Study of Spectral Modifications in Acidified Ignitable Liquids by Attenuated Total Reflection Fourier Transform Infrared Spectroscopy

In this work, the spectral characteristics of two types of acidified gasoline and acidified diesel fuel are discussed. Neat and acidified ignitable liquids (ILs) infrared absorption spectra obtained by attenuated total reflection Fourier transform infrared spectroscopy were compared in order to identify the modifications produced by the reaction of the ILs with sulfuric acid. Several bands crucial for gasoline identification were modified, and new bands appeared over the reaction time. In the case of acidified diesel fuel, no significant modifications were observed. Additionally, the neat and acidified ILs spectra were used to perform a principal components analysis in order to confirm objectively the results. The complete discrimination among samples was successfully achieved, including the complete differentiation among gasoline types. Taking into account the results obtained in this work, it is possible to propose spectral fingerprints for the identification of non-burned acidified ILs in forensic investigations related with arson or the use of improvised incendiary devices (IIDs)

Short wave infrared chemical imaging as future tool for analysing gunshot residues patterns in targets

This work used chemical imaging in the short-wave infrared region for analysing gunshot residues (GSR) patterns in cotton fabric targets shot with conventional and non-toxic ammunition. It presents a non-destructive, non-toxic, highly visual and hiperspectral-based approach. The method was based on classical least squares regression, and was tested with the ammunition propellants and their standard components' spectra. The propellants' spectra were satisfactorily used (R2 >0.966, and CorrCoef >0.982) for identifying the GSR irrespective of the type of ammunition used for the shooting. In a more versatile approach, nitrocellulose, the main component in the ammunition propellants, resulted an excellent standard for identifying GSR patterns (R2>0.842, and CorrCoef >0.908). In this case, the propellants' stabilizers (diphenilamine and centralite), and its nitrated derivatives as well as dinitrotoluene, showed also high spectral activity. Therefore, they could be recommended as complementary standards for confirming the GSR identification. These findings establish the proof of concept for a science-based evidence useful to support expert reports and final court rulings. This approach for obtaining GSR patterns can be an excellent alternative to the current and traditional chemical methods, which are based in presumptive and invasive colour tests.Ministerio de Economía y Competitividad (MINECO

Analytical tools for the analysis of fire debris. A review: 2008-2015

The analysis of fire debris evidence might offer crucial information to a forensic investigation, when for instance, there is suspicion of the intentional use of ignitable liquids to initiate a fire. Although the evidence analysis in the laboratory is mainly conducted by a handful of well-established methodologies, during the last eight years several authors proposed noteworthy improvements on these methodologies, suggesting new interesting approaches. This review critically outlines the most up-to-date and suitable tools for the analysis and interpretation of fire debris evidence. The survey about analytical tools covers works published in the 2008&-2015 period. It includes sources of consensus-classified reference samples, current standard procedures, new proposals for sample extraction and analysis, and the most novel statistical tools. In addition, this review provides relevant knowledge on the distortion effects of the ignitable liquid chemical fingerprints, which have to be considered during interpretation of results

Shooting distance estimation based on gunshot residues analyzed by XRD and multivariate analysis

The most used and validated methods for estimating the shooting distance using the gunshot residues (GSR) inforensic labs are based on chemographic colour tests. In these techniques, the cloth-trapped residues are trans-ferred to a surface to be revealed using chemical reagents. However, because they imply a visual inspection, theirinterpretation may vary, thus adding possible errors to the forensic results. Therefore, it is important tofind anobjective analysis technique for deciding during the results interpretation. In this study, X-Ray diffraction (XRD)was used to measure the GSR on cotton-polyester fabrics. The resulting diffractograms were aligned using acorrelation optimized warping (COW) function, and then analysed using partial least squares to latent structures(PLS), and orthogonal PLS (OPLS). Both methods gave good prediction models in the 5&-300 cm distance range,with determination coefficients of 0.99. Using the gun utilized during the shooting rendered good predictionmodels with quite small prediction errors (about 3 and 7%). Combining the two guns for the calculations, resultedin a prediction model with a larger prediction error (about 14%) but still good for predicting the shooting dis-tance. This would indicate that it is possible to use a similar gun to perform a shooting distance prediction withouthaving the actual gun used during the investigated shooting

Differentiation of blood and environmental interfering stains on substrates by Chemometrics-Assisted ATR FTIR spectroscopy

Blood is the most common and relevant bodily fluid that can be found in crime scenes. It is critical to correctly identify it, and to be able to differentiate it from other substances that may also appear at the crime scene. In this work, several stains of blood, chocolate, ketchup, and tomato sauce on five different substrates (plywood, metal, gauze, denim, and glass) were analysed by ATR FTIR spectroscopy assisted with orthogonal partial least square discriminant analysis (OPLS-DA) models. It was possible to differentiate blood from the environmental interfering substances independently of the substrate they were on, and to differentiate bloodstains according to the substrate they were deposited on. These results represent a proof-of-concept that open new horizons to differentiate bloodstains from other interfering substances on common substrates present in crime scenes

A comprehensive study of protein-mesoporous-macroporous silica interactions by extended canonical variate analysis of Raman spectra

Understanding the protein-support interactions is of major importance when manufacturing bionanomaterials to a certain application. These interactions can be the cause for enhanced properties or denaturation phenomena in the target protein. Raman spectroscopy was applied to a bionanomaterial comprehending the protein beta-galactosidase immobilized by physical adsorption into a mesoporous-macroporous silica material, with a nanoporous network consisting of 9-nm mesopores and 200-nm macropores. Raman spectra of the bionanomaterial evidenced a complex amount of differences related to the Raman shifts, intensities, band enlargement, appearance of new bands, and overlapping, in comparison with the silica support and the protein spectra. To help in the analysis of the Raman spectra and in the inspection of possible protein-support interactions, ECVA (extended canonical variate analysis) was used as a chemometric complementary tool, dividing the spectra into four segments: 1 (3,100 to 2,800 cm(-1)), 2 (1,800 to 1,500 cm(-1)), 3 (1,500 to 1,200 cm(-1)), and 4 (1,200 to 900 cm(-1)). Major alterations in the Amide I band (1,800 to 1,500 cm(-1)) and the amino acid band regions demonstrated possible structure alterations to a non-native form of the protein beta-galactosidase. Also, other minor alterations were observed in other spectral regions (3,100 to 2,800 cm(-1),1,500 to 1,200 cm(-1), and 1,200 to 900 cm(-1)) also representative of protein structure alteration due to protein-support interactions

Discrimination of non-explosive and explosive samples through nitrocellulose fingerprints obtained by capillary electrophoresis

This work is focused on a novel procedure to discriminate nitrocellulose-based samples with nonexplosive and explosive properties. The nitrocellulose study has been scarcely approached in the literature due to its special polymeric properties such as its high molar mass and complex chemical and structural characteristics. These properties require the nitrocellulose analysis to be performed by using a few organic solvents and in consequence, they limit the number of adequate analytical techniques for its study. In terms of identification of pre-blast explosives, mass spectrometry is one of the most preferred technique because it allows to obtain structural information. However, it has never been used to analyze polymeric nitrocellulose. In this study, the differentiation of non-explosive and explosive samples through nitrocellulose fingerprints obtained by capillary electrophoresis was investigated. A batch of 30 different smokeless gunpowders and 23 different everyday products were pulverized, derivatized with a fluorescent agent and analyzed by capillary electrophoresis with laser-induced fluorescence detection. Since this methodology is specific to d-glucopyranose derivatives (cellulosic and related compounds), and paper samples could be easily found in explosion scenes, 11 different paper samples were also included in the study as potential interference samples. In order to discriminate among samples, multivariate analysis (principal component analysis and soft independent modeling of class analogy) was applied to the obtained electrophoretic profiles. To the best of our knowledge, this represents the first study that achieve a successful discrimination between non-explosive and explosive nitrocellulose-based samples, as well as potential cellulose interference samples, and posterior classification of unknown samples into their corresponding groups using CE-LIF and chemometric tools.Ministerio de Ciencia e Innovació

Classification of Various Marijuana Varieties by Raman Microscopy and Chemometrics

Fernando Ortega Ojeda desarrolló el procedimiento de tratamiento estadístico de datos y supervisó los cálculos multivariantes en The Unscrambler y SIMCA. The Raman analysis of marijuana is challenging because of the sample's easy photo-degradation caused by the laser intensity. In this study, optimization of collection parameters and laser focusing on marijuana trichome heads allowed collecting Raman spectra without damaging the samples. The Raman spectra of Delta9-tetrahydrocannabinol (THC), cannabidiol (CBD), and cannabinol (CBN) standard cannabinoids were compared with Raman spectra of five different types of marijuana: four Sativa varieties (Amnesia Haze, Amnesia Hy-Pro, Original Amnesia, and Y Griega) and one Indica variety (Black Domina). The results verified the presence of several common spectral bands that are useful for marijuana characterization. Results were corroborated by the quantum chemical simulated Raman spectra of their acid-form (tetrahydrocannabinol acid (THCA), cannabidiol acid (CBDA)) and decarboxylated cannabinoids (THC, CBD, and CBN). A chemometrics-assisted method based on Raman microscopy and OPLS-DA offered good classification among the different marijuana varieties allowing identification of the most significant spectral bands.Instituto Universitario de Investigación en Ciencias Policiales (IUICP), Universidad de Alcalá (UAH)

Analysis and differentiation of paper samples by capillary electrophoresis and multivariate analysis

This work reports an investigation for the analysis of different paper samples using CEwith laser-induced detection. Papers from four different manufactures (white-copy paper)and four different paper sources (white and recycled-copy papers, adhesive yellow papernotes and restaurant serviettes) were pulverized by scratching with a surgical scalpel priorto their derivatization with a fluorescent labeling agent, 8-aminopyrene-1,3,6-trisulfonicacid. Methodological conditions were evaluated, specifically the derivatization conditionswith the aim to achieve the best S/N signals and the separation conditions in order toobtain optimum values of sensitivity and reproducibility. The best conditions, in termsof fastest, and easiest sample preparation procedure, minimal sample consumption, aswell as the use of the simplest and fastest CE-procedure for obtaining the best analyticalparameters, were applied to the analysis of the different paper samples. The registeredelectropherograms were pretreated (normalized and aligned) and subjected to multivari-ate analysis (principal component analysis). A successful discrimination among papersamples without entanglements was achieved. To the best of our knowledge, this workpresents the first approach to achieve a successful differentiation among visually similarwhite-copy paper samples produced by different manufactures and paper from differentpaper sources through their direct analysis by CE-LIF and subsequent comparative studyof the complete cellulose electropherogram by chemometric tools

Morphometric analysis of bite mark patterns caused by domestic dogs (Canis lupus familiaris) using dental wax registers

Dog bites are a known public health problem involving physical, mental and emotional traumas. From a forensic point of view, it has been stated that their morphological characters, and the intercanine and interincisive measurements, could allow a taxonomic and specific identification of the implicated animal. The aim of this study was to differentiate and identify the biological profile of a potential aggressor dog by analysing eight morphometric bite patterns belonging to three different dog breeds. The data obtained were analyzed following three categories: a) breeds; b) sexes among breeds; and c) sex within breed. Significant differences were detected among the variables (p <= 0.05), but only the maximum maxillary intercanines width (MaxCW) allowed a breed differentiation. The other variables allowed a differentiation between two breeds or one breed over the others. The principal components analysis (PCA) allowed visualizing the degree of dispersion and relationship among the scores. It showed three well-defined and separated breed groups, and different degrees of dispersion within and among breeds. The most important variable for such a differentiation was MaxCW. When considering sex among breeds for males, it showed a statistically significant difference, but only the diastema located between the third left mandibular, incisive and the left mandibular canine (C-I-ManL) allowed breed differentiation. For females, only MaxCW allowed a differentiation among breeds. The multivariate analysis permitted with a 95 % confidence interval, a breed and sex differentiation. Besides, the PCA models allowed classifying, identifying, separating and graphically showing the relationship among the variables. This made it possible to differentiate between breeds and sexes. Due to the large range of dog breeds around the world, this multivariate analysis could also help determining the dog's weight and size, narrowing down towards an approximate number of offending dogs, focussing on a certain kind of dog breed, and pinpointing any suspect dog