A study for potential rapid discrimination of smokeless powders by near-infrared spectroscopy and chemometric modeling methods for forensic purposes

Smokeless powder is the primary propellant in civilian and military ammunition. And in China, the use of propellant for making homemade ammunition and bombs is an incipient criminal practice. The identification and discrimination of the propellant used can provide forensic information for its sources. Depending upon the ammunition fabricant and ammunition type, the recipe of propellant changes. The characterization of smokeless powders in terms of its spectral components is useful for differentiating the propellants. In this work, near-infrared spectroscopy (NIR) and chemometric modeling were used to explore a possibility of differentiation and prediction of smokeless powders from different sources. By comparison, the proposed neural network model showed an average accuracy of over 80%. Also, the potential for discrimination of smokeless powders was well demonstrated by using easy and fast near-infrared spectroscopic analyses. The use of chemical agents and time-consuming chromatography and mass spectrometry could, thereby, be avoided.