This doctoral project aims to develop an innovative high-throughput screening approach for catalysts for the direct conversion of CO2 into synthetic fuels, known as CO2-FTS. This approach will combine a catalyst screening platform with in situ/operando characterization techniques and artificial intelligence methods to accelerate the discovery and optimization of high-performance catalysts. It aims to identify doped FeOx-type catalysts for the CO2-FTS reaction (>50% conversion, high selectivity towards C8-C16). Several high-throughput screening campaigns will allow for iterative optimization of compositions and reactive conditions. A numerical model of the parametric landscape will then be developed. This model will subsequently be coupled with multi-scale modeling from the active site to the reactor level. The developed catalysts will contribute to the energy transition by enabling a circular carbon economy.