The oxide layer that forms naturally on steel acts as a ‘natural’ barrier to the ingress or desorption of hydrogen: for the storage and transport of H2, this barrier effect is beneficial as it reduces the risk of hydrogen embrittlement of the underlying metal; for electrolysers, it would help to reduce line losses due to permeation (leakage) through the pipes by limiting desorption; in nuclear fusion applications, they would form a radiological barrier for tritium. However, the values of the parameters {diffusion; solubility; permeability} for hydrogen in the numerous possible oxide compositions and structures—which are necessary to quantify this barrier effect—are virtually non-existent in the literature. The main objective of the thesis will be to rapidly generate a reliable database covering a large number of iron oxide compositions and microstructures. The PhD student will combine rapid synthesis and screening methods (combinatorial synthesis of iron-based oxides with varying structures and compositions using HiPIMS, in situ monitoring and AI-driven optimisation, to be further developed) with techniques for local characterisation of hydrogen distribution (SIMS, nanoSIMS) via the use of isotopic tracers (deuterium) following gaseous exposure in a home-built apparatus. Concentration profiles will be processed using a routine developed (in Python) by the PhD student taking into account the composition and microstructure duality of the oxide layers. The expected final outcome would be a ‘3D’ mapping of hydrogen transport parameters in {Fe, O, Metal1, Metal2} quaternary systems, incorporating the concept of oxide microstructure. This approach could be applied to other systems, or even directed towards the search for optimised coating compositions.