# Optimized substrates and measurement approaches for Raman spectroscopy   of graphene nanoribbons

**Authors:** Jan Overbeck, Gabriela Borin Barin, Colin Daniels, Mickael Perrin,, Liangbo Liang, Oliver Braun, Rimah Darawish, Bryanna Burkhardt, Tim Dumslaff,, Xiao-Ye Wang, Akimitsu Narita, Klaus M\"ullen, Vincent Meunier, Roman Fasel,, Michel Calame, Pascal Ruffieux

arXiv: 1907.01797 · 2020-01-08

## TL;DR

This paper develops a Raman-optimized substrate and mapping method to enhance the characterization of graphene nanoribbons, enabling detailed analysis of their vibrational modes and quality assessment.

## Contribution

It introduces a novel Raman-optimized device substrate and mapping approach that significantly improves spectral signal and resolution for GNR analysis.

## Key findings

- Achieved Raman signal enhancement factors up to 120.
- Successfully monitored geometry-dependent low-frequency modes.
- Compared experimental modes with first-principles calculations.

## Abstract

The on-surface synthesis of graphene nanoribbons (GNRs) allows for the fabrication of atomically precise narrow GNRs. Despite their exceptional properties which can be tuned by ribbon width and edge structure, significant challenges remain for GNR processing and characterization. In this contribution, we use Raman spectroscopy to characterize different types of GNRs on their growth substrate and to track their quality upon substrate transfer. We present a Raman-optimized (RO) device substrate and an optimized mapping approach that allows for acquisition of high-resolution Raman spectra, achieving enhancement factors as high as 120 with respect to signals measured on standard SiO2/Si substrates. We show that this approach is well-suited to routinely monitor the geometry-dependent low-frequency modes of GNRs. In particular, we track the radial breathing-like mode (RBLM) and the shear-like mode (SLM) for 5-, 7- and 9-atom wide armchair GNRs (AGNRs) and compare their frequencies with first-principles calculations.

---
Source: https://tomesphere.com/paper/1907.01797