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PhD candidate in modelling realistic oxide nanoparticles using machine learning based simulations (PRE206_31082026_31)
- Barcelona, Spain
- Chemistry
The importance of oxide nanoparticles spans from fundamental astronomy (e.g. nanosilicate dust particles) to applied catalysis (e.g. photoactive TiO2 and electroactive IrO2 nanoparticles). Across these fields understanding the detailed structure and chemistry of these nanospecies is paramount for determining their properties and how they interact with their environment. The project will aim to simulate a range of realistic oxide nanoparticles with sizes from a few 10s of atoms to several 1000s of atoms. In each case, machine learned interatomic potentials (MLIPs) will be developed to describe