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Multidimensional profiling of human body hairs using qualitative and semi-quantitative approaches with SR-XRF, ATR-FTIR, DSC, and SEM-EDX

PUBLISHED June 28, 2023 (DOI: https://doi.org/10.54985/peeref.2306p7526624)

NOT PEER REVIEWED

Authors

Karen Cloete1 , Ziga Smit2 , Alessandra Gianoncelli3
  1. Universify of South Africa
  2. University of Ljubljana
  3. Elettra—Sincrotrone

Conference / event

African Light Source and African Physical Society Joint Virtual Event, November 2022 (Virtual)

Poster summary

A multidimensional approach was followed to differentiate body hairs based on their physico-chemical properties. This case report focused on the analysis of body hair samples from a female participant (age 39) to control for inter-individual variability in hair chemical makeup and other confounding variables. Hair samples were analyzed using synchrotron synchrotron microbeam X-ray fluorescence (SR-XRF), attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) (complemented with chemometrics analysis), energy dispersive X-ray analysis (EDX) (complemented with heatmap analysis), differential scanning calorimetry (DSC), and scanning electron microscopy (SEM) analysis (complemented by descriptive statistics) to profile different body hairs in terms of their elemental, biochemical, thermal, and cuticle properties. This multidimensional approach provided supportive information to emphasize that intricate factors are responsible for the differences in physico-chemical properties that may have important implications for forensic science and other studies involving hair as a research matrix.

Keywords

Forensic, Body hair, Synchrotron X-ray fluorescence, SEM-EDX, ATR-FTIR, DSC

Research areas

Material Sciences, Physics, Molecular and Cellular Biosciences, Chemistry, Biological Sciences

References

No data provided

Funding

No data provided

Supplemental files

No data provided

Additional information

Competing interests
No competing interests were disclosed.
Data availability statement
The datasets generated during and / or analyzed during the current study are available from the corresponding author on reasonable request.
Creative Commons license
Copyright © 2023 Cloete et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Cloete, K., Smit, Z., Gianoncelli, A. Multidimensional profiling of human body hairs using qualitative and semi-quantitative approaches with SR-XRF, ATR-FTIR, DSC, and SEM-EDX [not peer reviewed]. Peeref 2023 (poster).
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