High Explosives Mixtures Detection Using Fiber Optics Coupled: Grazing Angle Probe/Fourier Transform Reflection Absorption Infrared Spectroscopy

  • Oliva M. Primera-Pedrozo
  • Yadira M. Soto-Feliciano
  • Leonardo C. Pacheco-Londoño
  • Samuel P. Hernández-RiveraEmail author
Original Paper


Fourier Transform Infrared Spectroscopy operating in Reflection–Absorption mode has been demonstrated as a potential spectroscopic technique to develop new methodologies for detection of chemicals deposited on metallic surfaces. Mid-IR transmitting optical fiber bundle coupled to an external Grazing Angle Probe and an MCT detector together with a bench Michelson interferometer have been used to develop a highly sensitive and selective methodology for detecting traces of organic compounds on metal surfaces. The methodology is remote sensed, in situ and can detect surface loading concentrations of nanograms/cm2 of most target compounds. It is an environmentally friendly, solvent free technique that does not require sample preparation. In this work, the ever-important task of high explosives detection, present as traces of neat crystalline forms and in lab-made mixtures, equivalent to the important explosive formulation Pentolite, has been addressed. The sample set consisted of TNT, PETN (both pure samples) and the formulation based on them: Pentolite, present in various loading concentrations. The spectral data collected was subjected to a number of statistical pre-treatments, including first derivative and normalization transformations to make the data more suitable for the analysis. Principal Components Analysis combined with Linear Discriminant Analysis allowed the classification and discrimination of the target analytes contained in the sample set. Loading concentrations as 220 ng/cm2 were detected for each explosive in neat form and the in the simulated mixture of Pentolite.


Grazing angle probe RAIRS TNT PETN Pentolite 



This work was supported by the U.S. Department of Defense, University Research Initiative Multidisciplinary University Research Initiative (URI)-MURI Program, under grant number DAAD19-02-1-0257. The authors also acknowledge contributions from Scott Grossman and Aaron LaPointe of Night Vision and Electronic Sensors Directorate, Department of Defense.


  1. 1.
    Steinfeld, J. I., & Wormhoudt, J. (1998). Explosives detection: A challenge for physical chemistry. Annual Review of Physical Chemistry, 49, 203–232. doi: 10.1146/annurev.physchem.49.1.203.CrossRefGoogle Scholar
  2. 2.
    Pristera, F., Halik, M., Castelli, A., & Fredericks, W. (1960). Analysis of explosives using infrared spectroscopy. Analytical Chemistry, 32, 495–508. doi: 10.1021/ac60160a013.CrossRefGoogle Scholar
  3. 3.
    Mizaikoff, B. (2002). Sensory systems based on mid-infrared transparent fibers. In J. M. Chalmers & P. R. Griffiths (Eds.), Handbook of vibrational spectroscopy (Vol. 2, pp. 1560–1573). Chichester, UK: Wiley & Sons.Google Scholar
  4. 4.
    Griffiths, P. R., & De Haseth, J. A. (1986). Fourier-transform infrared spectrometry (p. 194). New York, NY: Wiley and Sons.Google Scholar
  5. 5.
    Umemura, J. (2002). Reflection–absorption spectroscopy of thin films on metallic substrates. In J. M. Chalmers & P. R. Griffiths (Eds.), Handbook of vibrational spectroscopy (Vol. 2, pp. 982–998). Chichester, UK: Wiley & Sons.Google Scholar
  6. 6.
    Melling, P. J., & Shelley, P. (2001). Spectroscopic accessory for examining films and coatings on solid surfaces, US Patent 6,3,10,348.Google Scholar
  7. 7.
    Mehta, N. K., Goenaga, J. E., Hernández, S. P., Thomson, M. A., & Melling, P. J. (2002). Development of an in-situ spectroscopic method for cleaning validation using mid-IR fiber optics. BioPharm, 15, 36–42. idem, 2003, Spectroscopy.Google Scholar
  8. 8.
    Hamilton, M. L., Perston, B. B., Harland, P. W., Williamson, B. E., Thomson, M. A., & Melling, P. J. (2005). Grazing-angle fiber-optic irras for in situ cleaning validation. Organic Process Research & Development, 9, 337–343. doi: 10.1021/op040213z.CrossRefGoogle Scholar
  9. 9.
    Perston, B. B., Hamilton, M. L., Williamson, B. E., Harland, P. W., Thomson, M. A., & Melling, P. J. (2007). Grazing-angle fiber-optic fourier transform infrared reflection–absorption spectroscopy for the in situ detection and quantification of two active pharmaceutical ingredients on glass. Analytical Chemistry, 79, 1231–1236. doi: 10.1021/ac061660a.CrossRefGoogle Scholar
  10. 10.
    Primera-Pedrozo, O. M., Pacheco Londoño, L. C., De la Torre-Quintana, L. F., Hernandez-Rivera, S. P., Chamberlain, R. T., & Lareau, R. T. (2004). Use of fiber optic coupled FT-IR in detection of explosives on surfaces: Sensors, and command, control, communications, and intelligence (C3I) technologies for homeland security and homeland defense III. In M. Edward Carapezza (Ed.), Proceedings of SPIE (vol. 5403, pp. 237–245).Google Scholar
  11. 11.
    Primera-Pedrozo, O. M., Pacheco-Londoño, L. C., Ruiz, O., Ramirez, M. L., Soto-Feliciano, Y. M., De la Torre Quintana, L. F., et al. (2005). Characterization of thermal inkjet technology TNT deposits by fiber optic-grazing angle probe FTIR spectroscopy: Sensors, and command, control, communications, and intelligence (C3I) technologies for homeland security and homeland defense IV. In Edward M. Carapezza (Ed.), Proceedings of SPIE (vol. 5778, pp. 543–552).Google Scholar
  12. 12.
    Gibbs, T. R., & Popolato, A. (Eds.). (1980). LASL explosive property data. Berkeley, CA: University of California Press.Google Scholar
  13. 13.
    Barreto-Cabán, M. A., Pacheco-Londoño, L., Ramírez, M. L., & Hernández-Rivera, S. P. (2006). Novel method for the preparation of explosive nanoparticles, sensors, and command, control, communications, and intelligence (C3I) technologies for homeland security and homeland defense V. In Edward M. Carapezza (Ed.), Proceedings of the Society for Photo-Instrumentation Engineers (vol. 6201, pp. 644–654). Bellingham, WA: SPIE.Google Scholar
  14. 14.
    Urbanski, T. (1964). Chemistry and technology of explosives. New York, NY: Macmillan Company. v. 1.Google Scholar
  15. 15.
    Stone, M., & Jonathan, P. (1993). Statistical thinking and technique for QSAR and related studies: General theory. Journal of Chemometrics, 7, 455–475. doi: 10.1002/cem.1180070603.CrossRefGoogle Scholar
  16. 16.
    Johnson, R. A., & Wichern, D. W. (1992). Applied multivariate statistical analysis. Englewood Cliffs: N.J.: Prentice-Hall.zbMATHGoogle Scholar
  17. 17.
    Mardia, K. V., Kent, J. T., & Bibbly, J. M. (1979). Multivariate analysis. New York: Academic Press.zbMATHGoogle Scholar
  18. 18.
    Huberty, C. J. (1994). Applied discriminant analysis. New Jersey: Wiley Interscience.zbMATHGoogle Scholar
  19. 19.
    Schrader, B. (1995). Infrared and Raman spectroscopy: Methods and applications. In B. Schrader (Ed.), (p. 215). New York, NY: VCH.Google Scholar
  20. 20.
    Lin-Vien, D., Colthup, N. B., Fateley, W. G., & Grasselli, J. G. (1991). The handbook of infrared and raman characteristic frequencies of organic molecules (pp. 179–189). San Diego, CA: Academic Press.Google Scholar
  21. 21.
    Olivero-Verbel, J., Vivas-Reyes, R., Pacheco-Londoño, L. C., Johnson-Restrepo, B., & Kannan, K. (2004). Discriminant analysis for activation of the aryl hydrocarbon receptor by polychlorinated naphthalenes. Journal of Molecular Structure: THEOCHEM, 678, 157–161. doi: 10.1016/j.theochem.2004.01.048.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Oliva M. Primera-Pedrozo
    • 1
  • Yadira M. Soto-Feliciano
    • 1
  • Leonardo C. Pacheco-Londoño
    • 1
  • Samuel P. Hernández-Rivera
    • 1
    Email author
  1. 1.Center for Chemical Sensors Development/Chemical Imaging Center, Department of ChemistryUniversity of Puerto Rico, MayagüezSan JuanUSA

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