Selective extraction and determination of Cr(VI) in food samples based on tandem electromembrane extraction followed by electrothermal atomic absorption spectrometry

A smartphone-based sensor for detection of iron and potassium in food and beverage samples

A novel approach for simultaneous detection of iron and potassium via a smartphone-based potentiometric method is proposed in this study. The screen printed electrodes were modified with carbon black nanomaterial and ion selective membrane including zinc (II) phtalocyanine as the ionophore. The developed Fe3+-selective electrode and K+-selective electrode exhibited detection limits of 1.0 × 10-6 M and 1.0 × 10-5 M for Fe3+ and K+ ions, respectively. The electrodes were used to simultaneously detect Fe3+ and K+ ions in apple juice, skim milk, soybean and coconut water samples with recovery values between 90%-100.5%, and validated against inductively coupled plasma-optical emission spectrometry. Due to the advantageous characteristics of the sensors and the portability of Near Field Communication potentiometer supported with a smartphone application, the proposed method offers sensitive and selective detection of iron and potassium ions in food and beverage samples at the point of need.

Chemical nature evolution of solid supports used in electromembrane extraction procedures: A comparative analysis based on metric tools

BACKGROUND

In recent decades, green chemistry has been focusing on the adaptation of different chemical methods towards environmental friendliness. Sample preparation procedures, which constitute a fundamental step in analytical methodology, have also been modified and implemented in this direction. In particular, electromembrane extraction (EME) procedures, which have traditionally used plastic supports, have been optimized towards greener approaches through the emergence of alternative materials. In this regard, biopolymer-based membranes (such as agarose or chitosan) have become versatile and very promising substitutes to perform these processes.

RESULTS

Different green metric tools (Analytical Eco-Scale, ComplexGAPI and AGREEprep have been applied to study the evolution of solid supports used in EME from nanostructured tissues and polymer inclusion membranes to agar films and chitosan flat membranes. The main goal is to evaluate the usage of these new biomaterials in the analytical procedure to quantify their environmental impact in the frame of Green Analytical Chemistry (GAC). In addition, both RGB model and BAGI metrics have been employed to study the sustainability of the whole procedure, including not only greenness, but also analytical performance and feasibility aspects. Results obtained after the performance of the mentioned metrics have demonstrated that the most efficient and environmentally friendly analytical methods are based on the use of chitosan supports. This improvement is mainly due to the chemical nature of this biopolymer as well as to the removal of organic solvents.

SIGNIFICANCE

This work highlights the advantages of biodegradable materials employment in EME procedures to achieve green analytical methodologies. These materials also contribute to raise the figure of merits regarding to the quantification parameters in a wide range of applications compared to classical supports employed in EME, thus enhancing sustainability of procedures.

Optical nanosensors based on noble metal nanoclusters for detecting food contaminants: A review

Food contaminants present a significant threat to public health. In response to escalating global concerns regarding food safety, there is a growing demand for straightforward, rapid, and sensitive detection technologies. Noble metal nanoclusters (NMNCs) have garnered considerable attention due to their superior attributes compared to other optical materials. These attributes include high catalytic activity, excellent biocompatibility, and outstanding photoluminescence properties. These features render NMNCs promising candidates for crafting nanosensors for food contaminant detection, offering the potential for the development of uncomplicated, swift, sensitive, user-friendly, and cost-effective detection approaches. This review investigates optical nanosensors based on NMNCs, including the synthesis methodologies of NMNCs, sensing strategies, and their applications in detecting food contaminants. Furthermore, it involves a comparative assessment of the applications of NMNCs in optical sensing and their performance. Ultimately, this paper imparts fresh perspectives on the forthcoming challenges. Hitherto, optical (particularly fluorescent) nanosensors founded on NMNCs have demonstrated exceptional sensing capabilities in the realm of food contaminant detection. To enhance sensing performance, future research should prioritize atomically precise NMNCs synthesis, augmentation of catalytic activity and optical properties, development of high-throughput and multimode sensing, integration of NMNCs with microfluidic devices, and the optimization of NMNCs storage, shelf life, and transportation conditions.

Machine learning integrated high quantum yield blue light carbon dots for real-time and on-site detection of Cr(VI) in groundwater and drinking water

The safety of groundwater and drinking water is directly related to the well-being of human beings and ecosystems. On-site monitoring and timely response to heavy metals in these water sources are crucial for water supply security. Fluorescent probes combined with machine learning technology have been applied to on-site detection of heavy metals. However, they were primarily focused on industrial-level detection and lacked the sensitivity required for detecting Cr(VI) in groundwater and drinking water. In this study, we developed an machine learning-integrated approach using high-quantum-yield (QY) N-doped blue-light carbon dots (N-BCDs) for instant detection of Cr(VI) in groundwater and drinking water. N-BCDs were synthesized within 3 min using a household microwave oven with citric acid and 1,2-diaminobenzene, resulting in a QY of approximately 90 %. The fluorescence of N-BCDs was quenched via the internal filter effect (IFE), enabling the detection of Cr(VI) within 1 min, with a detection limit of 0.1574 μg L-1 for Cr(VI) concentrations ranging from 0 to 60 μg L-1. We employed machine learning methods to determine Cr(VI) concentrations from simple shots, based on the red-green-blue (RGB) feature and Kmeans feature extraction. These features were input into four models (Ridge, XGB, SVR, and Linear), achieving a fitness of 95.2 %. Furthermore, the accuracies for Cr(VI) concentration identification in actual groundwater and drinking water were as high as 95.71 % and 96.81 %, respectively. Our work successfully extended the detection range of Cr(VI) to the μg level, significantly improving the practical applicability of the method and providing a new approach for on-site detection of Cr(VI) in groundwater and drinking water.

Using Multistage Energy Barrier of Heterojunctions in Improving Cr(VI) Detection

Detecting heavy metals in seawater is challenging due to the high salinity and complex composition, which cause strong interference. To address this issue, we propose using a multistage energy barrier as an electrochemical driver to generate electrochemical responses that can resist interference. The Ni-based heterojunction foams with different types of barriers were fabricated to detect Cr(VI), and the effects of the energy barriers on the electrochemical response were studied. The single-stage barrier can effectively drive the electrochemical response, and the multistage barrier is even more powerful in improving sensing performance. A prototype Ni/NiO/CeO2/Au/PANI foam with multistage barriers achieved a high sensitivity and recovery rate (93.63-104.79%) in detecting seawater while resisting interference. The use of multistage barriers as a driver to resist electrochemical interference is a promising approach.

Extraction performance of electromembrane extraction and liquid-phase microextraction in prototype equipment

In this comparative study, the performance of liquid-phase microextraction and electromembrane extraction in prototype equipment was evaluated for extraction of ninety basic substances from plasma. Using a commercial EME device based on conductive vials enabled a standardized and comprehensive comparison between the two methods. Extractions were performed from a pH-adjusted donor solution, across an organic liquid membrane immobilized in a porous polypropylene membrane, and into an acidic acceptor solution. In LPME, dodecyl acetate was used as the extraction solvent, while 2-nitrophenyl octyl ether was used for EME with an electric field applied across the system. To assess the extraction performance, extraction recovery plots and extraction time curves were constructed and analyzed. These plots provided insights into the efficiency and effectiveness of LPME and EME, allowing users to make better decisions about the most suitable method for a specific bioanalytical application. Both LPME and EME were effective for substances with 2.0 < log P < 4.0, with EME showing faster extraction kinetics. Small (200 µL) and large vials (600 µL) were compared, showing that smaller vials improved kinetics markedly in both techniques. Carrier-mediated extraction showed improved performance for analytes with log P < 2 in EME, however, with some limitations due to system instability. This is, to our knowledge, the first time LPME was performed in the commercial vial-based equipment. An evaluation of vial-based LPME investigating linearity, precision, accuracy, and matrix effects showed promising results. These findings contribute to a general understanding of the performance differences in vial-based LPME and EME.

Analytical Performance of Electromembranes as a Tool for Nanoconcentrations of Silver in Waters

Electromembranes increase the efficiency of metal transport in liquid-phase microextraction systems by applying an electric potential, which accelerates the transport. Nevertheless, to get high extraction percentages in short extraction times it is necessary to take into account a great variety of factors, and multivariate optimization techniques are the best alternative to determine the most influential variables and to optimize the extraction process. In this work, a fractional factorial design was applied to determine the most influential variables in the extraction of silver by electromembranes. Thus, the effect of tri-isobutylphosphine sulphide (Cyanex 471x) concentration in the organic solution, sodium thiosulphate concentration in the acceptor solution, nitrate concentration in the sample solution, extraction time, stirring rate and electric potential on the enrichment factor were studied. Once the most important variables were selected, a small composite design (Draper-Lin) was used to obtain their optimal values to maximize the enrichment factor. Under these conditions, an experimental enrichment factor of 49.91 ± 3.95 was achieved after 22 min. Finally, the effect of saline matrix on the enrichment factor was tested and the optimized system was successfully applied to analyse silver concentrations at ultratrace levels, within the range of 7-29 ng·L^-1 in different real seawater samples.

A facile fluorescence platform for chromium and ascorbic acid detection based on "on-off-on" strategy

In this paper, a facile and rapid fluorescence "on-off-on" strategy for the detection of chromium (Cr(VI)) and ascorbic acid (AA) was developed, which was based on the water-soluble carbon dots (CDs). The CDs was synthesized by a microwave-assisted treatment of L-tartaric acid, citric acid, and urea. The CDs have many advantages, such as high fluorescence quantum yield (20.5%) and good fluorescence stability. Based on inner filter effect (IFE) and static quenching, the fluorescence of the CDs can be quenched by Cr(VI) quickly; while the reduction of IFE and reducing action can make the fluorescence of the CDs recover by AA efficiently. Moreover, under the optimal experimental conditions, the CDs had a good detection performance for Cr(VI) in the range of 0.8 ∼ 189 µM with the limit of detection (LOD) of 0.16 µM. The linear detection for AA was ranged from 0.43 to 25.7 µM with a LOD of 0.1 µM. More importantly, the as-constructed fluorescence detecting platform was successfully applied for Cr(VI) and AA detection in the environmental samples and fruit samples, respectively. In addition, the application potential of the CDs in fluorescent films and anti-counterfeiting materials was further discussed in detail. This work will provide a novel idea for designing a portable sensor based on the CDs to quickly and sensitively detect Cr(VI) and AA.

Electromembrane extraction of nicotine in inhaled aerosols from tobacco cigarettes, electronic cigarettes, and heated tobacco products

Heated tobacco products and electronic cigarettes are considered as alternatives to traditional tobacco cigarettes. However, it is crucial to monitor and compare the nicotine concentration in inhaled aerosols from these tobacco products, owing to the addictive nature and adverse effects of nicotine on human health. This study aimed to provide an electromembrane extraction (EME) combined liquid chromatography method to extract and determine nicotine in different inhaled aerosols. EME showed high extraction efficiency, selectivity, and sample clean-up capability. Under the optimal parameters, the linear range for nicotine was 0.1-200 mg L-1 (r2 > 0.9998), and the limit of detection was 0.02 mg L-1. Good precision was obtained with the intra- and inter-day relative standard deviations of 2.2 % and 2.8 %, respectively. Repeatability was satisfactory (<7.7 %), and recoveries ranged from 81.0 % to 112.8 %. Finally, this method has been successfully used for the determination and comparison of nicotine in aerosols from these three tobacco products.

Toxic Metals in a Paddy Field System: A Review

The threat of toxic metals to food security and human health has become a high-priority issue in recent decades. As the world’s main food crop source, the safe cultivation of rice has been the focus of much research, particularly the restoration of toxic metals in paddy fields. Therefore, in this paper, we focus on the effects of toxic metals on rice, as well as the removal or repair methods of toxic metals in paddy fields. We also provide a detailed discussion of the sources and monitoring methods of toxic metals pollution, the current toxic metal removal, and remediation methods in paddy fields. Finally, several important research issues related to toxic metals in paddy field systems are proposed for future work. The review has an important guiding role for the future of heavy metal remediation in paddy fields, safe production of rice, green ecological fish culture, and human food security and health.