Analytical & Bioanalytical Electrochemistry
Volume:15 Issue: 2, Feb 2023

Praseodymium is a rare earth element with various applications. The analysis of the levels of the compounds of this elements is very important and various instrumental techniques have been used for the determination of this element in various samples. Among the various techniques used to this end, electrochemical and optical sensors constitute a set of powerful tools for the determination of traces of Pr3+ ions in various samples and concentration ranges. The present review tends to provide an overview on the various potentiometric and optical sensors developed for this purpose, with a focus on the ionophores used and the composition of the sensing elements.

We report on the electrodeposition of a zinc-nickel alloy using a sulphate bath on mild steel (MS) substrate. The Hull cell experiment was used to optimize the bath composition and operating conditions. Sulphanilic acid (SA) was used as an additive for the coatings. The bath demonstrated an abnormal co-deposition with more zinc being deposited over nobler nickel. The effect of temperature and current density on the coating thickness, hardness, corrosion resistance, and weight % of Ni content in the coating was investigated. The corrosion behaviour of coated zinc-nickel alloy film in sodium chloride (wt.% 3.5) solution was investigated using potentiodynamic polarization and electrochemical impedance spectroscopic approaches. The nickel content in the coatings was determined through the colorimetric method and verified by the energy dispersive X-ray spectroscopy (EDX) technique. Atomic force microscopy (AFM) and Scanning electron microscopy (SEM) techniques were used to determine the surface roughness and surface topography, of the coatings. The results show that the zinc-nickel coatings had the highest corrosion resistance (0.213 mm y-1) at optimal current density (3A dm-2). Thus, due to their superior corrosion resistance Zn-Ni coatings have been largely used to protect the mild steel components in many industries including the automotive, military, and aerospace segments.

Herein, the modest co-precipitation mode was implemented to fabricate the cadmium oxide nanoparticles (CdO/NPs). The size, elemental composition and morphological characteristics of the synthesized nanomaterials were confirmed by XRD, EDX and SEM measurements. The designed CdO nanoparticles were exploited for the amplification followed by pre-treatment of carbon paste electrode (CdO/MPCPE) and successfully utilised for the quantification of serotonin (SE) in the presence of epinephrine (EP) at biological pH.  The tailored composite sensor proclaims the rapid electron transport behaviour which results in accretion in the oxidation peak signals for SE and EP. The several experimental conditions includes pH of supportive buffer, speed rate and concentration of analytes species were idealised. The CdO/MPCPE displays better sensing capability towards specific and simultaneous quantifications and lower detection limits were achieved. The customised electrode facilitates the high selectivity, excellent electrocatalytic stability, and agreeable results for rapid diagnosis of identical bioactive entities.

Potentiodynamic polarization (PDP) and electrochemical impedance spectroscopy (EIS) techniques were used to examine the inhibitory effect of omeprazole (OMP) on the corrosive behavior of Al-Mg-Si alloy in 0.5 M H2SO4. SEM/EDS microscopy methods and X-ray diffraction (XRD) analysis were utilized to examine the surface morphology. According to the findings, OMP acted flawlessly as an inhibitor of corrosion for an Al-Mg-Si alloy in 0.5 M H2SO4 at 298 K. The effect of temperature on inhibition efficiency was also discussed. Moreover, the experimental results suggest that OMP is an effective inhibitor, with a maximum inhibition efficiency of 90.5% at a concentration of 1.5 g/L, and the potentiodynamic polarization curves show that it is a mixed-type inhibitor. Electrochemical impedance spectroscopy discovered that an inhibitory adsorption film was being formed on the surface of the Al-Mg-Si alloy, and that this adsorption isotherm model is being followed. Thermodynamic activation parameters have been identified and discussed.

Inactivation of water-soluble redox proteins and enzymes is often encountered in many biological systems under physiological conditions. In electrochemical experiments, if the initial redox form of a given water-soluble redox protein is engaged at the same time in an electrochemical transformation on the working electrode and in an irreversible chemical reaction, then the voltammetric outputs might show quite specific behavior due to the simultaneous interplay of electron transfer step and the chemical reaction. In this work, we present for the first time theoretical results of such a model applicable to the electrochemistry of hydrophilic redox proteins under conditions of square-wave voltammetry. We present the readers a large tabular overview of a series of voltammetric patterns of this electrode mechanism calculated at different rates of electron transfer step and different kinetics of chemical step. Moreover, in the work we give hints to apply suitable methodology to recognize this mechanism under conditions of square-wave voltammetry, while giving directions on how to assess the kinetics of both steps involved in this mechanism. The results elaborated in this work should be of help to experimentalists working in enzymatic voltammetry.

The quantitative structure-property relationship (QSPR) method has been used for the prediction of carbonate potentiometric selectivity of plasticized polymeric membrane sensors. The variable selection tools of genetic algorithm (GA) combined with the multiple linear regressions (MLR) as linear and support vector machine (SVM) as nonlinear regression methods have been used. The K-means clustering method has been used for dividing the data set into the training set and test set. The validation of the models was done by the internal cross-validation and external test set. The results showed that the GA-SVM was a very accurate method in predicting of carbonate potentiometric selectivity with high correlation coefficients of 0.983 and 0.965 for the training and test sets. The results of this study and the interpretation of entered descriptors in the model can help to design new selective ligands.