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Multidimensional Room-Temperature Fluorescence Microscopy for the Nondestructive Analysis of Forensic Trace Textile Fibers

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Date Issued:
2016
Abstract/Description:
The purpose of this dissertation is to advance nondestructive methodology for forensic fiber examination. Non-destructive techniques that can either discriminate between similar fibers or match a known to a questioned fiber (-) and still preserve the physical integrity of the fibers for further court examination - are highly valuable in forensic science. A challenging aspect of forensic fiber examinations involves the comparison of fibers colored with visually indistinguishable dyestuffs. This is not an uncommon situation, as there are numerous indistinguishable fibers pre-dyed with commercial dyes of virtually identical colors. Minimal chemical structural variations are actually encouraged by the dye patent process and commercial competition.The common denominator to forensic methodology is the fact that fiber analysis primarily focuses on the dyes used to color the fibers and do not investigate other potential discriminating components present in the fiber. This dissertation explores a different aspect of fiber analysis as it focuses on the total fluorescence emission of fibers. In addition to the contribution of the textile dye (or dyes) to the fluorescence spectrum of the fiber, we consider the contribution of intrinsic fluorescence impurities (-) i.e. impurities imbedded into the fibers during fabrication of garments - as a reproducible source of fiber comparison. Although fluorescence microscopy is used in forensic labs for single fiber examination, measurements are made with the aid of band-pass filters that provide very limited information on the spectral profiles of fibers. We take the non-destructive nature of fluorescence microscopy to a higher level of selectivity with the collection of room-temperature fluorescence excitation emission matrices (RTF-EEMs). The information contained in the EEMs was first used to select the best excitation wavelength for recording first order data, i.e. two-dimensional fluorescence spectra. Pairwise comparisons involved the following visually indistinguishable fibers: nylon 361 pre-dyed with acid yellow (AY) 17 and AY 23, acrylic 864 pre-dyed with basic green (BG) 1 and BG 4, acetate satin 105B pre-dyed with disperse blue (DB) 3 and DB 14, and polyester 777 pre-dyed with disperse red (DR) 1 and DR 19. With the exception of acrylic 864 fibers dyed with BG1 and BG4, the comparison of two-dimensional spectra via principal component analysis (PCA) provided accurate fiber identification for all the analyzed fibers. The same approach was later applied to the investigation of laundering effects on the comparison of textile fibers. The presence of brighteners and other detergent components adsorbed in the fibers provided spectral fingerprints that enhanced the fiber identification process.The full dimensionality of EEMs was then explored with the aid of parallel factor analysis (PARAFAC), a second order algorithm capable to determine the number of fluorescence components that contribute to an EEM along with their individual excitation and emission profiles. The application of PARAFAC was carried out unsupervised and supervised by linear discrimination analysis (LDA). The classification performances of PARAFAC and LDA-supervised PARAFAC were compared to the one obtained with supervised discriminant unfolded partial least squares (DU-PLS). The best discrimination was obtained with the supervised DU-PLS, which allowed the pairwise differentiation of the four pairs of investigated fibers.DU-PLS was then used to investigate weathering effects on the spectral features of cotton 400 pre-dyed with DB1, nylon 361 pre-dyed with AY17 and acrylic 864 pre-dyed with BG4. The investigated fibers were exposed to humid (Florida) and dry (Arizona) weathering conditions for three, six, nine and twelve months. In all cases, this algorithm was unable to differentiate non-exposed acrylic fibers from exposed acrylic fibers. DU-PLS was able to differentiate non-exposed cotton and nylon fibers from exposed fibers to Florida and Arizona weathering conditions. It was possible to determine the period of exposure to either Florida or Arizona conditions. It was also possible to discriminate between fibers exposed to Florida or Arizona weathering conditions for the same period of time. These results provide the foundation for future studies towards a non-destructive approach capable to provide information on the history of the fiber.
Title: Multidimensional Room-Temperature Fluorescence Microscopy for the Nondestructive Analysis of Forensic Trace Textile Fibers.
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Name(s): Mujumdar, Nirvani, Author
Campiglia, Andres, Committee Chair
Sigman, Michael, Committee Member
Harper, James, Committee Member
Rex, Matthew, Committee Member
Peale, Robert, Committee Member
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2016
Publisher: University of Central Florida
Language(s): English
Abstract/Description: The purpose of this dissertation is to advance nondestructive methodology for forensic fiber examination. Non-destructive techniques that can either discriminate between similar fibers or match a known to a questioned fiber (-) and still preserve the physical integrity of the fibers for further court examination - are highly valuable in forensic science. A challenging aspect of forensic fiber examinations involves the comparison of fibers colored with visually indistinguishable dyestuffs. This is not an uncommon situation, as there are numerous indistinguishable fibers pre-dyed with commercial dyes of virtually identical colors. Minimal chemical structural variations are actually encouraged by the dye patent process and commercial competition.The common denominator to forensic methodology is the fact that fiber analysis primarily focuses on the dyes used to color the fibers and do not investigate other potential discriminating components present in the fiber. This dissertation explores a different aspect of fiber analysis as it focuses on the total fluorescence emission of fibers. In addition to the contribution of the textile dye (or dyes) to the fluorescence spectrum of the fiber, we consider the contribution of intrinsic fluorescence impurities (-) i.e. impurities imbedded into the fibers during fabrication of garments - as a reproducible source of fiber comparison. Although fluorescence microscopy is used in forensic labs for single fiber examination, measurements are made with the aid of band-pass filters that provide very limited information on the spectral profiles of fibers. We take the non-destructive nature of fluorescence microscopy to a higher level of selectivity with the collection of room-temperature fluorescence excitation emission matrices (RTF-EEMs). The information contained in the EEMs was first used to select the best excitation wavelength for recording first order data, i.e. two-dimensional fluorescence spectra. Pairwise comparisons involved the following visually indistinguishable fibers: nylon 361 pre-dyed with acid yellow (AY) 17 and AY 23, acrylic 864 pre-dyed with basic green (BG) 1 and BG 4, acetate satin 105B pre-dyed with disperse blue (DB) 3 and DB 14, and polyester 777 pre-dyed with disperse red (DR) 1 and DR 19. With the exception of acrylic 864 fibers dyed with BG1 and BG4, the comparison of two-dimensional spectra via principal component analysis (PCA) provided accurate fiber identification for all the analyzed fibers. The same approach was later applied to the investigation of laundering effects on the comparison of textile fibers. The presence of brighteners and other detergent components adsorbed in the fibers provided spectral fingerprints that enhanced the fiber identification process.The full dimensionality of EEMs was then explored with the aid of parallel factor analysis (PARAFAC), a second order algorithm capable to determine the number of fluorescence components that contribute to an EEM along with their individual excitation and emission profiles. The application of PARAFAC was carried out unsupervised and supervised by linear discrimination analysis (LDA). The classification performances of PARAFAC and LDA-supervised PARAFAC were compared to the one obtained with supervised discriminant unfolded partial least squares (DU-PLS). The best discrimination was obtained with the supervised DU-PLS, which allowed the pairwise differentiation of the four pairs of investigated fibers.DU-PLS was then used to investigate weathering effects on the spectral features of cotton 400 pre-dyed with DB1, nylon 361 pre-dyed with AY17 and acrylic 864 pre-dyed with BG4. The investigated fibers were exposed to humid (Florida) and dry (Arizona) weathering conditions for three, six, nine and twelve months. In all cases, this algorithm was unable to differentiate non-exposed acrylic fibers from exposed acrylic fibers. DU-PLS was able to differentiate non-exposed cotton and nylon fibers from exposed fibers to Florida and Arizona weathering conditions. It was possible to determine the period of exposure to either Florida or Arizona conditions. It was also possible to discriminate between fibers exposed to Florida or Arizona weathering conditions for the same period of time. These results provide the foundation for future studies towards a non-destructive approach capable to provide information on the history of the fiber.
Identifier: CFE0006838 (IID), ucf:51773 (fedora)
Note(s): 2016-12-01
Ph.D.
Sciences, Chemistry
Doctoral
This record was generated from author submitted information.
Subject(s): Forensic fiber analysis -- fluorescence microscopy
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0006838
Restrictions on Access: public 2017-06-15
Host Institution: UCF

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