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Title: Near-field imaging using self mixing in terahertz frequency quantum cascade lasers
Author: Rubino, Pierluigi
ISNI:       0000 0004 8501 0696
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2019
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Self-mixing (SM) effect in terahertz (THz) quantum cascade lasers (QCLs) can be good a candidate to replace the standard detection systems, offering a compact and coherent detection. SM effect occurs when part of the radiation emitted from a laser and reflected from a target is re-injected into the laser cavity. The re-injected field interferes with the intra-cavity field creating perturbations that can be measured by recording the laser terminal voltage. Amplitude and phase of the re-injected field can be recorded. In this work, SM detection in THz QCLs was used to acquire images of radically different samples; a human skin sample, a skin sample containing melanoma and silicon wafers. A noise equivalent power (NEP) of 1.4pW \sqrt{Hz} is demonstrated, making SM techniques suitable for applications that requires detection of weak fields such as near-field (NF) systems. NF imaging allows the investigation of micro- and nano-scale structures below the diffraction limit. In this work SM detection in a THz QCL was combined with a scattering-type near-field optical microscope (s-SNOM) to achieve a sub-wavelength resolution < 100 nm. By exploiting the current-controlled frequency tuning of the THz QCL and the intrinsically coherent nature of the SM scheme, a stepped-frequency approach was developed to obtain interferometric data at each pixel of the image using an all-electrical approach. The possibility to retrieve complex permittivity information of materials is demonstrated by using two samples, Au/SiO_{2} (gold on silicon dioxide) and Au/KBr (gold on potassium bromide). The final part of this work is dedicated to the study and NF imaging of graphene with a particular focus on the possibility of imaging propagating plasmons using THz radiation. This thesis presents the relevant theory and describes the modelling of surface plasmons in graphene taking into account two possible substrates, SiO_{2} and hexagonal boron nitride, h-BN.
Supervisor: Dean, Paul ; Cunningham, John Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available