Cantatore Aldo F P, Menduni Giansergio, Zifarelli Andrea, Patimisco Pietro, Giglio Marilena, Gonzalez Miguel, Seren Huseyin R, Luo Pan, Spagnolo Vincenzo, Sampaolo Angelo
PolySense Lab, Dipartimento Interateneo di Fisica, University and Polytechnic of Bari, Via Amendola 173, Bari 70126, Italy.
PolySense Innovations srl, Via Amendola 173, Bari 70126, Italy.
Energy Fuels. 2024 Dec 19;39(1):638-646. doi: 10.1021/acs.energyfuels.4c03726. eCollection 2025 Jan 9.
A compact and portable gas sensor based on quartz-enhanced photoacoustic spectroscopy (QEPAS) for the detection of methane (C1), ethane (C2), and propane (C3) in natural gas (NG)-like mixtures is reported. An interband cascade laser (ICL) emitting at 3367 nm is employed to target absorption features of the three alkanes, and partial least-squares regression analysis is employed to filter out spectral interferences and matrix effects characterizing the examined gas mixtures. Spectra of methane, ethane, and propane mixtures diluted in nitrogen are employed to train and test the regression algorithm, achieving a prediction accuracy of ∼98%, ∼96%, and ∼93% on C1, C2, and C3, respectively. With respect to previously reported QEPAS sensors for natural gas analysis, the high prediction accuracy as well as the capability to discriminate and detect C3 within natural gas-like complex mixtures provided by the employment of partial least-squares regression mark significant improvements. Furthermore, these results enable an improved performance of the sensor for in situ, real-time, and online natural gas composition analysis.
报道了一种基于石英增强光声光谱（QEPAS）的紧凑便携式气体传感器，用于检测类天然气（NG）混合物中的甲烷（C1）、乙烷（C2）和丙烷（C3）。采用发射波长为3367 nm的带间级联激光器（ICL）来针对这三种烷烃的吸收特征，并且采用偏最小二乘回归分析来滤除表征所检测气体混合物的光谱干扰和基体效应。用氮气稀释的甲烷、乙烷和丙烷混合物的光谱来训练和测试回归算法，在C1、C2和C3上分别实现了约98%、约96%和约93%的预测准确度。相对于先前报道的用于天然气分析的QEPAS传感器，偏最小二乘回归的应用所提供的高预测准确度以及在类天然气复杂混合物中辨别和检测C3的能力标志着显著的改进。此外，这些结果使得该传感器在原位、实时和在线天然气成分分析方面的性能得到改善。
