ACS Nano 17, 1229 (2023)
Reliable, clean transfer and interfacing of 2D material layers are technologically as important as their growth. Bringing both together remains a challenge due to the vast, interconnected parameter space. We introduce a fast-screening descriptor approach to demonstrate holistic data-driven optimization across the entirety of process steps for the graphene–Cu model system. We map the crystallographic dependences of graphene chemical vapor deposition, interfacial Cu oxidation to decouple graphene, and its dry delamination across inverse pole figures. Their overlay enables us to identify hitherto unexplored (168) higher index Cu orientations as overall optimal orientations. We show the effective preparation of such Cu orientations via epitaxial close-space sublimation and achieve mechanical transfer with a very high yield (>95%) and quality of graphene domains, with room-temperature electron mobilities in the range of 40000 cm²/(V s). Our approach is readily adaptable to other descriptors and 2D material systems, and we discuss the opportunities of such a holistic optimization.