Research was conducted on thirteen 100% cotton denim samples using an acid wash, established by Murray, to extract oligosaccharides from the cellulosic material. The oligosaccharide ion groups (+, +, and +) for molecules with degrees of polymerization between two and seven (DP2-DP7) were analyzed using liquid chromatography coupled to mass spectrometry with an electrospray ionization interface (LC-ESI-MS). The results were compared using the least-squares means in a Multivariate ANOVA (MANOVA) test followed by Univariate ANOVA and Tukey HSD tests and demonstrated that the method could correctly determine that two samples were statistically different 85.9% of the time when analyzing the amount (ng) of each of the oligosaccharide ion groups separately, and 82.0% when analyzing the total moles of monosaccharide units released. A dye extraction was performed on the denim materials and the extract analyzed using gas chromatography coupled with mass spectrometry (GC-MS). Indigo dye was present in all of the denim samples except one. When these results were combined with the two oligosaccharide statistical analyses, the discriminating power was increased to 88.5% and 85.9%, respectively. Additional cellulosic materials were also investigated including four white 100% cotton t-shirts as well as five raw cotton samples grown in Tajikistan, Uzbekistan, Egypt, Iran, and Benin West Africa. The analytical methodology gave results for the white cotton t-shirts and raw cotton samples that were inconsistent with those obtained from the denim samples.

The analysis of 110 automotive paint samples was conducted for the research presented here. Laser-induced breakdown spectroscopy (LIBS) was the central instrument utilized for analysis although scanning electron microscopy / energy dispersive x-ray spectroscopy (SEM/EDS) and Fourier transform infrared spectroscopy - attenuated total reflection (FTIR-ATR) analyses were also performed. Two separate methods of LIBS analysis of samples were used: a cross sectional analysis and a drill down analysis. SEM/EDS analysis focused on the cross section while FTIR-ATR analysis concentrated on the clearcoat layer. Several different data/statistical analyses were evaluated including principal components analysis (PCA), two tailed t-tests based on several different metrics (Hit Quality Index (HQI), Pearson's correlation and Sorenson index), multivariate analysis of variance and receiver operating characteristic (ROC) curves. Full spectrum data analysis from LIBS spectra resulted in 99.7% discrimination between different sample comparisons and 12% between same sample comparisons based on HQI and t-tests. Peak analysis of LIBS spectra resulted in 87.5% discrimination between different sample comparisons and 5% between same sample comparisons based on MANOVA. When combining the results of the FTIR-ATR and SEM/EDS analyses, 88% of the samples could be discriminated.

Fatal accidents on the road are an unfortunate daily occurrence, with almost 30,000 deaths resulting from hit-and-runs in the USA between 2006 and 2021. The identification of the driver responsible for this road crime can become a challenge. Nonetheless, the accident scene provides a large amount of trace evidence that can prove critical to this matter, one of them being the tire marks. While traditional tire mark analysis is full of physical information helping the reconstruction of the event, additional information can be extracted from the rubber left during the braking event. Each tire model is manufactured with a specific design, obtained by a chemical formulation that can become its signature. Supplemental to the molecular profile of the rubber itself, analysis of the trace and contaminant elements can help build the chemical signature for the tire rubber. This work consists of establishing the link between the tire and the skid mark and particles it left during a braking event. The difference between tire models was proved from the elemental analysis of the tire rubber itself, showing that the specific content of minor and trace elements is specific to the model. Expanding to the problem of tire marks, the first challenge consists in efficiently sampling the rubber from the road. The development of an effective procedure to lift the tire particles from the mark is demonstrated in this work. This does present some challenges, including removal of other particles present within the lift and extraction of the tire rubber for further analysis by ICP-MS, providing an elemental profile for the sampled skid mark. Finally, with the skid mark rubber analyzed, it is compared with the elemental profile of the rubber from the source tire. The results of this comparison will be discussed in both simulated (with a lab- made tire mark maker) and field cases (from braking tests performed by the Florida Highway Patrol (FHP)). The results of my research provide the forensic community with the first evaluation of elemental analysis of tire rubber to use this seldom used trace evidence, all along the analytical process, from sampling to analysis to attribution.

Current fire debris analysis procedure involves using the chromatographic patterns of total ion chromatograms, extracted ion chromatograms, and target compound analysis to identify an ignitable liquid according to the American Society for Testing and Materials (ASTM) E 1618 standard method. Classifying the ignitable liquid is accomplished by a visual comparison of chromatographic data obtained from any extracted ignitable liquid residue in the debris to the chromatograms of ignitable liquids in a database, i.e. by visual pattern recognition. Pattern recognition proves time consuming and introduces potential for human error. One particularly difficult aspect of fire debris analysis is recognizing an ignitable liquid residue when the intensity of its chromatographic pattern is extremely low or masked by pyrolysis products. In this research, a unique approach to fire debris analysis was applied by utilizing the samples' total ion spectrum (TIS) to identify an ignitable liquid, if present. The TIS, created by summing the intensity of each ion across all elution times in a gas chromatography-mass spectrometry (GC-MS) dataset retains sufficient information content for the identification of complex mixtures . Computer assisted spectral comparison was then performed on the samples' TIS by target factor analysis (TFA). This approach allowed rapid automated searching against a library of ignitable liquid summed ion spectra. Receiver operating characteristic (ROC) curves measured how well TFA identified ignitable liquids in the database that were of the same ASTM classification as the ignitable liquid in fire debris samples, as depicted in their corresponding area under the ROC curve. This study incorporated statistical analysis to aid in classification of an ignitable liquid, therefore alleviating interpretive error inherent in visual pattern recognition. This method could allow an analyst to declare an ignitable liquid present when utilization of visual pattern recognition alone is not sufficient.

Fiber analysis using birefringence has been around for years but has only recently been looked at more closely under a microscope. Recent scientists have proposed methods to correct issues found with fiber analysis using birefringence, yet there has not be a defined perfect method. This research will focus on correcting previously found issues with works by Michel-Lévy and Sorensen's, as well as other scientists involved and perfecting the analysis of fiber through birefringence. The goal will be to take this research one step further into the analysis of textile fibers by RGB value analysis and birefringence. The RGB values will be analyzed in a color analysis program to compare HEX values. The cross section of the fiber will be done to receive an accurate diameter measurement of the fiber. Those RGB values and cross section diameter will then be matched to the Michel-Lévy chart and the birefringence will be determined.

A two-step protocol has been devised as a rapid and selective alternative to conventional differential extraction techniques with an increased recovery of DNA. The protocol involves pressure cycling with the Barocycler® NEP 2320 from Pressure Biosciences. Inc. in alkaline conditions for epithelial cell lysis and removal. This step is followed by alkaline lysis at 95º C for extraction of sperm cell DNA. At 1:1 or 2:1 female to male cell ratios, high selectivity and complete separation can be achieved. But at higher ratios, male allelic dropout is observed. This protocol has been modified to generate a clean male profile at a 20:1 cell ratio through optimization of NaOH concentration and inclusion of an additional pressure cycling step. Validation studies have been performed to assess the efficiency of this method under various conditions. An additional immunomagnetic cell capture pretreatment allowed for nearly complete separation at cell ratios of up to 200:1.

Positive identification of a deceased individual is one of the major aspects of modem forensic death investigations. Incomplete or fragmented skeletal remains pose a problem for identification because the normal methods forensic anthropologists employ for compiling a biological profile of the decedent are of no use. Ancestry is an important aspect of the biological profile that, when known, can help narrow the focus of investigations by excluding many individuals from the search scope. This thesis describes molecular genetic methods which can be used to estimate ancestry in order to aid in forensic identification when other methods fail. The Y chromosome is one aspect of the genome shown to contain markers which are associated with the geographical origins of its possessor. The laboratory aspect of this research involved taking bone samples from humerii, extracting DNA from these samples and then sequencing a number of Y-SNPs in order to predict the biogeographical origins of each sample. Performing this research demonstrated the steps involved in this type of genetic ancestral analysis. At present, anthropology can only distinguish between major population groups. However, as research continues to be performed, the discriminatory power of molecular genetic ancestral analyses such as this has the potential to be further refined so that sub-populations may be distinguished between. This could be of great value if introduced into the forensic community.

The manner in which remains decompose has been and is currently being researched around the world, yet little is still known about the generated scent of death. In fact, it was not until the Casey Anthony trial that research on the odor released from decomposing remains, and the compounds that it is comprised of, was brought to light. The Anthony trial marked the first admission of human decomposition odor as forensic evidence into the court of law; however, it was not “ready for prime time” as the scientific research on the scent of death is still in its infancy. This research employed the use of solid-phase microextraction (SPME) with gas chromatography-mass spectrometry (GC-MS) to identify the volatile organic compounds (VOCs) released from decomposing remains and to assess the impact that different environmental conditions had on the scent of death. Using human cadaver analogues, it was discovered that the environment in which the remains were exposed to dramatically affected the odors released by either modifying the compounds that it was comprised of or by enhancing/hindering the amount that was liberated. In addition, the VOCs released during the different stages of the decomposition process for both human remains and analogues were evaluated. Statistical analysis showed correlations between the stage of decay and the VOCs generated, such that each phase of decomposition was distinguishable based upon the type and abundance of compounds that comprised the odor. This study has provided new insight into the scent of death and the factors that can dramatically affect it, specifically, frozen, aquatic, and soil environments. Moreover, the results revealed that different stages of decomposition were distinguishable based upon the type and total mass of each compound present. Thus, based upon these findings, it is suggested that the training aids that are employed for human remains detection (HRD) canines should 1) be characteristic of remains that have undergone decomposition in different environmental settings, and 2) represent each stage of decay, to ensure that the HRD canines have been trained to the various odors that they are likely to encounter in an operational situation.

Mobile device data continues to increase in significance in both civil and criminal investigations. Location data is often of particular interest. To date, research has established that the devices are location aware, incorporate a variety of resources to obtain location information, and cache the information in various ways. However, a review of the existing research suggests varying degrees of reliability of any such recovered location data. In an effort to clarify the issue, this project offers case studies of multiple Android mobile devices utilized in controlled conditions with known settings and applications in documented locations. The study uses data recovered from test devices to corroborate previously identified accuracy trends noted in research involving live-tracked devices, and it further offers detailed analysis strategies for the recovery of location data from devices themselves. A methodology for reviewing device data for possible artifacts that may allow an examiner to evaluate location data reliability is also presented. This paper also addresses emerging trends in device security and cloud storage, which may have significant implications for future mobile device location data recovery and analysis. Discussion of recovered cloud data introduces a distinct and potentially significant resource for investigators, and the paper addresses the cloud resources' advantages and limitations.

In forensic casework analysis it is necessary to obtain genetic profiles from increasingly smaller amounts of biological material left behind by perpetrators of crime. The ability to obtain profiles from trace biological evidence is demonstrated with so-called ‘touch DNA evidence’ which is perceived to be the result of DNA obtained from shed skin cells transferred from donor to an object or person during physical contact. However, the current method of recovery of trace DNA involves cotton swabs or adhesive tape to sample an area of interest. This "blindswabbing" approach may result in the recovery of biological material from different individuals resulting in admixed DNA profiles which are often difficult to interpret. Profiles recovered from these samples are reported to be from shed skin cells with no biological basis for that determination. A specialized approach for the isolation of single or few cells from ‘touch DNA evidence’ is necessary to improve the analysis and interpretation of recovered profiles. Here we describe the development of optimized and robust micro volume PCR reactions (1-5 μL) to improve the sensitivity and efficiency of ‘touch DNA’ analysis. These methods will permit not only the recovery of the genetic profile of the donor of the biological material, but permit an identification of the tissue source of origin using mRNA profiling. Results showed that the 3.5 uL amplification volume, a fraction of the standard 25 uL amplification volume, was the most ideal volume for the DNA assay, as it had very minimal evaporation with a 50% profile recovery rate at a single cell equivalent input (~5 pg) with reducing amplification volume alone. Findings for RNA showed that by reducing both amplification steps, reverse transcriptase PCR (20 uL) and body fluid multiplex PCR (25 uL), to iv 5 uL, ideal results were obtained with an increase in sensitivity and detection of six different body fluids down to 50 pg. Once optimized at the trace level, the assays were applied to the collection of single and few cells. DNA findings showed that about 40% of a full profile could be recovered from a single buccal cell, with nearly 80% of a full profile recovered from only two cells. RNA findings from collected skin particles of "touched" surfaces showed accurate skin detection down to 25 particles and detection in one clump of particles. The profiles recovered were of high quality and similar results were able to be replicated through subsequent experiments. More studies are currently underway to optimize these developed assays to increase profile recovery at the single cell level. Methods of doing so include comparing different locations on touched surfaces for highest bio-particle recovery and the development of physical characteristics of bio-particles that would provide the most ideal results