Prussian blue based impedimetric urea biosensor

Reagent-Free Lactate Detection Using Prussian Blue and Electropolymerized-Molecularly Imprinted Polymers-Based Electrochemical Biosensors

Sweat lactate, a promising biomarker for assessing physical performance and health conditions, calls for noninvasive, convenient, and affordable detection methods. This study leverages molecularly imprinted polymers (MIPs) as a synthetic biorecognition element for lactate detection due to their affordability and high stability. Traditional MIPs-based electrochemical sensors often require external redox probes such as ferricyanide/ferrocyanide in the solution to signal the binding between analytes and MIPs, which restricts their applicability. To address this, our study introduces an innovative approach utilizing a layer of Prussian blue (PB) nanoparticles as the internal redox probe on screen-printed carbon electrodes (SPCE), followed by a layer of electropolymerized MIP (eMIP) for molecular recognition, enabling reagent-free lactate detection. The real-time growth of eMIP and the processes of template elution and lactate rebinding were examined and validated using electrochemical surface plasmon resonance (EC-SPR) spectroscopy. The sensor's performance was thoroughly investigated using Differential Pulsed Voltammetry (DPV) and Electrochemical Impedance Spectroscopy (EIS) with samples spiked in 0.1 M KCl solution and artificial sweat. The developed sensors demonstrated a fast and selective response to lactate, detecting concentrations from 1 to 35 mM with a Limit of Detection (LOD) of 0.20 mM, defined by a signal-to-noise ratio of 3 in the DPV measurements. They also exhibited excellent reproducibility, reusability, and a shelf life of up to 10 months under ambient conditions. These eMIP/PB/SPCE-based lactate sensors show considerable potential as point-of-care (POC) devices for sweat lactate detection, and the technology could be adapted for reagent-free detection of a broad spectrum of molecules.

Urea-Self Powered Biosensors: A Predictive Evolutionary Model for Human Energy Harvesting

The objective of this study is to create a reliable predictive model for the electrochemical performance of self-powered biosensors that rely on urea-based biological energy sources. Specifically, this model focuses on the development of a human energy harvesting model based on the utilization of urea found in sweat, which will enable the development of self-powered biosensors. In the process, the potential of urea hydrolysis in the presence of a urease enzyme is employed as a bioreaction for self-powered biosensors. The enzymatic reaction yields a positive potential difference that can be harnessed to power biofuel cells (BFCs) and act as an energy source for biosensors. This process provides the energy required for self-powered biosensors as biofuel cells (BFCs). To this end, initially, the platinum electrodes are modified by multi-walled carbon nanotubes to increase their conductivity. After stabilizing the urease enzyme on the surface of the platinum electrode, the amount of electrical current produced in the process is measured. The optimal design of the experiments is performed based on the Taguchi method to investigate the effect of urea concentration, buffer concentration, and pH on the generated electrical current. A general equation is employed as a prediction model and its coefficients calculated using an evolutionary strategy. Also, the evaluation of effective parameters is performed based on error rates. The obtained results show that the established model predicts the electrical current in terms of urea concentration, buffer concentration, and pH with high accuracy.

Determination of urea, phosphate, and potassium in agricultural runoff waters using electrochemical impedance spectroscopy

Large-scale use of chemical fertilizers has resulted in the contamination of agricultural runoff waters by soil macronutrients NPK, whose detection is of significant interest. This work reports the determination of macronutrients in the form of urea (N), orthophosphate PO43- (P), and potassium K+ (K) in simulated agricultural runoff waters. Their solutions were prepared by extracting water-soluble constituents of soil. This 'base' solution contains high concentrations of various species, including Cl-, SO42-, NO3-, PO43-, Na+, K+, and NH4+ along with natural organic matter. Predetermined amounts of urea (4 to 22.5 ppm), PO43- (7 to 50 ppm), and potassium K+ (25 to 250 ppm) were added to the base simulated runoff water to prepare standard stock solutions. Using stainless steel working and counter electrodes, a small AC perturbation (±10 mV vs. OCP, vs. Ag/AgCl) was applied and the frequency response of the working electrode-solution interface was measured from 1 Hz to 1 MHz. The interface itself was modeled as a suitable equivalent electrical circuit, and the magnitudes of its components were fitted from experimental data using nonlinear regression. It is observed that PO43- concentration is a linear function of charge transfer resistance arising from redox reaction, K+ concentration is a quadratic function of double-layer capacitance arising from its higher mobility, and urea concentration can be correlated as a linear function of constant phase element arising from its polarization in the presence of an applied electric field. The sensor exhibits good sensitivity, repeatability, and excellent performance against interfering species. These preliminary results show significant potential for development of a real-time or on-site sensing device.

Controlled Silanization of Transparent Conductive Oxides as a Precursor of Molecular Recognition Systems

The search for new molecular recognition systems has become the goal of modern electrochemistry. Creating a matrix in which properties can be controlled to obtain a desired analytical signal is an essential part of creating such tools. The aim of this work was to modify the surface of electrodes based on transparent conductive oxides with the use of selected alkoxysilanes (3-aminopropyltrimethoxysilane, trimethoxy(propyl)silane, and trimethoxy(octyl)silane). Electrochemical impedance spectroscopy and cyclic voltammetry techniques, as well as contact angle measurements, were used to determine the properties of the obtained layers. Here, we prove that not only was the structure of alkoxysilanes taken into account but also the conditions of the modification process-reaction conditions (time and temperature), double alkoxysilane modification, and mono- and binary component modification. Our results enabled the identification of the parameters that are important to ensure the effectiveness of the modification process. Moreover, we confirmed that the selection of the correct alkoxysilane allows the surface properties of the electrode material to be controlled and, consequently, the charge transfer process at the electrode/solution interface, hence enabling the creation of selective molecular recognition systems.

Application of Prussian Blue in Electrochemical and Optical Sensing of Free Chlorine

In this paper, an electrochemical free chlorine (FCL) sensor was formed by modifying a fluorine-doped tin oxide-coated glass slide (glass|FTO) with a layer of Prussian blue (glass|FTO|PB). The glass|FTO|PB sensor exhibited a wide linear detection range from 1.7 to 99.2 μmol L^-1 of FCL with a sensitivity of ~0.8 µA cm^-2 μmol^-1 L and showed high selectivity for FCL. However, ClO3-, ClO4- and NO3- ions have induced only a negligible amperometric response that is highly beneficial for a real-life sample analysis as these ions are commonly found in chlorine-treated water. Moreover, in this work, optical absorption measurement-based investigations of partially reduced PB were carried out as a means to characterize PB catalytic activity towards FCL and to investigate the possibility of applying PB for the optical detection of FCL.