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Chemometrics-enhanced fiber optic Raman detection, discrimination and quantification of chemical agents simulants concealed in commercial bottles

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Chemometric techniques such as partial least squares combined with discriminant analysis (PLS–DA) and
artificial neural networks (ANN) analysis were used to enhance the detection, discrimination and quantification
of chemical warfare agents simulants. Triethyl phosphate (TEP) mixed with commercial products
in their original containers was analyzed through the container walls using fiber-optic-coupled
Raman spectroscopy. Experiments were performed by employing a custom built optical fiber probe operating
at 488 nm. Detection was accomplished using mixtures of the contents of the commercial bottles
and water. The bottle materials included green plastic, green glass, clear plastic, clear glass, amber glass
and white plastic. To account for the low scattering-peak intensities of some bottle materials, integration
times were increased. Short integration times provided no information for amber glass and white plastic.
The limits of detection were on the order of 1–5%, depending on bottle materials and contents. Good discrimination was achieved with PLS–DA when models were generated from a dataset originating from the
same type of bottle material. ANN performed better when large sets of data were used, discriminating
TEP from bottle materials and contents, as well as accurately classifying over 90% of the data.

Keywords:
Partial least squares
Optical fiber coupled Raman probe
Chemical warfare agents simulants
Artificial neural networks

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Ketersediaan

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Informasi Detail

Judul Seri

Analytical Chemistry Research

No. Panggil

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Penerbit

New York : Elsevier B.V.., 2014

Deskripsi Fisik

Analytical Chemistry Research 2 (2014) 15–22

Bahasa

English

ISBN/ISSN

http://dx.doi.org/10

Klasifikasi

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Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

2 (2014)

Subjek

KIMIA ANALITIK

Info Detail Spesifik

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Pernyataan Tanggungjawab

agus

Versi lain/terkait

Lampiran Berkas

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