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Identification of Unknown Substances by Terahertz Spectroscopy and Multivariate Data Analysis

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Abstract

The identification of various substances by multivariate data analysis of terahertz transmittance spectra is demonstrated. Transmittance spectra were obtained by the use of a Fourier transform infrared spectrometer. By means of principal component analysis and partial least squares regression, the spectral data were analyzed in order to identify substances and mixtures of several substances. With only three principal components, detection and identification of substances are possible with high accuracy. Using these methods, concentration ratios of substances in mixtures of two substances can be determined with an accuracy of 10 %. It is shown that the method is robust against disturbances in the spectra such as standing waves. This is particularly important for practical applications.

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Acknowledgments

This work was founded by the German Federal Ministry of Education and Research (Grant No. 13 N12022). A. Pohl, N. Deßmann, and K. Dutzi acknowledge support by the Helmholtz Research School on Security Technologies.

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Authors and Affiliations

  1. Department of Physics, Humboldt University zu Berlin, Newtonstr. 15, 12489, Berlin, Germany

    Andreas Pohl, Nils Deßmann & Heinz-Wilhelm Hübers

  2. Institute of Optical Sensor Systems, German Aerospace Center (DLR), Rutherfordstraße 2, 12489, Berlin, Germany

    Andreas Pohl, Nils Deßmann, Katja Dutzi & Heinz-Wilhelm Hübers

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  1. Andreas Pohl
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  2. Nils Deßmann
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Correspondence to Andreas Pohl.

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Pohl, A., Deßmann, N., Dutzi, K. et al. Identification of Unknown Substances by Terahertz Spectroscopy and Multivariate Data Analysis. J Infrared Milli Terahz Waves 37, 175–188 (2016). https://doi.org/10.1007/s10762-015-0217-x

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  • DOI: https://doi.org/10.1007/s10762-015-0217-x

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