Nanostructured coatings combining order and disorder, such as those fabricated via layer-by-layer assembly (LBL), possess considerable practical significance. These coatings offer advantages in ease of fabrication compared to more highly ordered counterparts while exhibiting enhanced functionality due to their tunable properties. However, accurately modeling these systems remains challenging, as materials with nonrandom disorder require novel structural descriptors. The challenge of establishing robust structure-property relationships for multifunctional coatings has yet to be fully resolved. In this study, we apply microscopy-informed graph-theoretical models to address this issue, demonstrating their unique capability to characterize the intricate architecture of LBL films alongside their electrical, optical, and mechanical properties. Furthermore, graph-theoretical structural descriptors enable the design of conductivity-optimized LBL coatings, which can be effectively scaled from millimeter-scale laboratory samples to meter-scale curvilinear surfaces, such as drone wings and other multifunctional aerospace coatings.
