We report on amperometric solid-contact potassium-selective electrodes based on catalytically synthesized Prussian Blue nanoparticles. Both the films and nanoparticles are able to generate amperometric response in flow-injection mode under constant potential. However, nanoparticles provide higher sensitivity than the films. Moreover, the intrinsic permeability of Prussian blue for potassium ions allows for selective detection of potassium in comparison to sodium even without ion-selective membrane. The results of Electrochemical impedance spectroscopy were used to manage the sensitivity by controlling the charge transfer resistance for ion-selective membranes of different density. By performing measurements in Bis-Tris as a carrier buffer containing no interfering cations an additional increase in selectivity was enabled. The record selectivity coefficient logK _Na⁺_/K⁺ is -2.7 for amperometric flow-injection mode was achieved. The obtained results indicate the prospects for analysis of biological fluids since Na⁺/K⁺ ratio is approximately 20-40.

In this work, an amperometric biosensor for lactate determination based on a Sonogel-Carbon transducer has been developed and evaluated using the lactate oxidase enzyme coated with a multipolymer layer as a bioreceptor. The biosensor obtained had adequate sensitivity (4.16 x 10^-8 A mM^-1) and a wide linear working range (0.2-20 mM) that allowed the determination of lactate at high concentrations without showing enzyme saturation phenomena. The selectivity of the biosensor was also verified using interferents commonly observed in physiological samples. Moreover, a microfluidic cell was designed and fabricated to allow the determination of lactate with the proposed biosensor in a continuous regime. In the end, the viability of the biosensor was tested with the proposed flow system using synthetic samples, obtaining excellent results.

In this work, germanene and its derivatives (Ge-H, Ge-CH₃, Ge-C₃-CN) were explored as competitive immunoassays for the direct detection of gut-derived metabolites, kynurenic acid (KA) and quinolinic acid (QA) using disposable screen-printed carbon electrodes via impedance. The competition occurs between the free KA/QA standards and the BSA-conjugated antigens for a fixed amount of primary antibody binding sites. As a result, this affects the charge transfer resistance (R_ct) of the [Fe(CN)₆]^3-/4- redox couple at the electrode surface. Hence, the impedimetric signal measured due to the change in R_ct will be correlated to the KA and QA presence and concentration.

In this work, a “green” electrochemical paper-based device (ePAD) for the voltammetric determination of Tl(I) is described. A mini voltammetric cell was patterned on chromatographic paper using screen-printing to deposit three carbon electrodes and plotting with a hydrophobic ink to from a circular assay zone. The sample was added to the assay zone (which was pre-loaded with Bi(III)) and Tl(I) is quantified by anodic stripping voltammetry (ASV). The experimental conditions and the potential interferences were studied. The limit of detection was at the low μg L^-1 level, indicating that these devices can serve successfully as fit-for-purpose disposable voltammetric sensors for Tl(I).

The development of electrochemical sensors with high sensitivity for the simultaneous detection of ascorbic acid (AA), dopamine (DA) and uric acid (UA) is urgently desirable in clinical medicine. However, the challenge lies in achieving simultaneous detection due to their closely oxidation potentials. In this work, we present the synthesis of a composite material comprised of in-situ grown TiO₂ nanowires (NWs) on a Ti₃C₂T_x substrate (Ti₃C₂T_x/TiO₂ NWs) through a facile alkali process. After modifying a glassy carbon electrode (GCE) with Ti₃C₂T_x/TiO₂ NWs (Ti₃C₂T_x/TiO₂ NWs/GCE), it showed excellent electrocatalytic activity for the simultaneous detection of AA/DA/UA by regulating the surface functional groups of Ti₃C₂T_x. Remarkably, the Ti₃C₂T_x/TiO₂ NWs/GCE enabled simultaneous detection of AA in the range of 300-1800 μM, DA in the range of 2-33 μM, and UA in the range of 2-33 μM. The limits of detection (LODs) for AA, DA, and UA were estimated as 66.07 μM, 0.023 μM, and 0.011 μM, respectively. The proposed Ti₃C₂T_x/TiO₂NWs/GCE demonstrated good stability, high selectivity, and reliable reproducibility, making it a promising electrochemical sensor for the detection of AA, DA, and UA. This work offers a new perspective for human health monitoring, paving the way for advancements in this field.

Smart, ultra-scaled, always-on wearable, and implantable (WI) sensors are an exciting frontier in personalized medicine. These sensors integrate sensing and actuation capabilities, enabling real-time analyte detection for on-demand drug delivery, akin to a biological organ. The microneedle (MN)-based patch serves as a critical novel interface element in this system. It is inexpensive, minimally invasive, and safe, showing promise in glycemic management and insulin therapy in laboratory and animal studies. However, the current design of MNs relies primarily on empirical approaches, with significant challenges. These challenges include potential diffusion delays that may impede time-critical drug intervention and an iterative design process lacking a clear understanding of the trade-off between response time and limits of detection. In this paper, we introduce the first predictive framework for MN sensors, based on physical scaling laws and biomimetic concepts. Our framework is supported by experimental and numerical validations, establishing analytical scaling relationships that capture the fundamental workings of hollow and porous-swellable MN sensors. It quantifies essential performance metrics like "response time (RT)" and "limit of detection (LOD)" while assessing trade-offs associated with various geometrical and physical parameters of the MN technology. As a result, our model provides a universal framework for interpreting/integrating experimental findings reported by laboratories worldwide. By leveraging this predictive framework, researchers can advance the development and optimization of MN sensors, leading to improved performance and expanded applications in the field of wearable and implantable technologies.

Potentiometric sensors, known as ion-selective electrodes, are widely used for measuring ion concentrations in aqueous solutions [1] due to their simplicity, portability, cost-effectiveness, and accuracy. Among the different types of ion-selective electrodes, those with plasticized polymeric membranes have gained significant attention due to their adjustable analytical performance such as selectivity and sensitivity by modifying the active substance, ion-exchanger, solvent-plasticizer and, most important, lipophilic ligands, or ionophores.

Discovering novel and effective ionophores for different ions is a complex and time-consuming process involving guesses about ionophore structure, synthetic availability assessment, synthesis, purification, preparation of sensor membranes, and electrochemical characterization. Despite these efforts, the resulting sensors may not meet the desired characteristics for practical analytical applications.

Recent studies have demonstrated the effectiveness of the Quantitative Structure-Property Relationship (QSPR) approach in predicting sensor properties based on ionophore structure [2]. In this approach, molecular descriptors representing structural properties are related to the property of interest through mathematical modeling. This study aims to extend the application of QSPR to predict the sensitivity of novel ionophores towards three heavy metal ions: Cu²⁺, Cd²⁺, and Pb²⁺, in potentiometric sensors. The study focuses on four new diphenylphosphoryl acetamides ionophores, which have shown increased extraction ability towards metal ions. The reasonable correspondence was found between model predictions and experimental sensitivity values.

References:

1. Zdrachek, E., Bakker, E. Potentiometric Sensing. Anal. Chem. 2021, 93(1), 72-102.
2. Vladimirova, N., Polukeev, V., Ashina, J., Babain, V., Legin, A., Kirsanov, D. Prediction of Carbonate Selectivity of PVC-Plasticized Sensor Membranes with Newly Synthesized Ionophores through QSPR Modeling. Chemosensors 2022, 10, 43.

In this work, we report the development of a technique to fabricate a screen-printed electrode (SPE) and its applications for uric acid sensing. The SPE was fabricated using a printing technique using an office printer printed on a photo paper substrate. Particularly, the conductive ink used for printing the working electrode (WE) and counter electrode (CE) consisted of graphene oxide (GO) and gold nanorod (AuNR) material. While the reference electrode (RE) was made by applying the conductive silver paste to the fabricated SPE. The electrochemical measurement of uric acid solution using fabricated SPE GO/AuNR provides a higher signal than the commercially available SPE. The electroanalytical performance of the fabricated SPE based on GO/AuNR toward the measurement of uric acid solution exhibited a linear range of 0.8−200 μM, a detection limit of 0.5 μM, a quantitation limit of 1.0 μM, outstanding repeatability (% relative standard deviation) of 4.885 % as well as good selectivity with ascorbic acid, dopamine, glucose, urea, and sodium as interference. Furthermore, the fabricated SPE based on GO/AuNR was successfully employed for the determination of uric acid concentration in human urine samples using the standard addition approach.

Conjugated polymers (CPs) are an intriguing material to build fluorescent Cr₂O₇^2- sensors with excellent sensitivity but often lack specific recognition groups. In this study, several typical amino acids with N and O atom identifying groups were incorporated into fluorene and then six polyfluorene derivatives were synthesized using electrochemical polymerization. Compared to other cations and anions, all of these amino acid-functionalized polyfluorenes have good selectivity towards Cr₂O₇^2- and enable ultra-trace response with detection thresholds at pM or even fM level.

Urban industrial areas are often a matter of concern due to the emissions of air pollutants that may affect the air quality of the adjacent cities. The aerosol pollutants are monitored by governmental agencies that employ regulatory monitoring stations which are very accurate, but also very expensive, bulky, and maintenance demanding. For this reason, it often happens that the monitoring of the air quality in large areas are covered by few stations. This situation can lead to the building of air pollutant maps having a low spatio-temporal resolution. An appealing way to address this issue is represented by the Low-Cost miniaturized gas Sensors (LCS) employed in the Low-Cost air quality Monitors (LCM). Despite the various and unquestionable points of strength characterizing these devices, the scientific community has raised several warnings about the accuracy of their measurements and many caveats in their use. In this study, a new LCM model designed and implemented in our laboratories has been used to perform the measurements of the NO₂ and PM concentrations in the industrial area of Brindisi (Italy). The LCSs installed in the LCM used for this experiment are the NO2B43F for NO₂ measurements, and the SPS30 for particulate matter (PM) detection. Data gathered by the LCM have been compared with reference instrumentations for a rigorous analysis of the performance achievable through these low-cost technologies in this particular case.