Van der Waals Heterostructures and 2D Materials with Native Oxide for Emerging Electronic Applications
type: CreativeWork
description: The rapid advancement of Artificial Intelligence (AI) and Machine Learning (ML) in various industries has created a significant energy demand. However, this demand poses a challenge as the world strives to shift towards sustainable energy sources. The current computational paradigms, reliant on complementary metal-oxide-semiconductor (CMOS) transistors, are becoming more inadequate for meeting these emerging demands due to limitations imposed by materials characteristics and device architecture. To address this computational paradigm shift, an innovative material platform is necessary. Two-dimensional (2D) layered materials and their heterostructures offer a promising solution to meet this demand, owing to their unique properties. In addition, oxidation processes of 2D materials, which are termed "morphotaxy", allow for precise control over the material thickness and the fabrication of complex heterostructures, opening the door for advanced computing architectures such as non-von Neumann neuromorphic computing. This thesis explores the critical role of interfaces in the performance and efficiency of devices based on 2D materials van der Waals (vdW) and semiconductor/native oxide heterostructures. The susceptibility of these materials to contamination is highlighted, especially in vdW heterostructures. Elemental analysis of chemical species present at the interfaces of hBN-encapsulated graphene is conducted to determine the origin of contaminants. The findings highlighted the difference between contaminants originating from the heterostructure stacking process and the ones from the device lithography process. Moreover, the impact of such interfaces on carrier transport across two 2D materials and the realisation of phenomena like moiré superlattices in vdW heterostructures based on twisted WSe2/MoS2 hetero-bilayer is discussed. The results showed that inhomogeneity across the heterostructure interface brought by strain and contamination has an impact on the formation…
abstract: The rapid advancement of Artificial Intelligence (AI) and Machine Learning (ML) in various industries has created a significant energy demand. However, this demand poses a challenge as the world strives to shift towards sustainable energy sources. The current computational paradigms, reliant on complementary metal-oxide-semiconductor (CMOS) transistors, are becoming more inadequate for meeting these emerging demands due to limitations imposed by materials characteristics and device architecture. To address this computational paradigm shift, an innovative material platform is necessary. Two-dimensional (2D) layered materials and their heterostructures offer a promising solution to meet this demand, owing to their unique properties. In addition, oxidation processes of 2D materials, which are termed "morphotaxy", allow for precise control over the material thickness and the fabrication of complex heterostructures, opening the door for advanced computing architectures such as non-von Neumann neuromorphic computing. This thesis explores the critical role of interfaces in the performance and efficiency of devices based on 2D materials van der Waals (vdW) and semiconductor/native oxide heterostructures. The susceptibility of these materials to contamination is highlighted, especially in vdW heterostructures. Elemental analysis of chemical species present at the interfaces of hBN-encapsulated graphene is conducted to determine the origin of contaminants. The findings highlighted the difference between contaminants originating from the heterostructure stacking process and the ones from the device lithography process. Moreover, the impact of such interfaces on carrier transport across two 2D materials and the realisation of phenomena like moiré superlattices in vdW heterostructures based on twisted WSe2/MoS2 hetero-bilayer is discussed. The results showed that inhomogeneity across the heterostructure interface brought by strain and contamination has an impact on the formation…
author: Almutairi, Abdulaziz
language: eng
keywords: 2D materials, Graphene, Memristors, Morphotaxy, Neuromorphic Computing, TMDs, Van der Waals Heterostructures
license: https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/dbe73c84-8221-4b0a-b307-773586d0af78/download
license: https://www.rioxx.net/licenses/all-rights-reserved/
date published: 2023-12-30
date modified: 2026-07-22T22:24:24Z
provider: Cambridge University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Cambridge

PropertyValue
property ID: DOI
value: 10.17863/CAM.108311