Infrared analysis of hair dyeing and bleaching history.


Journal

Analytical methods : advancing methods and applications
ISSN: 1759-9679
Titre abrégé: Anal Methods
Pays: England
ID NLM: 101519733

Informations de publication

Date de publication:
07 08 2020
Historique:
entrez: 31 7 2020
pubmed: 31 7 2020
medline: 15 5 2021
Statut: ppublish

Résumé

Forensic examination of hair is commonly performed to trace its origin and make a connection between a suspect and a crime scene. Such examination is based on subjective microscopic analysis of hair. During the last decade, several spectroscopic approaches have been proposed to make forensic analysis of hair more robust and reliable. Surface-enhanced Raman and attenuated total internal reflection infrared spectroscopies allowed for detection and identification of dyes directly on hair and even differentiation between commercial brands of those colorants. However, these is a question that remains unanswered: can artificial dyes be detected on bleached hair or bleaching can be used to fully erase information about hair coloring? In this study, we report experimental results that provide a clear answer to this question. We show that infrared analysis can be used to differentiate between undyed bleached hair and hair that was colored with both permanent and semi-permanent dyes prior to bleaching. We also show that IR analysis can be used to distinguish between undyed unbleached and undyed bleached hair. We demonstrate that in combination with multivariate statistical analysis, IR analysis can be used to distinguish with 96-100% accuracy between those hair classes.

Identifiants

pubmed: 32729856
doi: 10.1039/d0ay01068e
doi:

Substances chimiques

Hair Dyes 0
Sodium Compounds 0
Hypochlorous Acid 712K4CDC10

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3741-3747

Auteurs

Fernando Contreras (F)

Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas 77843, USA. dkurouski@tamu.edu.

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Classifications MeSH