# Raman Scattering Analysis of High Explosives on Human Hair: From Aromatic (TNT) to Aliphatic (RDX and PETN)

## TL;DR

This study uses Raman spectroscopy and PCA to detect high explosives on different types of human hair, showing rapid and accurate identification.

## Contribution

The study introduces a non-invasive method for detecting HEs on hair using Raman scattering and PCA with minimal sample preparation.

## Key findings

- Raman spectroscopy with PCA successfully detected TNT, RDX, and PETN on black, bleached, and gray hair.
- Gray hair showed better discrimination of explosives due to the absence of melanin.
- PCA with derivative data pretreatment improved classification of HEs based on NO2 vibrations.

## Abstract

There is a need to develop rapid, in situ methods that require less sample preparation and lower limits of detection for the detection of High Explosives (HEs). Considering that human hair is one of the primary attributes of the human body, its presence can be used to identify possible traces of hair evidence for forensic screenings. Using non-invasive in situ approaches coupled with multivariate analysis (MVA) can enable rapid detection, thereby decreasing analysis time and reducing the cognitive load on analysts, with response times as low as milliseconds or lower. This preliminary study demonstrates the detection of 2,4,6-trinitrotoluene (TNT), 1,3,5-trinitroperhydro-1,3,5-triazine (RDX), and pentaerythritol tetranitrate (PETN) on black, bleached, and natural gray human hair coupled with principal component analysis (PCA). It was possible to discriminate the HE signals from those of the substrates (hair types) on black, gray, and bleached hair by monitoring characteristic peaks for the nitro group’s vibrations of the explosives. Gray hair presented good discrimination for the explosives due to the absence of melanin. The best modes for discriminating HEs from all three hair types were identified using PCA, with data pretreatment based on the first and second derivatives of the algorithms. The classifications were based on the more substantial variation in the NO2 symmetric vibration for each HE.