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Dataset associated with "All-electronic phase-resolved THz microscopy using the self-mixing effect in a semiconductor laser"

Rubino, Pierluigi and Keeley, James and Sulollari, Nikollao and Burnett, Andrew D and Valavanis, Alex and Kundu, Imon and Rosamond, Mark C. and Li, Lianhe and Linfield, Edmund H. and Davies, A. Giles and Cunningham, John E. and Dean, Paul (2021) Dataset associated with "All-electronic phase-resolved THz microscopy using the self-mixing effect in a semiconductor laser". University of Leeds. [Dataset] https://doi.org/10.5518/977

Dataset description

This dataset relates to data presented in the work, "All-electronic phase-resolved THz microscopy using the self-mixing effect in a semiconductor laser". In this work we report all-electronic coherent scattering-type scanning near-field microscopy (s-SNOM) using a terahertz-frequency quantum cascade laser. By exploiting the coherent self-mixing effect in these lasers, in conjunction with electronic frequency tuning of the laser, we demonstrate spatial mapping of both the amplitude and phase of the scattered field with deeply sub-wavelength resolution. We apply our technique for coherent microscopy of a phonon-resonant crystal. The extracted amplitude and phase parameters reveal clear contrast when compared to both metallic and non-resonant dielectric materials, and show excellent agreement with those calculated using a finite-dipole model of the near-field interaction between the s-SNOM tip and the resonant sample in the Reststrahlen band.

Keywords: terahertz, scattering-type, Scanning Near-Field Microscopy, coherent imaging, quantum cascade lasers, self-mixing
Subjects: F000 - Physical sciences > F300 - Physics > F310 - Applied physics
F000 - Physical sciences > F300 - Physics > F360 - Optical physics > F361 - Laser physics
Divisions: Faculty of Engineering > School of Electronic and Electrical Engineering
Related resources:
LocationType
https://doi.org/10.1021/acsphotonics.0c01908Publication
License: Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited: 29 Apr 2021 14:48
URI: https://archive.researchdata.leeds.ac.uk/id/eprint/835

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