A Review On Analytical Techniques Used For Forensic Fiber Analysis

Abstract

Textile fibers are a key form of trace evidence, and play a very important role in crime scene investigation. Different kinds of techniques are used for fiber analysis, identification and/or differentiation. The focus of this chapter is to provide readers with a detailed review of different analytical methods that use light sources for either illumination or detection of trace samples for forensic fiber examination purposes. UV-vis MSP is mainly used for the examination of colors on fibers. Additional determination of dyes and pigments on the fibers is provided by Raman spectroscopy. Sometimes, it also provides information regarding the polymeric nature of the fibers; however, FTIR spectroscopy is recommended to determine the nature, class and subclass of fibers. Being complementary to each other, both Raman and FTIR spectroscopy should be used together in order to perform a comprehensive analysis of the evidence at molecular levels. More informative spectroscopic techniques such as IR-chemical imaging and X-ray fluorescence spectroscopy are emerging in the field of fiber analysis. Recently, our group employed fluorescence microscopy for enhancing textile fiber identification using detergent fluorescence, and for the discrimination of visually and microscopically indistinguishable single fiber pairs. This chapter aims to provide readers with a comprehensive review regarding several analytical techniques that are used for forensic fiber analysis; along with their advantages and limitations. Microscopic, spectroscopic, and chromatographic techniques will be reviewed according to earlier reports published by several researchers and forensic experts.

Publication Date

1-1-2018

Publication Title

Comprehensive Series in Photochemical and Photobiological Sciences

Volume

17

Number of Pages

175-206

Document Type

Article; Book Chapter

Personal Identifier

scopus

DOI Link

https://doi.org/10.1039/9781788010344-00175

Socpus ID

85051730709 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85051730709

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