Kinetics, Thermodynamics, and Mechanistic Studies of Arsenic Removal Utilizing Natural Soil as Adsorbent.

The contamination of water sources with the heavy metal contaminant arsenic (As) causes substantial risks to humans, animals, and other living organisms. Therefore, the introduction of methods for the removal of As is important. The present study aimed to investigate the adsorption model and mechanism of As removal utilizing natural soil adsorbents. The batch adsorption technique was used to analyze the impacts of various parameters such as contact time, initial As concentration, pH, and temperature. Adsorption mechanisms were studied through adsorption kinetic, isotherm, and thermodynamic models. The batch adsorption study findings indicate that the optimal conditions for maximum As removal were achieved by application of 2.2 g of adsorbents in 50 µg/L of As solution for 60 min of contact time at a pH of 5.5 ± 0.5 and a temperature of 40 °C. The highest removal efficiency was achieved when red soil was employed as the adsorbent. The kinetic, isotherm, and thermodynamic models revealed that As adsorption was a chemisorptive, nonspontaneous, and endothermic process.

Detection and discrimination of sedative-hypnotics in spiked beverage dry residues using attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy combined with chemometrics.

Drugs-facilitated crimes (DFCs) involve the incapacitation of victims under the influence of drugs. Conventionally, a drug administration act is often determined through the examination of biological samples; however, dry residues from any surface, such as drinking glass if related to a DFC could be a potential source of evidence. This study was aimed to establish an attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy coupled with chemometrics for the determination of spiked sedative-hypnotics from dry residues of a drug-spiked beverage. In this study, four sedative-hypnotics, namely diazepam, ketamine, nimetazepam, and xylazine were examined using ATR-FTIR spectroscopy. Subsequently, the ATR-FTIR profiles were compared and decomposed by principal component analysis (PCA) followed by linear discriminant analysis (LDA) for their detection and discrimination. Visual comparison of ATR-FTIR profiles revealed distinct spectra among the tested drugs. An initial unsupervised exploratory PCA model indicated the separation of four main sedative-hypnotics clusters, and the proposed PCA score-LDA model had allowed for a 100% accurate classification. Discrimination of sedative-hypnotics from a dry beverage previously spiked with these drugs was also possible upon an additional extraction procedure. In conclusion, ATR-FTIR coupled with PCA score-LDA model was useful in detecting and discriminating sedative-hypnotics, including those that had been previously spiked into a beverage.

Vortex-assisted dispersive liquid-liquid microextraction-gas chromatography (VADLLME-GC) determination of residual ketamine, nimetazepam, and xylazine from drug-spiked beverages appearing in liquid, droplet, and dry forms.

Presently, investigations of drug-facilitated crimes (DFCs) rely on the detection of substances extracted from biological samples following intake by the victim. However, such detection requires rapid sampling and analysis prior to metabolism and elimination of the drugs from the body. In cases of suspected DFCs, drug-spiked beverage samples, whether in liquid, droplet, or even dried form, can be tested for the presence of spike drugs and used as evidence for the occurrence of DFCs. This study aimed to quantitatively determine three sedative-hypnotics (ketamine, nimetazepam, and xylazine) from drug-spiked beverages using a vortex-assisted dispersive liquid-liquid microextraction-gas chromatography (VADLLME-GC) approach. In this study, a GC method was first developed and validated, followed by the optimization of the VADLLME protocol, which was then applied to quantify the target substances in simulated forensic case scenarios. The developed GC method was selective, sensitive (limit of detection: 0.08 µg/ml [ketamine]; 0.16 µg/ml [nimetazepam]; 0.08 µg/ml [xylazine]), linear (R2 > 0.99), precise (%RSD <7.2%), and accurate (% recovery: 92.8%-103.5%). Higher recoveries were achieved for the three drugs from beverage samples in liquid form (51%-97%) as compared to droplet (48%-96%) and dried (44%-93%) residues. The recovery was not hindered by very low volumes of spiked beverage and dried residues. In conclusion, the developed VADLLME-GC method successfully recovered ketamine, nimetazepam, and xylazine from spiked beverages that are likely to be encountered during forensic investigation of DFCs.

Quick determination and discrimination of commercial hand sanitisers using attenuated total reflectance-Fourier transform infrared spectroscopy and chemometrics.

Due to the outbreak of the COVID-19 pandemic, practicing personal hygiene such as frequent hand sanitising has become a norm. The making of effective hand sanitiser products should follow the recommended formulations, but the high demand worldwide for such affordable products could have made them a candidate for counterfeiting, thus deserving forensic determination and profiling for source determination or supply chain tracing. In this study, determination and discrimination of hand sanitisers was carried out by employing attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy combined with chemometrics. Fifty commercially available hand sanitisers were obtained from the market and analysed. ATR-FTIR profiles of each sanitiser were compared and decomposed by principal component analysis (PCA) followed by linear discriminant analysis (LDA). Physical observation enabled the discrimination of seven samples based on their respective colours, the presence of beads and their colours, and the physical forms of formulations. Subsequently, eight distinct patterns were observed through visual comparison of ATR-FTIR profiles of the remaining 43 samples. An initial unsupervised exploratory PCA model indicated the separation of two main groups with ATR-FTIR profiles similar to those of ethanol and isopropanol, respectively. The PCA score-LDA model provided good predictions, with a 100% correct classification into eight different groups. In conclusion, this study demonstrated a quick determination and discrimination of hand sanitiser samples, allowing screening for any restricted components and sample-to-sample comparison.