Scaling and statistics of bottom-up synthesized armchair graphene nanoribbon transistors

Bottom-up assembled nanomaterials and nanostructures allow for the studies of rich and unprecedented quantum-related and mesoscopic transport phenomena. However, it can be difficult to quantify the correlations between the geometrical or structural parameters obtained from advanced microscopy and measured electrical characteristics when they are made into macroscopic devices. Here, we propose a strategy to connect the nanomaterial morphologies and the device performance through a Monte Carlo device model and apply it to understand the scaling trends of bottom-up synthesized armchair graphene nanoribbon (GNR) transistors. A new nanofabrication process is developed for GNR transistors with channel length down to 7 nm. The impacts of the GNR spatial distributions and the device geometries on the device performance are investigated systematically through comparison of experimental data with the model. Through this study, challenges and opportunities of transistor technologies based on bottom-up synthesized GNRs are pinpointed, paving the way to the further improvement of the GNR device performance for future transistor technology nodes.

Automated summary

We propose a strategy to connect nanomaterial morphologies and device performance through a Monte Carlo device model, and apply it to understand the scaling trends of bottom-up synthesized armchair graphene nanoribbon (GNR) transistors. We systematically investigate the impacts of GNR spatial distributions and device geometries on device performance by comparing experimental data with the model. This study identifies challenges and opportunities for transistor technologies based on bottom-up synthesized GNRs, paving the way for further improvement of GNR device performance for future transistor technology nodes.