The role of precursor coverage in the synthesis and substrate transfer of graphene nanoribbons

Abstract

Graphene nanoribbons (GNRs) with atomically precise widths and edge topologies have well-defined band gaps that depend on ribbon dimensions, making them ideal for room-temperature switching applications like field-effect transistors (FETs). For effective device integration, it is crucial to optimize growth conditions to maximize GNR length and, consequently, device yield. Equally important is establishing device integration and monitoring strategies that maintain GNR quality during the transition from growth to device fabrication. Here, we investigate the growth and alignment of 9-atom-wide armchair graphene nanoribbons (9-AGNRs) on a vicinal gold substrate, Au(788), with varying molecular precursor doses (PD) and, therefore, different resulting GNR coverages. Our investigation reveals that GNR growth location on Au(788) substrate is coverage-dependent. Scanning tunneling microscopy shows a strong correlation between GNR length evolution and both PD and GNR growth location. Employing Raman spectroscopy, samples with eight different PDs were analyzed. GNR alignment improves with length, achieving near-perfect alignment with an average length of ∼40 nm for GNRs growing solely at the Au(788) step edges. To fully exploit GNR properties in device architectures, GNRs need to be transferred from their metallic growth substrate to semiconducting or insulating substrates. Upon transfer, samples with higher PD present systematically better alignment preservation and less surface disorder, attributed to reduced GNR mobility during the transfer process. Importantly, PD also affects the substrate transfer success rate, with higher success rates observed for samples with higher GNR coverages (77%) compared to lower GNR coverages (53%). Our findings characterize the important relationship between precursor dose, GNR length, alignment quality, and surface disorder during GNR growth and upon substrate transfer, offering crucial insights for the further development of GNR-based nanoelectronic devices.