Conventional electrochemical sensors use voltammetric and amperometric methods with external power supply and modulation systems, which hinder the flexibility and application of the sensors. To avoid the use of an external power system and to minimize the number of electrochemical cell components, a self-powered electrochemical sensor (SPES) for hydrogen peroxide was investigated here. Iron phthalocyanine, an enzyme mimetic material, and Ni were used as a cathode catalyst and an anode material, respectively. The properties of the iron phthalocyanine catalyst modified by graphene nanoplatelets (GNPs) were investigated. Open circuit potential tests demonstrated the feasibility of this system. The GNP-modulated interface helped to solve the problems of aggregation and poor conductivity of iron phthalocyanine and allowed for the achievement of the best analytical characteristics of the self-powered H2O2 sensor with a low detection limit of 0.6 µM and significantly higher sensitivity of 0.198 A/(M·cm2) due to the enhanced electrochemical properties. The SPES demonstrated the best performance at pH 3.0 compared to pH 7.4 and 12.0. The sensor characteristics under the control of external variable load resistances are discussed and the cell showed the highest power density of 65.9 μW/cm2 with a 20 kOhm resistor. The practical applicability of this method was verified by the determination of H2O2 in blood serum.

This work compares the electroanalytical performance of two electroanalytical systems based on (1) the glassy carbon electrode (GCE), and (2) the electrified liquid-liquid interface (eLLI), for the detection of fluoroquinolone antibiotic-danofloxacin (DANO). Our aim was to define the optimal conditions to detect the chosen analyte with two employed systems, extract a number of electroanalytical parameters, study the mechanism of the charge transfer reactions (oxidation at GCE and ion transfer across the eLLI), and to provide physicochemical constants for DANO. Detection of the chosen analyte was also performed in the spiked milk samples. To the best of our knowledge, this is the first work that directly compares the electroanalytical parameters obtained with solid electrode (in this case GCE) and eLLI. We have found that for DANO the latter provides better electroanalytical parameters (lower LOD and LOQ) as well as good selectivity when the milk was analyzed.

This paper demonstrates, for the first time, the stability of synthetic diamond as a passive layer within neural implants. Leveraging the exceptional biocompatibility of intrinsic nanocrystalline diamond, a comprehensive review of material aging analysis in the context of in-vivo implants is provided. This work is based on electric impedance monitoring through the formulation of an analytical model that scrutinizes essential parameters such as the deposited metal resistivity, insulation between conductors, changes in electrode geometry, and leakage currents. The evolution of these parameters takes place over an equivalent period of approximately 10 years. The analytical model, focusing on a fractional capacitor, provides nuanced insights into the surface conductivity variation. A comparative study is performed between a classical polymer material (SU8) and synthetic diamond. Samples subjected to dynamic impedance analysis reveal distinctive patterns over time, characterized by their physical degradation. The results highlight the very high stability of diamond, suggesting promise for the electrode\'s enduring viability. To support this analysis, microscopic and optical measurements conclude the paper and confirm the high stability of diamond and its strong potential as a material for neural implants with long-life use.

Peripheral nerve stimulation (PNS) is an effective means to elicit sensation for rehabilitation of people with loss of a limb or limb function. While most current PNS paradigms deliver current through single electrode contacts to elicit each tactile percept, multi-contact extraneural electrodes offer the opportunity to deliver PNS with groups of contacts individually or simultaneously. Multi-contact PNS strategies could be advantageous in developing biomimetic PNS paradigms to recreate the natural neural activity during touch, because they may be able to selectively recruit multiple distinct neural populations. We used computational models and optimization approaches to develop a novel biomimetic PNS paradigm that uses interleaved multi-contact (IMC) PNS to approximate the critical neural coding properties underlying touch. The IMC paradigm combines field shaping, in which two contacts are active simultaneously, with pulse-by-pulse contact and parameter variations throughout the touch stimulus. We show in simulation that IMC PNS results in better neural code mimicry than single contact PNS created with the same optimization techniques, and that field steering via two-contact IMC PNS results in better neural code mimicry than one-contact IMC PNS. We also show that IMC PNS results in better neural code mimicry than existing PNS paradigms, including prior biomimetic PNS. Future clinical studies will determine if the IMC paradigm can improve the naturalness and usefulness of sensory feedback for those with neurological disorders.

UNASSIGNED: To use computational modeling to provide a complete and logical description of the electrical and thermal behavior during stereoelectroencephalography-guided (SEEG) radiofrequency thermo-coagulation (RF-TC).
UNASSIGNED: A coupled electrical-thermal model was used to obtain the temperature distributions in the tissue during RF-TC. The computer model was first validated by an ex vivo model based on liver fragments and later used to study the impact of three different factors on the coagulation zone size: 1) the difference in the tissue surrounding the electrode (gray/white matter), 2) the presence of a peri-electrode gap occupied by cerebrospinal fluid (CSF), and 3) the energy setting used (power-duration).
UNASSIGNED: The model built for the experimental validation was able to predict both the evolution of impedance and the short diameter of the coagulation zone (error < 0.01 mm) reasonably well but overestimated the long diameter by 2 - 3 mm. After adapting the model to clinical conditions, the simulation showed that: 1) Impedance roll-off limited the coagulation size but involved overheating (around 100 °C); 2) The type of tissue around the contacts (gray vs. white matter) had a moderate impact on the coagulation size (maximum difference 0.84 mm), and 3) the peri-electrode gap considerably altered the temperature distributions, avoided overheating, although the diameter of the coagulation zone was not very different from the no-gap case (<0.2 mm).
UNASSIGNED: This study showed that computer modeling, especially subject- and scenario-specific modeling, can be used to estimate in advance the electrical and thermal performance of the RF-TC in brain tissue.

As a new pollutant treatment technology, microbial fuel cell (MFC) has a broad prospect. In this article, the devices assembled using walnut shells are named biochar-microbial fuel cell (B-MFC), and the devices assembled using graphene are named graphene-microbial fuel cell (G-MFC). Under the condition of an external resistance of 1,000 Ω, the B-MFC with biochar as the electrode plate can generate a voltage of up to 75.26 mV. The maximum power density is 76.61 mW/m2, and the total internal resistance is 3,117.09 Ω. The removal efficiency of B-MFC for ammonia nitrogen (NH3-N), chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) was higher than that of G-MFC. The results of microbial analysis showed that there was more operational taxonomic unit (OTU) on the walnut shell biochar electrode plate. The final analysis of the two electrode materials using BET specific surface area testing method (BET) and scanning electron microscope (SEM) showed that the pore size of walnut shell biochar was smaller, the specific surface area was larger, and the pore distribution was smoother. The results show that using walnut shells to make electrode plates is an optional waste recycling method and an electrode plate with excellent development prospects.

The accelerating environmental impact of the textile industry, especially in water management, requires efficient wastewater treatment strategies. This study examines the effectiveness of various electrode pairs in the Electrocoagulation (EC) process for treating textile wastewater, focusing on removing of Total Suspended Solids (TSS), turbidity, Chemical Oxygen Demand (COD), and Total Organic Carbon (TOC). A comprehensive analysis was conducted using thirty-six electrode pair combinations, consisting of six materials: Aluminium (Al), Zinc (Zn), Carbon (C), Copper (Cu), Mild Steel (MS), and Stainless Steel (SS). The results demonstrated that different electrode pairs yielded varying removal efficiencies for various pollutants, with the highest efficiencies being 92.09% for COD (Al-C pair), 99.66% for TSS (Al-Cu pair), 99.17% for turbidity (Al-MS pair), and 70.99% for TOC (SS-SS pair). However, no single electrode pair excelled in removing all pollutant categories. To address this, three Multi-Criteria Decision Making (MCDM) methods such as TOPSIS, VIKOR, and PROMETHEE II were used to assess the most effective electrode pair. The results indicated that the Al-Zn combination was the most efficient, exhibiting high removal efficiencies for various pollutants (99.32% for TSS, 98.88% for turbidity, 68.62% for COD, and 57.96% for TOC). This study demonstrates that the EC process can effectively treat textile effluent and emphasizes the importance of selecting suitable electrode materials. Furthermore, pollutant removal was optimal with the Al-Zn electrode pair, offering a balanced and efficient approach to textile wastewater treatment. Thus, MCDM methods offer a robust framework for assessing and optimizing electrode selection, providing valuable insights for sustainable environmental management practices.

Rapid and reliable immunosensing is undoubtedly one of the priorities in the efficient management and combat against a pandemic, as society has experienced with the SARS-CoV-2 outbreak; simple and cost-effective sensing strategies are at the forefront of these efforts. In this regard, 2D-layered MXenes hold great potential for electrochemical biosensing due to their attractive physicochemical properties. Herein, we present a V2CTx MXene-based sensing layer as an integral part of a label-free immunosensor for sensitive and selective detection of the SARS-CoV-2 spike protein. The sensor was fabricated on a supporting screen-printed carbon electrode using Nafion as an immobilizing agent for MXene and glutaraldehyde, the latter enabling effective binding of protein A for further site-oriented immobilization of anti-SARS-CoV-2 antibodies. A thorough structural analysis of the sensor architecture was carried out, and several key parameters affecting the fabrication and analytical performance of the immunosensor were investigated and optimized. The immunosensor showed excellent electroanalytical performance in combination with an impedimetric approach and exhibited a low detection limit of only 45 fM SARS-CoV-2 spike protein. Its practical applicability was successfully demonstrated by measuring the spike protein in a spiked artificial nasopharyngeal fluid sample.

Graphene-based materials are actively being investigated as sensing elements for the detection of different analytes. Both graphene grown by chemical vapor deposition (CVD) and graphene oxide (GO) produced by the modified Hummers\' method are actively used in the development of biosensors. The production costs of CVD graphene- and GO-based sensors are similar; however, the question remains regarding the most efficient graphene-based material for the construction of point-of-care diagnostic devices. To this end, in this work, we compare CVD graphene aptasensors with the aptasensors based on reduced GO (rGO) for their capabilities in the detection of NT-proBNP, which serves as the gold standard biomarker for heart failure. Both types of aptasensors were developed using commercial gold interdigitated electrodes (IDEs) with either CVD graphene or GO formed on top as a channel of liquid-gated field-effect transistor (FET), yielding GFET and rGO-FET sensors, respectively. The functional properties of the two types of aptasensors were compared. Both demonstrate good dynamic range from 10 fg/mL to 100 pg/mL. The limit of detection for NT-proBNP in artificial saliva was 100 fg/mL and 1 pg/mL for rGO-FET- and GFET-based aptasensors, respectively. While CVD GFET demonstrates less variations in parameters, higher sensitivity was demonstrated by the rGO-FET due to its higher roughness and larger bandgap. The demonstrated low cost and scalability of technology for both types of graphene-based aptasensors may be applicable for the development of different graphene-based biosensors for rapid, stable, on-site, and highly sensitive detection of diverse biochemical markers.

This work presents a significant investigation involving both electrochemical experiment and quantum chemical simulation approaches. The objective was to characterize the electrochemical detection of dopamine (DA). The detection was carried out using a modified carbon paste electrode (CPE) incorporating bentonite (Bent) and l-cysteine (CySH) (named as CySH/Bent/CPE). To understand and explain the oxidation mechanism of DA on the CySH/Bent modified electrode surface, the coupling of the two approaches were exploited. The CySH/Bent/CPE showed excellent electroactivity toward DA such as good sensibility, selectivity, stability, and regenerative ability. The developed sensor shows a dynamic linear range from 0.8 to 80 μM with a limit of detection and quantification of 0.5 μM and 1.5 μM, respectively. During the quantitative analysis of DA in presence of ascorbic acid (AA) and uric acid (UA) the electrochemical oxidation signals of AA, DA, and UA distinctly appear as three separate peaks. The potential differences between the peaks are 190 mv, 150 mv, and 340 mV for the AA-DA, DA-UA, and AA-UA oxidation pairs, respectively. These observations stem from square wave voltammetry (SWV) studies, along with the corresponding redox peak potential separations. The developed sensor is simple and accurate to monitor DA in human serum samples. On the other hand, CySH acts as an electrocatalyst on the CySH/Bent/CPE surface by increasing its active electron transfer sites, as suggested by the quantum chemical modeling with analytical results of Fukui. Furthermore, the voltammetric results obtained agree well with the theoretical calculations.