Characterization of 1D and 2D Materials with Tip-Enhanced Raman Spectroscopy

María Olivia Avilés, The University of Western Ontario

Abstract

Carbon-based materials, such as 1D single-walled carbon nanotubes (SWCNT) or 2D graphene, are promising materials for a variety of applications in energy storage, biosensors, and medical imaging applications. Similarly, beyond graphene, 2D transition metal dichalcogenides (TDM) that can have either a metallic or semiconducting character have gained interest for potential applications in electronics and photonics. Specifically, metallic TMDs such as vanadium disulfide (VS₂) show potential applications in optoelectronics and lithium-ion batteries. On the other hand, semiconducting TDMs like tungsten disulfide (WS₂) show a direct band gap, making them interesting for photovoltaic applications, transistors, or photodetectors. The characterization of the chemical and physical properties of such nanomaterials thus become necessary to understand their performance. Moreover, given that structural defects have a negative impact on their integration into devices understanding the formation of these defects is therefore critical. Raman spectroscopy is one of the fundamental techniques that can help to identify chemical properties of materials revealing functional groups at the surface or the presence of crystalline and structural defects. Tip-Enhanced Raman Spectroscopy (TERS) combines Raman spectroscopy and atomic force microscopy (AFM) to obtain spatial resolution that goes beyond the diffraction limit. TERS relies on the resonance of the local surface plasmon (LSPR) and a lightning-rod effect in the vicinity of the apex of a sharp metallic nanoscale tip, yielding to sub 20nm spatial resolution.

In this thesis, 1D and 2D carbon materials such as single walled carbon nanotubes and graphene, are characterized through TERS and artificial intelligence (AI) methods. Artificial neural networks (ANNs), a sub-field of machine learning are applied to analyze large amount of collected spectra and sort them efficiently based on their metallic or semiconductor character. 2D metallic VS₂ and semiconductive WS₂ are synthesized using chemical vapor deposition and analyzed though TERS discovering surface ripples and hidden layers. Furthermore, through the characterization of VS₂, it was found that photo-oxidation process promoted the production of vanadium oxides. Other characterization techniques such as Kelvin probe microscopy (KPFM) and nanomechanical modes were applied to reveal the electronic properties of these materials.