Quantifying alignment and quality of graphene nanoribbons: A polarized Raman spectroscopy approach
Graphene nanoribbons (GNRs) are atomically precise stripes of graphene with tunable electronic properties, making them promising for room-temperature switching applications like field-effect transistors (FETs). However, challenges persist in GNR processing and characterization, particularly regardin...
Gespeichert in:
Veröffentlicht in: | Carbon (New York) 2024-01, Vol.218, p.118688, Article 118688 |
---|---|
Hauptverfasser: | , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Graphene nanoribbons (GNRs) are atomically precise stripes of graphene with tunable electronic properties, making them promising for room-temperature switching applications like field-effect transistors (FETs). However, challenges persist in GNR processing and characterization, particularly regarding GNR alignment during device integration. In this study, we quantitatively assess the alignment and quality of 9-atom-wide armchair graphene nanoribbons (9-AGNRs) on different substrates using polarized Raman spectroscopy. Our approach incorporates an extended model that describes GNR alignment through a Gaussian distribution of angles. We not only extract the angular distribution of GNRs but also analyze polarization-independent intensity contributions to the Raman signal, providing insights into surface disorder on the growth substrate and after substrate transfer. Our findings reveal that low-coverage samples grown on Au(788) exhibit superior uniaxial alignment compared to high-coverage samples, attributed to preferential growth along step edges, as confirmed by scanning tunneling microscopy (STM). Upon substrate transfer, the alignment of low-coverage samples deteriorates, accompanied by increased surface disorder. For high-coverage samples, the alignment is preserved, and the disorder on the target substrate is reduced compared to the low-coverage samples. Our extended model enables a quantitative description of GNR alignment and quality, facilitating the development of GNR-based nanoelectronic devices.
[Display omitted] |
---|---|
ISSN: | 0008-6223 1873-3891 |
DOI: | 10.1016/j.carbon.2023.118688 |