences
• Language requirements    English level B2 (CEFR), Willingness to learn French    
• Other requirements    Numerical geology, geochemistry-thermochemistry, proficiency in Python programming, practical knowledge in AI

To apply, please send your cover letter and CV to the IFPEN supervisor indicated here below.