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Dataset for Gas spectroscopy with integrated frequency monitoring through self-mixing in a terahertz quantum-cascade laser.

Citation

Chhantyal-Pun, Rabi and Valavanis, Alexander and Keeley, James and Rubino, Pierluigi and Kundu, Iman and Han, Yingjun and Dean, Paul and Li, Lianhe and Davies, A. Giles and Linfield, Edmund (2017) Dataset for Gas spectroscopy with integrated frequency monitoring through self-mixing in a terahertz quantum-cascade laser. University of Leeds. [Dataset] https://doi.org/10.5518/204

Dataset description

This archive contains the dataset associated with the publication entitled 'Gas spectroscopy with integrated frequency-monitoring through self-mixing in a terahertz quantum-cascade laser'.  In this work, we demonstrate a gas spectroscopy technique based on self-mixing interferometry in a 3.4-THz quantum-cascade laser (QCL). All previous QCL spectroscopy techniques have required additional THz instrumentation (detectors, mixers or spectrometers) for system-precalibration or in situ spectral analysis. By contrast, our system self-calibrates the laser frequency to a precision of 630 MHz (0.02%) by analyzing voltage perturbations across the QCL, in response to optical feedback from a mirror mounted on a 0-800-mm round-trip delayline. We demonstrate spectroscopy of methanol by introducing a gas cell into the feedback path, and show that a limiting absorption coefficient of ~0.0001 /cm is resolvable. This dataset includes the raw data used to generate all figures within the publication.

Keywords: infrared spectra, quantum cascade lasers, submillimeter wave technology, spectroscopy
Subjects: F000 - Physical sciences > F300 - Physics > F360 - Optical physics > F361 - Laser physics
F000 - Physical sciences > F100 - Chemistry > F180 - Analytical chemistry
Divisions: Faculty of Engineering and Physical Sciences > School of Electronic and Electrical Engineering > Institute of Microwaves and Photonics
Related resources:
LocationType
https://doi.org/10.1364/OL.43.002225Publication
https://eprints.whiterose.ac.uk/112720/Publication
License: Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited: 17 Aug 2017 10:47
URI: https://archive.researchdata.leeds.ac.uk/id/eprint/238

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