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

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 H (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.

Additional information: The paper associated with this dataset is in review. The dataset may change as a result of the review.
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 > School of Electronic and Electrical Engineering > Institute of Microwaves and Photonics
Related resources:
LocationType
https://doi.org/10.1364/OL.43.002225Publication
http://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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