Laser-Based Standoff Detection of Surface-Bound Explosive Chemicals

Citation

David L. Huestis, Gregory P. Smith, and Harald Oser “Laser-based standoff detection of surface-bound explosive chemicals”, Proc. SPIE 7679, Micro- and Nanotechnology Sensors, Systems, and Applications II, 76790G (5 May 2010); https://doi.org/10.1117/12.849769

Abstract

Avoiding or minimizing potential damage from improvised explosive devices (IEDs) such as suicide, roadside, or vehicle bombs requires that the explosive device be detected and neutralized outside its effective blast radius. Only a few seconds may be available to both identify the device as hazardous and implement a response. As discussed in a study by the National Research Council, current technology is still far from capable of meeting these objectives. Conventional nitrocarbon explosive chemicals have very low vapor pressures, and any vapors are easily dispersed in air. Many point detection approaches rely on collecting trace solid residues from dust particles or surfaces. Practical approaches for standoff detection are yet to be developed. For the past 5 years, SRI International has been working toward development of a novel scheme for standoff detection of explosive chemicals that uses infrared (IR) laser evaporation of surfacebound explosive followed by ultraviolet (UV) laser photofragmentation of the explosive chemical vapor, and then UV laser-induced fluorescence (LIF) of nitric oxide. This method offers the potential of long standoff range (up to 100 m or more), high sensitivity (vaporized solid), simplicity (no spectrometer or library of reference spectra), and selectivity (only nitrocompounds).

© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.


Read more from SRI

  • An arid, rural Nevada landscape

    Can AI help us find valuable minerals?

    SRI’s machine learning-based geospatial analytics platform, already adopted by the USGS, is poised to make waves in the mining industry.

  • Two students in a computer lab

    Building a lab-to-market pipeline for education

    The SRI-led LEARN Network demonstrates how we can get the best evidence-based educational programs to classrooms and students.

  • Code reflected in a man's eyeglasses

    LLM risks from A to Z

    A new paper from SRI and Brazil’s Instituto Eldorado delivers a comprehensive update on the security risks to large language models.