Self-mixing detection of methane and carbon dioxide using mid-infrared quantum cascade lasers

at the 4319.78 nm absorption line, which are comparable to detector-based schemes. Additionally, a separate validation experiment demonstrated measurement accuracy of at least 90%.

Authors

Institutions

Publication Details

Journal
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy
Published
2026-04-01
DOI
https://doi.org/10.1016/j.saa.2026.127838
Primary Topic
Spectroscopy and Laser Applications
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Self-mixing detection of methane and carbon dioxide using mid-infrared quantum cascade lasers

Θωμάς Νίκας, Μαριαλένα Ακριώτου, Dimitris Syvridis, Nikos Stefanakos et al.
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy
Spectroscopy and Laser Applications
article

Self-mixing detection of methane and carbon dioxide using mid-infrared quantum cascade lasers

Θωμάς Νίκας, Μαριαλένα Ακριώτου, Dimitris Syvridis, Nikos Stefanakos, Boris Mizaikoff, Gabriela Flores Rangel
article en

Abstract

at the 4319.78 nm absorption line, which are comparable to detector-based schemes. Additionally, a separate validation experiment demonstrated measurement accuracy of at least 90%.

Spectrochimica Acta Part A Molecular and Biomolecular SpectroscopyVol. 358
Universität Ulm (DE), National and Kapodistrian University of Athens (GR), Applied Technologies (United States) (US)
HORIZON EUROPE Framework Programme
Openalex Percentile: Top 38%
Spectroscopy and Laser Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.