Discrimination and classification of chemical warfare agent simulants using a Love-wave sensor array

Abstract

An array made up of Love-wave sensors has been developed as a detection system for chemical warfare agents (CWAs). This array has been tested with well-known CWA simulants detecting very low concentrations, such as 40 ppb of DMMP, a simulant of sarin nerve gas, 250 ppb of DPGME, a simulant of nitrogen mustard and 15 ppm of DMA, a simulant of distilled mustard. Additionally, principal component analysis (PCA) as a data pre-processing and discrimination technique, and probabilistic neural networks (PNN) as a patterns classification technique, have been applied, obtaining good results concerning to discrimination and sensitivity.