PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
Here we report on the application of multivariate analysis on optical sensors for gas detection based on Quartz-Enhanced Photoacoustic Spectroscopy (QEPAS) technique, focused on the analysis of complex gas mixtures. In real-world applications the effects of spectral and non-spectral interference occurring within the gas samples cannot be neglected in order to increase sensors selectivity and accuracy. In this work, Partial Least Squares Regression (PLSR) is selected as regression technique and tested on different gas samples for different applications. PLSR is able to retrieve analytes concentrations filtering out both: i) spectral contributions of analytes characterized by strongly overlapping features; ii) correlation effects due to the interaction among the sample’s components, i.e., matrix effects characterizing the photoacoustic detection.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
The alert did not successfully save. Please try again later.
Andrea Zifarelli, Giansergio Menduni, Aldo Francesco Pio Cantatore, Pietro Patimisco, Christine Holzl, Vincenzo Spagnolo, "Multivariate spectral analysis in quartz-enhanced photoacoustic spectroscopy," Proc. SPIE 12430, Quantum Sensing and Nano Electronics and Photonics XIX, 124300W (15 March 2023); https://doi.org/10.1117/12.2650131