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Improving the performance of hollow waveguide-based infrared gas sensors via tailored chemometrics

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Abstract

The use of chemometrics in order to improve the molecular selectivity of infrared (IR) spectra has been evaluated using classic least squares (CLS), partial least squares (PLS), science-based calibration (SBC), and multivariate curve resolution-alternate least squares (MCR-ALS) techniques for improving the discriminatory and quantitative performance of infrared hollow waveguide gas sensors. Spectra of mixtures of isobutylene, methane, carbon dioxide, butane, and cyclopropane were recorded, analyzed, and validated for optimizing the prediction of associated concentrations. PLS, CLS, and SBC provided equivalent results in the absence of interferences. After addition of the spectral characteristics of water by humidifying the sample mixtures, CLS and SBC results were similar to those obtained by PLS only if the water spectrum was included in the calibration model. In the presence of an unknown interferant, CLS revealed errors up to six times higher than those obtained by PLS. However, SBC provided similar results compared to PLS by adding a measured noise matrix to the model. Using MCR-ALS provided an excellent estimation of the spectra of the unknown interference. Furthermore, this method also provided a qualitative and quantitative estimation of the components of an unknown set of samples. In summary, using the most suitable chemometrics approach could improve the selectivity and quality of the calibration model derived for a sensor system, and may avoid the need to analyze expensive calibration data sets. The results obtained in the present study demonstrated that (1) if all sample components of the system are known, CLS provides a sufficiently accurate solution; (2) the selection between PLS and SBC methods depends on whether it is easier to measure a calibration data set or a noise matrix; and (3) MCR-ALS appears to be the most suitable method for detecting interferences within a sample. However, the latter approach requires the most extensive calculations and may thus result in limited temporal resolution, if the concentration of a component should be continuously monitored.

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Acknowledgments

DPG acknowledges financial support by the grant “Segles V” provided by the University of Valencia, the Ministerio de Educación y Ciencia (CTQ2011-25743) and the Generalitat Valenciana (PROMETEO 2010–055), enabling a research stay at the Institute of Analytical and Bioanalytical Chemistry, Univ. Ulm. JK acknowledges her grant (Sara Borrell CD12/00667) from the Instituto Carlos III (Ministry of Economy and Competitiveness). This work was performed in part under the auspices of the US Department of Energy by the University of California, Lawrence Livermore National Laboratory (LLNL) under contract no. W-7405-Eng-48. This project was funded in part by the Laboratory Directed Research and Development Program at LLNL under subcontract nos. B565491, B594450, B590992, B598643, and B603018.

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Authors and Affiliations

  1. Analytical Chemistry Department, University of Valencia, Edificio Jeroni Muñoz, 46100, Burjassot, Valencia, Spain

    David Perez-Guaita & Miguel de la Guardia

  2. Institute of Analytical and Bioanalytical Chemistry, University of Ulm, 89081, Ulm, Germany

    Andreas Wilk & Boris Mizaikoff

  3. Division of Neonatology, University Hospital Materno-Infantil La Fe, Bulevar Sur, s/n, 46026, Valencia, Spain

    Julia Kuligowski

  4. Leitat Technological Center, Bio In Vitro Division, Health Research Institute La Fe, 46026, Valencia, Spain

    Guillermo Quintás

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  1. David Perez-Guaita
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  2. Andreas Wilk
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  3. Julia Kuligowski
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  4. Guillermo Quintás
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  5. Miguel de la Guardia
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  6. Boris Mizaikoff
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Correspondence to Boris Mizaikoff.

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Perez-Guaita, D., Wilk, A., Kuligowski, J. et al. Improving the performance of hollow waveguide-based infrared gas sensors via tailored chemometrics. Anal Bioanal Chem 405, 8223–8232 (2013). https://doi.org/10.1007/s00216-013-7230-5

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  • DOI: https://doi.org/10.1007/s00216-013-7230-5

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