石墨烯
升华(心理学)
材料科学
接口
化学气相沉积
产量(工程)
反向
纳米技术
计算机科学
复合材料
数学
几何学
计算机硬件
心理治疗师
心理学
作者
Oliver J. Burton,Zachary Winter,Kenji Watanabe,Takashi Taniguchi,Bernd Beschoten,Christoph Stampfer,Stephan Hofmann
出处
期刊:ACS Nano
[American Chemical Society]
日期:2023-01-03
卷期号:17 (2): 1229-1238
被引量:19
标识
DOI:10.1021/acsnano.2c09253
摘要
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.
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