Trace detection of energetic materials is a method to screen personnel, packages and other items for concealed
explosives. It is likely, that a person who carries explosives will contaminate himself and the package with the
explosive.
We present first results on the development of a compact detector combining Pulsed Laser Fragmentation (PLF)
with fragments detection. A passively q-switched UV microchip laser photofragments surface contaminations.
The concentration ratio of the fragments NO and NO2 is a sufficient indicator for the presence of nitrogen-based
explosives. For TNT, the results suggest, that a surface density as small as a few ng/cm2 can be reliably detected.
After attacks with anthrax pathogens have been committed since 2001 all over the world the fast detection and
determination of biological samples has attracted interest. A very promising method for a rapid test is Laser Induced
Breakdown Spectroscopy (LIBS). LIBS is an optical method which uses time-resolved or time-integrated spectral
analysis of optical plasma emission after pulsed laser excitation. Even though LIBS is well established for the
determination of metals and other inorganic materials the analysis of microbiological organisms is difficult due to their
very similar stoichiometric composition. To analyze similar LIBS-spectra computer assisted chemometrics is a very
useful approach.
In this paper we report on first results of developing a compact and fully automated rapid test for the detection of
hazardous microbiological material. Experiments have been carried out with two setups: A bulky one which is composed
of standard laboratory components and a compact one consisting of miniaturized industrial components. Both setups
work at an excitation wavelength of λ=1064nm (Nd:YAG). Data analysis is done by Principal Component Analysis
(PCA) with an adjacent neural network for fully automated sample identification.
A fiber optical laser sensor is applied for online and in-situ concentration monitoring of volcano gases. This can help to better understand the mechanisms underlying volcanic activity and enable the establishment of novel warning systems.
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