UV RESONANCE RAMAN INVESTIGATION OF EXPLOSIVES’ UV PHOTOCHEMISTRY

Detection of explosives has become an important field of research due to the increased number of terrorist attacks utilizing improvised explosive devices (IEDs). We show that UV resonance Raman (UVRR) spectroscopy is a sensitive and incisive technique for detection of explosives. Deep UV excitation of explosives gives resonance enhancement and greater sensitivity enabling trace detection of explosives and their photochemical products. We demonstrate how we can utilize UVRR to analyze characteristic spectral changes that result from explosives’ photochemistry. In this work, we examined the 229 nm photochemistry of some of the main military explosives, TNT, RDX, and PETN in solution and solid state. We monitored the decrease in intensity of the UVRR bands of the initial explosive and the increase in intensity of the UVRR photoproduct bands during photolysis. Detection of photochemical product UVRR bands can be used to detect the previous presence of explosives even after they have been photolyzed. We determined solution state quantum yields, which gives insight to the susceptibility of the explosive to photolysis upon irradiation. We also determined the initial photoproducts formed by photolysis by using high performance liquid chromatography-high resolution mass spectrometry (HPLC-HRMS) measurements

Glance duration for the (a) first three glances, (b) first 24 glances, and (c) last three glances from the navigation entry tasks; error bars represent 1 standard error of the mean.

<p>Glance duration for the (a) first three glances, (b) first 24 glances, and (c) last three glances from the navigation entry tasks; error bars represent 1 standard error of the mean.</p

Cumulative probability distribution of glance duration for the first three glances of the navigation entry tasks.

<p>Cumulative probability distribution of glance duration for the first three glances of the navigation entry tasks.</p

Cumulative probability distribution of glance duration for the first six glances from data set A (on the left) and data set B (on the right) for the radio tuning tasks.

<p>Cumulative probability distribution of glance duration for the first six glances from data set A (on the left) and data set B (on the right) for the radio tuning tasks.</p

Cumulative probability distribution of glance duration for the last three glances of the navigation entry tasks.

<p>Cumulative probability distribution of glance duration for the last three glances of the navigation entry tasks.</p

Glance frequency distribution for the navigation entry tasks across both data sets; the dashed line shows mean number of glances and the dotted line represent 2 standard deviations.

<p>Glance frequency distribution for the navigation entry tasks across both data sets; the dashed line shows mean number of glances and the dotted line represent 2 standard deviations.</p

Cumulative probability distribution of glance duration for the first six glances of the radio tuning tasks.

<p>Cumulative probability distribution of glance duration for the first six glances of the radio tuning tasks.</p

Order in which participants had to press the buttons for completion of the radio tuning task for: (A) data set A; (B) data set B.

<p>Order in which participants had to press the buttons for completion of the radio tuning task for: (A) data set A; (B) data set B.</p

Cumulative probability distribution of glance duration for the last six glances from the radio tuning tasks.

<p>Cumulative probability distribution of glance duration for the last six glances from the radio tuning tasks.</p

Results of the KS test for the first six glances of data set B for the radio tuning tasks; each cell entry shows <i>D</i> statistics of the KS test for the two glances indicated by the row and column indices.

<p>Results of the KS test for the first six glances of data set B for the radio tuning tasks; each cell entry shows <i>D</i> statistics of the KS test for the two glances indicated by the row and column indices.</p