This article presents a quantitative analysis of printed nanostructured networks using high-resolution 3D FIB-SEM nanotomography. The study investigates the morphology of printed networks of graphene, WS₂, and silver nanosheets (AgNSs), as well as silver nanowires (AgNWs), to understand how nanosheet/nanowire size influences network structure. A comprehensive toolkit is developed to extract morphological characteristics such as network porosity, tortuosity, specific surface area, pore dimensions, and nanosheet orientation, which are linked to network resistivity. The technique is extended to interrogate the structure and interfaces within printed vertical heterostacks, demonstrating its potential for device characterisation and optimisation. Liquid-deposited networks of 0D nanoparticles, 1D nanowires or nanotubes, and 2D nanosheets have shown great promise in emerging applications in printed electronics, sensing, catalysis, and energy storage. However, the performance of these devices is often limited by network morphology. Printed 2D networks tend to consist of porous, disordered arrays of nanosheets with variable degrees of connectivity, alignment, and inter-sheet coupling. These morphological factors heavily influence carrier mobility in nanosheet devices. The study demonstrates that the performance of printed 2D capacitors and transistors is crucially dependent on the morphological tailoring of dielectric layers to ensure spatial continuity and prevent interlayer electrical shorting. Network porosity and pore tortuosity determine the accessible nanosheet surface area for sensing or catalysis, as well as electrolyte infiltration and ion kinetics in battery and supercapacitor electrodes. Standard techniques such as mercury intrusion porosimetry (MIP) and N₂ BET analysis have been used to determine pore-size-distribution and specific surface area in thick, vacuum filtered nanosheet networks. However, these methods generally require sample volumes that are far beyond the scope of printed thin-film devices. FIB-SEM-NT effectively bridges the gap between these tomographic techniques by offering spatial resolutions of a few nanometres over representative sample volumes. This has been demonstrated through high-resolution reconstructions of oil shales, drug release coatings, fuel cells, and commercial battery electrodes. The study uses FIB-SEM-NT to interrogate the morphology of printed nanostructured networks at high resolution. It reports 3D imaging with a voxel size of 5 nm × 5 nm × 15 nm and demonstrates a suite of techniques to extract quantitative morphological information from these images. The study applies FIB-SEM-NT to characterise network structure in printed graphene, WS₂, and AgNS films, as well as AgNW networks, finding the morphological properties to scale with nanosheet or nanowire dimensions. This is then directly linked to the electrical resistivity of printed graphene networks of different nanosheet sizes. The analysis is extended to compareThis article presents a quantitative analysis of printed nanostructured networks using high-resolution 3D FIB-SEM nanotomography. The study investigates the morphology of printed networks of graphene, WS₂, and silver nanosheets (AgNSs), as well as silver nanowires (AgNWs), to understand how nanosheet/nanowire size influences network structure. A comprehensive toolkit is developed to extract morphological characteristics such as network porosity, tortuosity, specific surface area, pore dimensions, and nanosheet orientation, which are linked to network resistivity. The technique is extended to interrogate the structure and interfaces within printed vertical heterostacks, demonstrating its potential for device characterisation and optimisation. Liquid-deposited networks of 0D nanoparticles, 1D nanowires or nanotubes, and 2D nanosheets have shown great promise in emerging applications in printed electronics, sensing, catalysis, and energy storage. However, the performance of these devices is often limited by network morphology. Printed 2D networks tend to consist of porous, disordered arrays of nanosheets with variable degrees of connectivity, alignment, and inter-sheet coupling. These morphological factors heavily influence carrier mobility in nanosheet devices. The study demonstrates that the performance of printed 2D capacitors and transistors is crucially dependent on the morphological tailoring of dielectric layers to ensure spatial continuity and prevent interlayer electrical shorting. Network porosity and pore tortuosity determine the accessible nanosheet surface area for sensing or catalysis, as well as electrolyte infiltration and ion kinetics in battery and supercapacitor electrodes. Standard techniques such as mercury intrusion porosimetry (MIP) and N₂ BET analysis have been used to determine pore-size-distribution and specific surface area in thick, vacuum filtered nanosheet networks. However, these methods generally require sample volumes that are far beyond the scope of printed thin-film devices. FIB-SEM-NT effectively bridges the gap between these tomographic techniques by offering spatial resolutions of a few nanometres over representative sample volumes. This has been demonstrated through high-resolution reconstructions of oil shales, drug release coatings, fuel cells, and commercial battery electrodes. The study uses FIB-SEM-NT to interrogate the morphology of printed nanostructured networks at high resolution. It reports 3D imaging with a voxel size of 5 nm × 5 nm × 15 nm and demonstrates a suite of techniques to extract quantitative morphological information from these images. The study applies FIB-SEM-NT to characterise network structure in printed graphene, WS₂, and AgNS films, as well as AgNW networks, finding the morphological properties to scale with nanosheet or nanowire dimensions. This is then directly linked to the electrical resistivity of printed graphene networks of different nanosheet sizes. The analysis is extended to compare