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High-throughput characterisation and device integration of nanomaterials


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Abstract

This thesis introduces high-throughput methods for the characterisation and fabrication of nanomaterial devices using InAs nanowires, bilayer graphene, MoS2, and MoSe2/WSe2 lateral heterostructures. First, a novel method for nanofabrication is introduced using a lithography-optimised fiducial marker system LithoTag, which is used for the identification of individual InAs nanowires and for automatically designing >200 devices with high alignment accuracy. The presented method provides the foundation for subsequent research presented in this thesis. The focus then moves to other nanomaterial characterisation methods and investigates spectroscopic ellipsometric contrast microscopy (SECM) for mapping twist angle disorder in optically resonant twisted bilayer graphene. Ellipsometric angles were optimised to enhance the image contrast based on measured and calculated reflection coefficients of incident light, allowing the mapping of individual twisted bilayer domains to <1° accuracy. The high-throughput methodology is then applied to ALD encapsulation. Hundreds of MoS2 field-effect transistors (FETs) were encapsulated with different Al2O3 recipes to evaluate their electrical performance. MoS2 FETs encapsulated with O3 pre-treated Al2O3 exhibit the highest mobility and lowest hysteresis. It was also found that in-situ oxidising pre-treatments counteract the n-doping of conventional alumina ALD processes. The last chapter applies the results of previous chapters to MoSe2/WSe2 heterostructures. SECM was used to optimise the contrast between MoSe2 and WSe2 and used to identify >1000 heterostructure domains. This was followed by the automatic fabrication of 48 p-n junction devices aligned to the MoSe2/WSe2 interface using the LithoTag system and encapsulation with in-situ O3 pre-treated Al2O3. The results illustrate the advantages of combined high-throughput methodology for characterisation and device integration of nanomaterials.

Description

Date

2024-02-23

Advisors

Alexander-Webber, Jack

Qualification

Doctor of Philosophy (PhD)

Awarding Institution

University of Cambridge

Rights and licensing

Except where otherwised noted, this item's license is described as All Rights Reserved
Sponsorship
EPSRC (2436333)