Mark Baron

An analysis of legal highs—do they contain what it says on the tin?

In recent years the availability of so-called legal highs over the Internet has hugely increased. Numerous online legal-high retailers market a broad variety of products which are advertised as research chemicals, bath salts, or plant food although clearly intended for human consumption as recreational drug replacements. No guidelines exist as to what is sold and in what purity. Consumers are led to believe that purchased goods are entirely legal. In this study, several legal-high products were purchased and analyzed for their content. The powdered products were screened with attenuated total reflectance-Fourier Transform Infrared (ATR-FTIR) followed by gas chromatography-mass spectrometry (GC-MS) analysis of methanol extracts. Spectra were compared to reference standards and the NIST library. Results showed that 6 out of 7 products did not contain the advertised active ingredient. Moreover, five samples contained the controlled substances benzylpiperazine and 1-[3-(trifluoromethyl)phenyl]piperazine combined with caffeine.

Review of analytical techniques for arson residues

ABSTRACT: Arson is a serious crime that affects society through cost, property damage, and loss of life. It is important that the methods and technologies applied by fire investigators in detection of evidence and subsequent analyses have a high degree of reliability, sensitivity, and be subject to rigorous quality control and assurance. There have been considerable advances in the field of arson investigation since the 1950s. Classification of ignitable liquids has been updated to include many new categories due to developments in the petroleum industry. Techniques such as steam or vacuum distillation and gas chromatography (GC) with flame ionization detection that may have been considered acceptable—even a benchmark—40 years ago, are nowadays generally disfavored, to the extent that their implementation may almost be considered as ignorance in the field. The advent of readily available mass spectrometric techniques has revolutionized the field of fire debris analysis, increasing the degree of sensitivity and discrimination possible considerably. Multi‐dimensional GC—particularly GC × GC—while not yet widely applied, is rapidly gaining recognition as an important technique. This comprehensive review focuses on techniques and practices used in fire investigation, from scene investigation to analysis.

Development of a GC‐MS Method for the Simultaneous Analysis of Latent Fingerprint Components

ABSTRACT: Latent fingerprint residue is a complex mixture of organic and inorganic compounds. A full understanding of the composition of this mixture and how it changes after deposition is lacking. Three solvent systems were compared for the simultaneous extraction and derivatization with ethyl chloroformate of selected amino and fatty acids from a nonporous substrate (Mylar®) for subsequent analysis by gas chromatography‐mass spectrometry. A solvent system comprised of sodium hydroxide, ethanol, and pyridine was found to be the most effective. This method was applied to the analysis of latent fingerprint residue deposited on Mylar® and preliminary data are presented. Twelve amino acids (e.g., serine, glycine, and aspartic acid) and 10 fatty acids (e.g., tetradecanoic, hexadecanoic, and octadecanoic acids) were identified. The potential application of this method to further the understanding of latent fingerprint chemistry has been demonstrated.

Temperature sensing using reversible thermochromic polymeric films

Temperature sensing membranes using Nafion® as the polymeric support matrix have been prepared incorporating common pH indicators and stains as visible indicators. These simple systems depend on the temperature sensitivity of the acid-base equilibria between the indicator and the acidic Nafion®. The films are able to sense temperature change through a change in film colour resulting from the equilibrium shift between different forms of the indicating dye. The dyes (phenolphthalein, methylene blue, safranin-O and crystal violet) studied covered a temperature range from 4 to 70 °C. © 2003 Elsevier Science B.V. All rights reserved.

Analysis of amino acids in latent fingerprint residue by capillary electrophoresis-mass spectrometry

The analysis of the chemical composition of fingerprints is important for the development and improvement of existing fingerprint enhancement techniques. This study demonstrates the first analysis of a latent fingerprint sample, using an optimized CE-MS method. In total 12 amino acids were detected in the fingerprint sample. MS/MS fragmentation was used to provide additional identity confirmation, for which eight of the twelve detected amino acids generated confirmatory product ions. Nine amino acids were quantified and their relative abundances were consistent with previous studies with serine and glycine being the most abundant. The successful detection of amino acids from latent fingerprints demonstrates that CE-MS is a potential future technique for further study of such compounds in fingerprint samples.

Polymeric matrices for immobilising zinc tetraphenylporphyrin in absorbance based gas sensors

Zinc tetraphenylporphyrin (ZnTPP) was incorporated in six silicone elastomers and three thermoplastics. The stability of ZnTPP in these membranes on storage under ambient light and in the dark over 35 days period was measured using absorption spectroscopy. The characteristic Soret band absorbance of ZnTPP in all the polymeric membranes stored under ambient light decreased, with the absorbance of ZnTPP in silicone membranes was scarcely measurable after 14 days. However, when stored in the dark, the rate of decrease in the Soret band absorbance of ZnTPP within these membranes appears to be dependent on the concentration of ZnTPP incorporated in them. Possible explanations for this behaviour are discussed. Ethyl cellulose (EC) and poly(vinyl chloride) (PVC) yielded active membranes with little or no change in their spectral characteristics on storage in the dark. Addition of diethyl phthalate to both thermoplastics reduced response and reversal times of the membranes when exposed to ammonia (NH3) gas (EC, <120 s; PVC, <10 s). The response characteristics of optimised sensing membranes of PVC exposed to ammonia gas were measured. These membranes responded to ammonia gas in less than 10 s and are capable of detecting ammonia gas at levels less than 0.5 mg m−3; however, these membranes were also found to be sensitive to relative humidity.

A specific case in the classification of woods by FTIR and chemometric: discrimination of Fagales from Malpighiales

Fourier transform infrared (FTIR) spectroscopic data was used to classify wood samples from nine species within the Fagales and Malpighiales using a range of multivariate statistical methods. Taxonomic classification of the family Fagaceae and Betulaceae from Angiosperm Phylogenetic System Classification (APG II System) was successfully performed using supervised pattern recognition techniques. A methodology for wood sample discrimination was developed using both sapwood and heartwood samples. Ten and eight biomarkers emerged from the dataset to discriminate order and family, respectively. In the species studied FTIR in combination with multivariate analysis highlighted significant chemical differences in hemicelluloses, cellulose and guaiacyl (lignin) and shows promise as a suitable approach for wood sample classification.

Chemometric Study on the Forensic Discrimination of Soil Types Using Their Infrared Spectral Characteristics

Soil has been utilized in criminal investigations for some time because of its prevalence and transferability. It is usually the physical characteristics that are studied; however, the research carried out here aims to make use of the chemical profile of soil samples. The research we are presenting in this work used sieved (2 mm) soil samples taken from the top soil layer (about 10 cm) that were then analyzed using mid-infrared spectroscopy. The spectra obtained were pretreated and then input into two chemometric classification tools: nonlinear iterative partial least squares followed by linear discriminant analysis (NIPALS-LDA) and partial least squares discriminant analysis (PLS-DA). The models produced show that it is possible to discriminate between soil samples from different land use types and both approaches are comparable in performance. NIPALS-LDA performs much better than PLS-DA in classifying samples to location.

Enhancement of Microcrystalline Identification of γ-Hydroxybutyrate*

Abstract: An enhancement of the microcrystalline test for the detection of γ‐hydroxybutyrate (GHB) is described. The original test used a silver/copper reagent which consisted of 0.1 g of silver nitrate and 0.1 g of copper nitrate in 10 mL water. The enhanced test utilizes lanthanum nitrate in place of copper nitrate. A detection limit of 0.5 mg/mL was achieved and the visual discrimination was improved because of larger sized crystals. Transient crystals were observed between 0.1 and 0.4 mg/mL. Silver nitrate alone appeared to be suitable for GHB detection but was not specific as other hydroxyl acids, such as glycolic acid, produced a similar crystal pattern. Tests conducted on chemical precursors of GHB and substances with similar biological activity highlight the specificity of the enhanced test. The reagent is therefore selective and sensitive for GHB in aqueous solutions. However, in beverage testing, crystal formation appeared to be inhibited for some drinks. Citric acid was identified as a possible interference depending on its concentration relative to GHB.

Application of chemometric analysis to infrared spectroscopy for the identification of wood origin

In this study, the chemical characteristics of wood are used for plant taxonomic classification based on the current Angiosperm Phylogeny Group classification (APG III System) for the division, class and subclass of woody plants. Infrared spectra contain information about the molecular structure and intermolecular interactions among the components in wood, but the understanding of this information requires multivariate techniques for the analysis of highly dense data sets. This article is written with the purposes of specifying the chemical differences among taxonomic groups and predicting the taxa of unknown samples with a mathematical model. Principal component analysis, t test, stepwise discriminant analysis and linear discriminant analysis were some of the multivariate techniques chosen. A procedure to determine the division, class, subclass and order of unknown samples was built with promising implications for future applications of Fourier transform infrared spectroscopy in wood taxonomy classification.