He, YingMa, YufeiTong, YaoYu, XinTittel, Frank K.2018-08-172018-08-172018He, Ying, Ma, Yufei, Tong, Yao, et al.. "HCN ppt-level detection based on a QEPAS sensor with amplified laser and a miniaturized 3D-printed photoacoustic detection channel." <i>Optics Express,</i> 26, no. 8 (2018) Optical Society of America: 9666-9675. https://doi.org/10.1364/OE.26.009666.https://hdl.handle.net/1911/102467Ultra-high sensitive and stable detection of hydrogen cyanide (HCN) based on a quartz-enhanced photoacoustic spectroscopy (QEPAS) sensor was realized using an erbium-doped fiber amplifier (EDFA) as well as a miniaturized 3D-printed photoacoustic detection channel (PADC) for the first time. A HCN molecule absorption line located at 6536.46 cm-1 was selected which was in the range of the EDFA emission spectrum. The detection sensitivity of the reported EDFA-QEPAS sensor was enhanced significantly due to the high available EDFA excitation laser power. A 3D printing technique was used to develop the compact PADC, resulting in a size of 29 × 15 × 8 mm3 and a mass of ~5 g in order to improve the sensor stability and implement sensor applications requiring a compact size and light weight. At atmospheric pressure, room temperature and a 1 s acquisition time, a minimum detection limit (MDL) of 29 parts per billion (ppb) was achieved, corresponding to a normalized noise equivalent absorption (NNEA) coefficient of 1.08 × 10-8 cm-1W/Hz-1/2. The long-term performance and the stability of the HCN EDFA-QEPAS sensor system were investigated using an Allan deviation analysis. It indicated that the MDL can be improved to 220 parts per trillion (ppt) with an integration time of 300 s, which demonstrated this compact, integrated and miniaturized 3D-printed PADC based sensor had an excellent stability.engAn OSA-formatted open access journal article PDF may be governed by the OSA Open Access Publishing Agreement signed by the author and any applicable copyright laws. Authors and readers may use, reuse, and build upon the article, or use it for text or data mining without asking prior permission from the publisher or the Author(s), as long as the purpose is non-commercial and appropriate attribution is maintained.Journal articleoe-26-8-9666https://doi.org/10.1364/OE.26.009666