Iron (Fe) is an essential micronutrient for the development of oceanic biomass, which is one of the main carbon sinks on a global scale. In about 30% of the oceans, the development of this biomass is constrained by an iron deficiency that limits primary production. This deficiency is related to the very low concentrations of soluble Fe (bioaccessible in first approximation) in the surface waters. In order to understand the origin and consequences of these low Fe levels (in the order of ng Fe/L), various models have sought to determine the variability of Fe inputs to the ocean, particularly via aerosols. In the last decade, progress in the measurement of Fe isotopic composition has made it possible to test the sensitivity of these models to spatiotemporal variations in inputs, especially in the case of anthropogenic aerosols, which are known to be highly soluble in cloud water. However, this approach is made difficult by the existence of isotopic fractionation phenomena that would be linked to the dissolution of particles within clouds. Our previous works seem to show that this isotopic effect is linked to the existence of a competition between Fe-ligand complexes in solution and the presence of some similar complexes on the surface of particles. The FAAR project aims to explain these processes through a double approach, both experimental and theoretical. First, it will simulate the dissolution of model Fe aerosol particles in solutions mimicking cloud water, to link the isotopic composition of the soluble Fe to the characteristics of the surface complexes. These model particles are alpha hematite nanoparticles whose crystal growth has been controlled, in order to produce nanoparticles with preferential facets exposed to cloud water. Second, this fractionation will be estimated via quantum chemical methods, based on Ab Initio calculations and compared, in the same way, to the respective stabilities of the surface and solution complexes, in order to conclude on the possibility of extending our simulations to more realistic atmospheric conditions.