Identification of different hair dyes in dyed hair using Attenuated Total Reflection Fourier Transform Infrared (ATR FT-IR) and Surface Enhancing Raman Spectroscopy (SERS).

Abstract

Forensic analysis of dyed hair by using Attenuated Total Reflectance Fourier Transform Infrared (ATR FT-IR) Spectroscopy and Surface Enhanced Raman Spectroscopy (SERS) was undertaken to differentiate between commercial hair dye brands. Human hair samples across five natural colors were dyed and subsequently analyzed to identify chemical changes induced by the dyeing process. Solvent dye extraction experiments were then conducted to isolate and compare the dye's chemical makeup against its commercial counterparts. Statistically, dye brands could be differentiated by Partial Least Squares Discriminant Analysis (PLSDA), demonstrating the applicability of machine learning in forensic hair dye analysis. While ATR FT-IR showed promising results in identifying characteristic bands and achieving high predictive accuracy, SERS faced limitations in data acquisition, indicating areas for future research. Overall, the findings highlight the potential of spectroscopic techniques combined with statistical analysis to enhance forensic investigations of dyed hair. Further exploration into used solvents and nanoparticle types for improved SERS are suggested. This research contributes to the development of forensic methodologies for dyed hair evidence, aiming for integration into forensic databases to support crime laboratory analyses.