A colorimetric paper-based optode sensor for highly sensitive and selective determination of thiocyanate in urine sample using cobalt porphyrin derivative

Surface-engineered natural fibers: Emerging alternative substrates for chemical sensor applications: A review

Natural fiber has become one of the most widely used alternative materials for chemical sensor fabrication due to its advantages, such as biocompatibility, flexibility, and self-microfluidic properties. Enhanced natural fiber surface has been used as a substrate in colorimetric and electrochemical sensors. This review focuses on improving the natural fiber properties for preparation as a substrate for chemical sensors. Various methods for natural fiber extraction are discussed and compared. Bleaching and decolorization is important for preparation of colorimetric sensors, while carbonization and nanoparticle doping are favorable for increasing their electrical conductivity for electrochemical sensor fabrication. Also, example fabrications and applications of natural fiber-based chemical sensors for chemical and biomarker detection are discussed. The selectivity of the sensors can be introduced and improved by surface modification of natural fiber, such as enzyme immobilization and biorecognition element functionalization, illustrating the adaptability of natural fiber as a smart sensing device, e.g., wearable and portable sensors. Ultimately, the high performances of natural fiber-based chemical sensors indicate the potential uses of natural fiber as a renewable and eco-friendly substrate material in the field of chemical sensors and biosensors for clinical diagnosis and environmental monitoring.

Design a Friendly Nanoscale Chemical Sensor Based on Gold Nanoclusters for Detecting Thiocyanate Ions in Food Industry Applications

The surfactant cetyltrimethylammonium bromide (CTAB) induces the aggregation of gold nanoclusters (GNCs), leading to the development of a proposed fluorometric technique for detecting thiocyanate (SCN-) ions based on an anti-aggregation mechanism. This approach is straightforward to execute, highly sensitive, and selective. A significant quenching effect occurs in fluorescence upon using the aggregation agent CTAB in GNCs synthesis, resulting in a transition from intense red fluorescence to dim red. The decrease in fluorescence intensity of GNCs in the presence of CTAB is caused by the mechanism of fluorescence quenching mediated by aggregation. As the levels of SCN- rise, the fluorescence of CTAB-GNCs increases; this may be detected using spectrofluorometry or by visually inspecting under UV irradiation. The recovery of red fluorescence of CTAB-GNCs in the presence of SCN- enables the precise and discerning identification of SCN- within the concentration range of 2.86-140 nM. The minimum detectable concentration of the SCN- ions was 1 nM. The selectivity of CTAB-GNCs towards SCN- ions was investigated compared to other ions, and it was demonstrated that CTAB-GNCs exhibit exceptional selectivity. Furthermore, we believe that CTAB-GNCs have novel possibilities as favorable sensor candidates for various industrial applications. Our detection technique was validated by analyzing SCN- ions in milk samples, which yielded promising results.

Application of Paper-Based Microfluidic Analytical Devices (µPAD) in Forensic and Clinical Toxicology: A Review

The need for providing rapid and, possibly, on-the-spot analytical results in the case of intoxication has prompted researchers to develop rapid, sensitive, and cost-effective methods and analytical devices suitable for use in nonspecialized laboratories and at the point of need (PON). In recent years, the technology of paper-based microfluidic analytical devices (μPADs) has undergone rapid development and now provides a feasible, low-cost alternative to traditional rapid tests for detecting harmful compounds. In fact, µPADs have been developed to detect toxic molecules (arsenic, cyanide, ethanol, and nitrite), drugs, and drugs of abuse (benzodiazepines, cathinones, cocaine, fentanyl, ketamine, MDMA, morphine, synthetic cannabinoids, tetrahydrocannabinol, and xylazine), and also psychoactive substances used for drug-facilitated crimes (flunitrazepam, gamma-hydroxybutyric acid (GHB), ketamine, metamizole, midazolam, and scopolamine). The present report critically evaluates the recent developments in paper-based devices, particularly in detection methods, and how these new analytical tools have been tested in forensic and clinical toxicology, also including future perspectives on their application, such as multisensing paper-based devices, microfluidic paper-based separation, and wearable paper-based sensors.

Trends in Paper-Based Sensing Devices for Clinical and Environmental Monitoring

Environmental toxic pollutants and pathogens that enter the ecosystem are major global issues. Detection of these toxic chemicals/pollutants and the diagnosis of a disease is a first step in efficiently controlling their contamination and spread, respectively. Various analytical techniques are available to detect and determine toxic chemicals/pathogens, including liquid chromatography, HPLC, mass spectroscopy, and enzyme-linked immunosorbent assays. However, these sensing strategies have some drawbacks such as tedious sample pretreatment and preparation, the requirement for skilled technicians, and dependence on large laboratory-based instruments. Alternatively, biosensors, especially paper-based sensors, could be used extensively and are a cost-effective alternative to conventional laboratory testing. They can improve accessibility to testing to identify chemicals and pollutants, especially in developing countries. Due to its low cost, abundance, easy disposal (by incineration, for example) and biocompatible nature, paper is considered a versatile material for the development of environmentally friendly electrochemical/optical (bio) sensor devices. This review presents an overview of sensing platforms constructed from paper, pointing out the main merits and demerits of paper-based sensing systems, their fabrication techniques, and the different optical/electrochemical detection techniques that they exploit.

Novel (E)−2-((1-(thiophen-2-yl)ethylidene)-amino) phenol Manganese(II) as an Ionophore Based on Thiocyanate-Selective Electrodes and Its Applications

Novel highly selective potentiometric sensor based on aquadichloro(E)−2-((1-(thiophen-2-yl)ethylidene)-amino)phenol manganese(II)trihydrate as an anion carrier. The thiocayanate electrode displayed a very high selectivity compared with others inorganic anions. Different sensors with plasticized PVC membranes have been investigated. The sensors construction containing different amounts of ionophore with and without additives. The pH over 3.5–6.5 range has been studied. Optimized membrane electrode included 66 mg PVC, 132 mg o-nitrophenyloctylether, 10 mol % tetrakis(trifluoromethyl)phenyl borate and 2% [Mn(C12H11NOS)(Cl2)(H2O)]· 3H2O. The optimized sensors exhibit Nernstian response for thiocyanate through a linear concentration ranging from (5 × 10−8 to 9.06 × 10−1 M) with a detection limit of 3 × 10−8 M and a slope of −57.7 mV decade−1, the measurement carried out in acetate buffer pH 4.7. The response time of electrode <10 s and the lifetime of the sensor more than 6 weeks. The proposed electrode was effectively utilized to estimation of thiocyanate in saliva sample, the results revealed a valid agreement with reference colorimetric method.

Synthesis of New Cobalt(III) Meso-Porphyrin Complex, Photochemical, X-ray Diffraction, and Electrical Properties for Photovoltaic Cells

The present work describes the preparation and characterization of a new cobalt(III) porphyrin coordination compound named (chlorido)(nicotinoylchloride)[meso-tetra(para-chlorophenyl)porphyrinato]cobalt(III) dichloromethane monosolvate with the formula [Co^III(TClPP)Cl(NTC)]·CH₂Cl₂ (4). The single-crystal X-ray molecular structure of 4 shows very important ruffling and waving distortions of the porphyrin macrocycle. The Soret and Q absorption bands of 4 are very red-shifted as a consequence of the very distorted porphyrin core. This coordination compound was also studied by fluorescence and cyclic voltammetry. The efficiency of our four porphyrinic compounds-the H₂TClPP (1) free-base porphyrin, the [Co^II(TClPP)] (2) and [Co^III(TClPP)Cl] (3) starting materials, and the new Co(III) metalloporphyrin [Co^III(TClPP)Cl(NTC)]·CH₂Cl₂ (4)-as catalysts in the photochemical degradation was tested on malachite green (MG) dye. The current voltage of complexes 3 and 4 was also studied. Electrical parameters, including the saturation current density (J_s) and barrier height (ϕ_b), were measured.

RGB color analysis of formaldehyde in vegetables based on DNA functionalized gold nanoparticles and triplex DNA

A highly sensitive and selective RGB color analysis for the detection of formaldehyde (FA) was developed by using a DNA functionalized gold nanoparticle (AuNPs-DNA) probe. When complementary oligonucleotides (oligo 2 and oligo 3) and a silver ion (Ag⁺) were added to the AuNPs-DNA solution, triplex DNA was formed, resulting in the aggregation of AuNPs, and accompanied by a solution color change from red to purple. With the addition of formaldehyde, it reacted with Ag⁺, decreased the stability of triplex DNA between AuNPs-DNA, induced the dispersion of AuNPs, and the color of AuNPs recovered to red. Therefore, the formaldehyde concentration could be estimated with the RGB (red, green, blue) values of the AuNP solution by using a smartphone application (APP). The R value of the system was proportional to the concentration of formaldehyde within the range of 0.23-4.50 mg L^-1, with a detection limit of 0.14 mg L^-1. The method has been successfully applied to detect the residues of formaldehyde in vegetable samples and has the potential of the on-site determination of formaldehyde.

Machine learning and chemometrics for electrochemical sensors: moving forward to the future of analytical chemistry

Electrochemical sensors and biosensors have been successfully used in a wide range of applications, but systematic optimization and nonlinear relationships have been compromised for electrode fabrication and data analysis. Machine learning and experimental designs are chemometric tools that have been proved to be useful in method development and data analysis. This minireview summarizes recent applications of machine learning and experimental designs in electroanalytical chemistry. First, experimental designs, e.g., full factorial, central composite, and Box-Behnken are discussed as systematic approaches to optimize electrode fabrication to consider the effects from individual variables and their interactions. Then, the principles of machine learning algorithms, including linear and logistic regressions, neural network, and support vector machine, are introduced. These machine learning models have been implemented to extract complex relationships between chemical structures and their electrochemical properties and to analyze complicated electrochemical data to improve calibration and analyte classification, such as in electronic tongues. Lastly, the future of machine learning and experimental designs in electrochemical sensors is outlined. These chemometric strategies will accelerate the development and enhance the performance of electrochemical devices for point-of-care diagnostics and commercialization.