Literature DB >> 20223064

Fourier transform infrared photoacoustic multicomponent gas spectroscopy with optical cantilever detection.

Christian Bernd Hirschmann1, Juho Uotila, Satu Ojala, Jussi Tenhunen, Riitta Liisa Keiski.   

Abstract

The sensitivity of photoacoustic spectroscopy was improved with the invention of optical cantilever detection (PAS-OCD). However, the ability of present PAS-OCD devices to carry out multicomponent detection is poor. To overcome this, a Fourier transform infrared photoacoustic spectrometer with optical cantilever detection (FT-IR-PAS-OCD) prototype was assembled. In this article, the first evaluation and performance tests of the prototype are described. Selectivity, sensitivity, and the linearity of the signal response are evaluated. The linear response was studied for methane and carbon dioxide and confirmed in the whole analyzed concentration range from 500 to 3500 ppm and from 2500 to 17500 ppm, respectively. The calculated signal-to-noise ratio (SNR) and limit of detection were 2027 and 0.5 ppm for methane and 1362 and 4 ppm for carbon dioxide, with a measurement time of 100 seconds. Selectivity was studied with a multicomponent gas mixture of propene, methane, carbon dioxide, and methylmercaptane. The results indicate that a quantitative analysis of all components in the mixture is possible using the FT-IR-PAS-OCD.

Entities:  

Year:  2010        PMID: 20223064     DOI: 10.1366/000370210790918490

Source DB:  PubMed          Journal:  Appl Spectrosc        ISSN: 0003-7028            Impact factor:   2.388


  2 in total

1.  FT-IR-cPAS--new photoacoustic measurement technique for analysis of hot gases: a case study on VOCs.

Authors:  Christian Bernd Hirschmann; Niina Susanna Koivikko; Jussi Raittila; Jussi Tenhunen; Satu Ojala; Katariina Rahkamaa-Tolonen; Ralf Marbach; Sarah Hirschmann; Riitta Liisa Keiski
Journal:  Sensors (Basel)       Date:  2011-05-16       Impact factor: 3.576

2.  Highly sensitive broadband differential infrared photoacoustic spectroscopy with wavelet denoising algorithm for trace gas detection.

Authors:  Lixian Liu; Huiting Huan; Wei Li; Andreas Mandelis; Yafei Wang; Le Zhang; Xueshi Zhang; Xukun Yin; Yuxiang Wu; Xiaopeng Shao
Journal:  Photoacoustics       Date:  2020-12-05
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.