Automotive catalysts are versatile porous materials, having prevented billions of tons of pollutants from entering the atmosphere. Their 3D structure-property relationships are complex, determined by porosity, particle size, and adhesion between substrate, washcoat base layer, and precious metal active components, therefore making them challenging to image and characterize at high resolution. We demonstrate several novel 3D microscopy approaches to imaging the pore structure of gasoline particulate filters (GPF), polymer electrolyte fuel cells (PEFC), and metal organic frameworks (MOF). We used X-ray microscopy for 3D imaging, pore analysis, and quantification of washcoat and substrate layers on a honeycomb support. 3D Reconstruction and segmentation was achieved through Deep Learning of GPF datasets. Further, X-ray nanotomography was used to study porous PEFC agglomerate structures and undertake simulations. Finally, FESEM “sweet spot” imaging was conducted to understand platinum nanoparticle decoration on perovskite catalysts, revealing details of terracing and exsolution not previously visible in SEM.