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NE Scientists Chien, Sheen, Raptis and Wang win R&D 100 Award

Group Photo of the award winners

Group photo of the award winners. Clockwise from top: Hual-Te Chien, Paul Raptis, Shuh-Haw Sheen, and Kevin Wang.

Aug. 26, 2011
Researchers from Argonne National Laboratory's Nuclear Engineering Division received an R&D 100 award for the Photoacoustic Spectroscopy (PAS) System for Remote Detection of Explosives and Chemicals. Hual-Te Chien, Shuh-Haw Sheen, Apostolos Raptis and Ke (Kevin) Wang, developed Argonne's portable PAS remote and extended-range detection system which can be used for homeland security and defense applications to identify and locate toxic chemicals, roadside bombs, or special nuclear materials with high sensitivity and great selectivity for chemicals and explosives in an open-field environment. The Argonne PAS System can also be used for environmental monitoring, crime scene forensics and cargo and food inspections.

Photoacoustic Spectroscopy (PAS) System for Remote Detection of Explosives and
      Chemicals

Scientists Hual-Te Chien and Kevin Wang pictured while operating the PAS System.

The PAS System uses a special acoustic resonator that is designed to detect an acoustic signal generated by the photoacoustic effect in an open-field. When the detector's laser is aimed at a gas plume or solid materials from a distance, it excites the selected molecules, which transfers their internal energy to translational energy through collisions with ambient gas/air molecules. The collisions cause thermal expansion, which generate an acoustic wave at the frequency of the laser modulation. The photoacoustic spectrometer module then processes the acoustic wave to identify the exact chemical or explosive.

Argonne's PAS System is an outgrowth of the traditional laboratory PAS system, which requires a sample collection to measures gas concentrations at parts-per-billion or parts-per-trillion levels.

Lead developer Hual-Te Chien is a second time R&D 100 Award Winner.

 

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Last Modified: Wed, April 20, 2016 9:36 AM

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