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In recent years, liquid metal catalysts have emerged as a compelling choicefor the controllable, large-scale, and high-quality synthesis oftwo-dimensional materials. At present, there is little mechanisticunderstanding of the intricate catalytic process, though, of its governingfactors or what renders it superior to growth at the corresponding solidcatalysts. Here, we report on a combined experimental and computational studyof the kinetics of graphene growth during chemical vapor deposition on a liquidcopper catalyst. By monitoring the growing graphene flakes in real time usingin situ radiation-mode optical microscopy, we explore the growth morphology andkinetics over a wide range of CH4-to-H2 pressure ratios and depositiontemperatures. Constant growth rates of the flakes' radius indicate a growthmode limited by precursor attachment, whereas methane-flux-dependent flakeshapes point to limited precursor availability. Large-scale free energysimulations enabled by an efficient machine-learning moment tensor potentialtrained to density-functional theory data provide quantitative barriers for keyatomic-scale growth processes. The wealth of experimental and theoretical datacan be consistently combined into a microkinetic model that reveals mixedgrowth kinetics that, in contrast to the situation at solid Cu, is partlycontrolled by precursor attachment alongside precursor availability. Keymechanistic aspects that directly point toward the improved graphene qualityare a largely suppressed carbon dimer attachment due to the facileincorporation of this precursor species into the liquid surface and alow-barrier ring-opening process that self-heals 5-membered rings resultingfrom remaining dimer attachments.

Operando Characterization and Machine-Learning Surrogated Molecular  Simulations Reveal the Growth Kinetics of Graphene on Liquid Copper during  Chemical Vapor Deposition