Exploiting nanoscale variations in two dimensional materials for predicting material properties and machine vision applications
- UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
- Kirby B. Schmidt (Creator)
- Institution
- The University of North Carolina at Greensboro (UNCG )
- Web Site: http://library.uncg.edu/
- Advisor
- Tetyana Ignatova
Abstract: Two dimensional nanomaterials are atomically thin sheets of molecules that have properties significantly different to their bulk counterparts. This dissertation investigates the electronic and optical properties of two dimensional materials and their Van der Waals heterostructures, employing Raman spectroscopy as a powerful tool for characterization. A relationship between strain, doping and photoluminescence in Van der Waals heterostructures is established which contribute to the nanovariations to the optical signal in microscale devices. These nanoscale variations in a two dimensional sensing devices contribute to inaccuracies in the detection of analytes adsorbed to the surface. Further, Machine vision techniques are also utilized to enhance the efficiency and accuracy of Raman spectroscopy data analysis and image registration. This registration leads to novel analysis of multispectral images. The research uses advanced strain analysis from Raman spectroscopy of two dimensional nanomaterials to register Raman spectral maps with images of data acquired from different microscopic techniques, such as Scanning Electron Microscopy, Kelvin Probe Force Microscopy, and Scanning Near-Field Optical Microscopy. Optical microscopy is also used for the rapid identification of high quality cleaved two dimensional flakes in an automated way. A one-stage object detection neural network is used for identifying high quality nanoflakes, and the model uses reinforcement learning as new high quality flakes are confirmed via Raman spectroscopy. Novel machine vision techniques are further used to subsegment multiterraced layers. The results contribute to the advancement of two dimensional materials research and provide insights into potential applications of these materials in various fields.
Exploiting nanoscale variations in two dimensional materials for predicting material properties and machine vision applications
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Created on 5/1/2023
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Additional Information
- Publication
- Dissertation
- Language: English
- Date: 2023
- Keywords
- Computer Vision, Nanomaterials, Raman Spectroscopy
- Subjects
- Nanostructured materials $x Optical properties
- Nanostructured materials $x Electric properties
- Raman spectroscopy
- Computer vision