The durability of materials used in many areas of energy production is limited by their degradation in the operating environment, which is often oxidising and at high temperature. This is particularly true of High Temperature Electrolysers (HTE) for the production of ‘green’ hydrogen, or the fuel cladding used in nuclear reactors to produce electricity. Anti-corrosion coatings can/should be applied to improve the lifespan of these installations, thereby conserving resources. A process for synthesising coatings using a reactive vapour route with liquid organometallic precursors (DLI - MOCVD) appears to be a very promising process.
The aim of this thesis is to model and simulate the DLI-MOCVD coating synthesis process for the two applications proposed above. Simulation results (deposition rate, deposit composition, spatial homogeneity) will be compared with experimental results from large-scale ‘pilot’ reactors at the CEA in order to optimise the model's input parameters. On the basis of this CFD simulation/experiments dialogue, the optimum conditions for deposition on a scale 1 component will be proposed. A coupling between CFD simulations and Machine Learning will be developed to accelerate the change of scale and the optimisation of scale 1 deposits.