Search Results (1,911)

Surface and sub-surface atomic configurations are critical for catalysis as they host the active sites governing electrochemical processes. This study employs density functional theory (DFT) calculations and Monte Carlo simulations combined with the cluster-expansion approach to investigate atom distribution and Pt segregation in Pt-Fe alloys across varying Pt/Fe ratios. Our simulations reveal a strong tendency for Pt atoms to segregate to the surface layer while Fe atoms enrich the sub-surface region. Crucially, the calculations predict the stability of a periodic Pt₂Fe alloy surface model, characterized by specific defect structures, at low platinum content and low annealing temperatures. Electronic structure analysis indicates that forming this Pt₂Fe surface alloy lowers the d-band center of Pt atoms, weakening CO adsorption and thereby enhancing resistance to CO poisoning. Although defect-induced strains can modulate the d-band center, crystal orbital Hamilton population (COHP) analysis confirms that such strains generally strengthen Pt-CO interactions. Therefore, the theoretical design of Pt₂Fe alloy surfaces and controlling defect density are predicted to be effective strategies for enhancing catalyst resistance to CO poisoning. This work highlights the advantages of periodic Pt₂Fe surface models for anti-CO poisoning and provides computational guidance for designing efficient Pt-based electrocatalysts. Full article

Objectives: Most antiviral vaccines are created by inactivating the virus using chemical methods. The inactivation and production of viral vaccine preparations after the irradiation of viruses with accelerated electrons has a number of significant advantages. Determining the integrity of the genome of the resulting viral particles is necessary to assess the quality and degree of inactivation after irradiation. Methods: This work was performed on the Sabin 2 model polio virus. To determine the most sensitive and most radiation-resistant part, the polio virus genome was divided into 20 segments. After irradiation at temperatures of 25 °C, 2–8 °C, −20 °C, or −70 °C, the amplification intensity of these segments was measured in real time. Results: The best correlation between the amplification cycle and the irradiation dose at all temperatures was observed for segment 3D, left. Consequently, this section of the poliovirus genome is the least resistant to the action of accelerated electrons and is the most representative for determining genome integrity. The worst dependence was observed for the VP1 right section, which, therefore, cannot be used to determine genome integrity during inactivation. The electrochemical approach was also employed for a comparative assessment of viral RNA integrity before and after irradiation. An increase in the irradiation dose was accompanied by an increase in signals indicating the electrooxidation of RNA heterocyclic bases. The increase in peak current intensity of viral RNA electrochemical signals confirmed the breaking of viral RNA strands during irradiation. The shorter the RNA fragments, the greater the peak current intensities. In turn, this made the heterocyclic bases more accessible to electrooxidation on the electrode. Conclusions: These results are necessary for characterizing the integrity of the viral genome for the purpose of creating of antiviral vaccines. Full article

Myocardial infarction (MI) remains one of the most common cardiovascular diseases and a leading cause of morbidity and mortality worldwide. In recent years, natural polymeric patches have attracted increasing attention as a promising therapeutic platform for myocardial tissue repair. This study explored the fabrication and evaluation of screen-printed electrodes (SPEs) on chitosan film as a novel platform for cardiac patch applications. Chitosan is a biodegradable and biocompatible natural polymer that provides an ideal substrate for SPEs, providing mechanical stability and promoting cell adhesion. Silver ink was employed to enhance electrochemical performance, and the electrodes exhibited strong adhesion and structural integrity under wet conditions. Mechanical testing and swelling ratio analysis were conducted to assess the patch’s physical robustness and aqueous stability. Silver ink was employed to enhance electrochemical performance, which was evaluated using cyclic voltammetry. In vitro, electrical stimulation through the chitosan–SPE patch significantly increased the expression of cardiac-specific genes (GATA-4, β-MHC, troponin I) in bone marrow mesenchymal stem cells (BMSCs), indicating early cardiogenic differentiation potential. In vivo, the implantation of the chitosan–SPE patch in a rat MI model demonstrated good tissue integration, preserved myocardial structure, and enhanced ventricular wall thickness, indicating that the patch has the potential to serve as a functional cardiac scaffold. These findings support the feasibility of screen-printed electrodes fabricated on chitosan film substrates as a cost-effective and scalable platform for cardiac repair, offering a foundation for future applications in cardiac tissue engineering. Full article

Electrochemical biosensors are revolutionizing food testing by addressing critical limitations of conventional strategies that suffer from cost, complexity, and field-deployment challenges. Emerging fluorescence and Raman techniques, while promising, face intrinsic drawbacks like photobleaching and matrix interference in opaque or heterogeneous samples. In contrast, electrochemical biosensors leverage electrical signals to bypass optical constraints, enabling rapid, cost-effective, and pretreatment-free analysis of turbid food matrices. This review highlights their operational mechanisms, emphasizing nano-enhanced signal amplification (e.g., Au nanoparticles and graphene) and biorecognition elements (antibodies, aptamers, and molecularly imprinted polymers) for ultrasensitive assay of contaminants, additives, and adulterants. By integrating portability, scalability, and real-time capabilities, electrochemical biosensors align with global food safety regulations and sustainability goals. Challenges in standardization, multiplexed analysis, and long-term stability are discussed, alongside future directions toward AI-driven analytics, biodegradable sensors, and blockchain-enabled traceability, ultimately fostering precision-driven, next-generation food safety and quality testing. Full article

Aluminum–copper casting alloys are potential candidate materials for use in marine applications where high mechanical strength and superior fatigue resistance are desired. The corrosion and protection of aluminum alloy B206 in seawater through surface passivation continues to pose challenges, hampering its widespread use in marine structures. In this study, the electrochemical behavior of B206 is investigated in artificial seawater at temperatures and dissolved oxygen (DO) concentrations anticipated during service in marine environments. In particular, the influence of anodizing B206 in deaerated seawater on the subsequent corrosion behavior of the alloy is studied using potentiodynamic and potentiostatic polarization, electrochemical impedance spectroscopy (EIS), and Mott–Schottky analysis. The results showed that the effect of DO on the corrosion of B206 is more significant than the effect of temperature. In the absence of DO, results of potentiostatic polarization, EIS, and Mott–Schottky analysis at anodic potentials all indicated the development of a thicker, more protective passive layer in colder seawater. Moreover, passive layer thickness modeled using Power-Law was found to range between 3 and 9 nm, whilst decreasing in thickness with temperature. Donor densities of the n-type passive layer are on the order of 1021 cm⁻³ and increase with temperature. The findings presented in this study support the feasibility of implementing anodizing for B206 in marine service environments. Full article

This study developed a two-dimensional multiphysics-coupled model for co-electrolysis of CO₂ and H₂O in solid oxide electrolysis cells (SOECs) using COMSOL Multiphysics, systematically investigating the influence mechanisms of key operating parameters including temperature, voltage, feed ratio, and flow configuration on co-electrolysis performance. The results demonstrate that increasing temperature significantly enhances CO₂ electrolysis, with the current density increasing over 12-fold when temperature rises from 923 K to 1423 K. However, the H₂O electrolysis reaction slows beyond 1173 K due to kinetic limitations, leading to reduced H₂ selectivity. Higher voltages simultaneously accelerate all electrochemical reactions, with CO and H₂ production at 1.5 V increasing by 15-fold and 13-fold, respectively, compared to 0.8 V, while the water–gas shift reaction rate rises to 6.59 mol/m³·s. Feed ratio experiments show that increasing CO₂ concentration boosts CO yield by 5.7 times but suppresses H₂ generation. Notably, counter-current operation optimizes reactant concentration distribution, increasing H₂ and CO production by 2.49% and 2.3%, respectively, compared to co-current mode, providing critical guidance for reactor design. This multiscale simulation reveals the complex coupling mechanisms in SOEC co-electrolysis, offering theoretical foundations for developing efficient carbon-neutral technologies. Full article

The electrodynamics of current provide much of our technology, from telegraphs to the wired infrastructure powering the circuits of our electronic technology. Current flow is analyzed by its own rules that involve the Maxwell Ampere law and magnetism. Electrostatics does not involve magnetism, and so current flow and electrodynamics cannot be derived from electrostatics. Practical considerations also prevent current flow from being analyzed one charge at a time. There are too many charges, and far too many interactions to allow computation. Current flow is essential in biology. Currents are carried by electrons in mitochondria in an electron transport chain. Currents are carried by ions in nerve and muscle cells. Currents everywhere follow the rules of current flow: Kirchhoff’s current law and its generalizations. The importance of electron and proton flows in generating ATP was discovered long ago but they were not analyzed as electrical currents. The flow of protons and transport of electrons form circuits that must be analyzed by Kirchhoff’s law. A chemiosmotic theory that ignores the laws of current flow is incorrect physics. Circuit analysis is easily applied to short systems like mitochondria that have just one internal electrical potential in the form of the Hodgkin Huxley Katz (HHK) equation. The HHK equation combined with classical descriptions of chemical reactions forms a computable model of cytochrome c oxidase, part of the electron transport chain. The proton motive force is included as just one of the components of the total electrochemical potential. Circuit analysis includes its role just as it includes the role of any other ionic current. Current laws are now needed to analyze the flow of electrons and protons, as they generate ATP in mitochondria and chloroplasts. Chemiosmotic theory must be replaced by an electro-osmotic theory of ATP production that conforms to the Maxwell Ampere equation of electrodynamics while including proton movement and the proton motive force. Full article

Fast charging accelerates lithium-ion battery operation but increases the risk of lithium (Li) plating—a process that undermines efficiency, longevity, and safety. Here, we introduce a predictive modeling framework that captures the onset and severity of Li plating under practical fast-charging conditions. By integrating an empirically parameterized SOC threshold model with time-dependent kinetic simulations and Arrhenius based thermal analysis, we delineate operating regimes prone to irreversible Li accumulation. The framework distinguishes reversible and irreversible plating fractions, quantifies energy losses, and identifies a critical activation energy (0.25 eV) associated with surface-limited deposition. Visualizations in the form of severity maps and voltage-zone risk classifications enable direct application to battery management systems. This approach bridges electrochemical degradation modeling with real-time charge protocol design, offering a practical tool for safe, high-performance battery operation. Full article

Micro-textures are crucial for enhancing surface performance in diverse applications, but traditional radial electrochemical micromachining (REMM) suffers from process complexity and workpiece damage. This study presents radial ultrasonic rolling electrochemical micromachining (RUREMM), an advanced technique integrating an ultrasonic field to improve electrolyte renewal, disrupt passivation layers, and optimize electrochemical reaction uniformity on SS304 surfaces. Aimed at overcoming challenges in precision machining, the research explores the synergistic effects of ultrasonic energy and flow field dynamics, offering novel insights for high-quality metal micromachining applications. The research establishes a mathematical model to analyze the interaction between the ultrasonic energy field and electrolytic machining and optimizes the flow field in the narrow electrolytic gap using Fluent software, revealing that an initial electrolyte velocity of 4 m/s and ultrasonic amplitude of 35 μm ensure optimal stability. High-speed photography is employed to capture bubble distribution and micro-pit formation dynamics, while SS304 surface experiments analyze the effects of machining parameters on micro-dimple localization and surface quality. The results show that optimized parameters significantly improve micro-texture quality, yielding micro-pits with a width of 223.4 μm, depth of 28.9 μm, aspect ratio of 0.129, and Ra of 0.205 μm, providing theoretical insights for high-precision metal micromachining. Full article

The escalating demand for efficient thermal management in lithium-ion batteries necessitates precise characterization of their thermal behavior under diverse operating conditions. This study develops a three-dimensional (3D) electrochemical–thermal coupling model grounded in porous electrode theory and energy conservation principles. The model solves multi-physics equations such as Fick’s law, Ohm’s law, and the Butler–Volmer equation, to resolve coupled electrochemical and thermal dynamics, with temperature-dependent parameters calibrated via the Arrhenius equation. Simulations under varying discharge rates reveal that high-rate discharges exacerbate internal heat accumulation. Low ambient temperatures amplify polarization effects. Forced convection cooling reduces surface temperatures but exacerbates core-to-surface thermal gradients. Structural optimization strategies demonstrate that enhancing through-thickness thermal conductivity reduces temperature differences. These findings underscore the necessity of balancing energy density and thermal management in lithium-ion battery design, proposing actionable insights such as preheating protocols for low-temperature operation, optimized cooling systems for high-rate scenarios, and material-level enhancements for improved thermal uniformity. Full article

The electrocatalytic CO₂ reduction reaction (CO₂RR) offers an energy-saving and environmentally friendly approach to producing hydrocarbon fuels. The use of a gas diffusion electrode (GDE) flow cell has generally improved the rate of CO₂RR, while the gas diffusion layer (GDL) remains a significant challenge. In this study, we successfully engineered a novel metal–organic framework (MOF) heterojunction through the controlled coating of zeolitic imidazolate framework (ZIF-L) on ultrathin nickel—metal–organic framework (Ni-MOF) nanosheets. This innovative architecture simultaneously integrates GDL functionality and exposes abundant solid–liquid–gas triple-phase boundaries. The resulting Ni-MOF@ZIF-L heterostructure demonstrates exceptional performance, achieving a formate Faradaic efficiency of 92.4% while suppressing the hydrogen evolution reaction (HER) to 6.7%. Through computational modeling of the optimized heterojunction configuration, we further elucidated its competitive adsorption behavior and electronic modulation effects. The experimental and theoretical results demonstrate an improvement in electrochemical CO₂ reduction activity with suppressed hydrogen evolution for the heterojunction because of its hydrophobic interface, good electron transfer capability, and high CO₂ adsorption at the catalyst interface. This work provides a new insight into the rational design of porous crystalline materials in electrocatalytic CO₂RR. Full article

This study explores the corrosion inhibition of C38 steel in a 1 M hydrochloric acid (HCl) solution using a novel benzoxazole-2-thione compound. The inhibitor was synthesized and structurally characterized by both ¹H NMR (DMSO-d₆/TMS) and ¹³C NMR spectroscopy. Electrochemical techniques, including Tafel polarization and electrochemical impedance spectroscopy, were employed to evaluate the inhibition performance. The results indicate that the benzoxazole-2-thione significantly reduces the corrosion rate, achieving a maximum inhibition efficiency of 95.25% at a concentration of 10⁻⁴ M. To gain deeper insights into the inhibition mechanism, theoretical methods such as density functional theory, Monte Carlo simulations, and molecular dynamics were applied to investigate the adsorption behavior of the compound on the steel surface. The adsorption process follows the Langmuir isotherm model, suggesting the coexistence of physisorption and chemisorption interactions. Surface morphology and elemental composition analyses using scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDX) confirm the formation of a protective inhibitor film on the steel surface. Full article

Accurate State of Charge (SOC) estimation is challenged by battery aging and complex internal dynamics. This work introduces a novel framework, Mamba-PG, that leverages the Mamba architecture to integrate internal gas pressure—a direct indicator of electrochemical state—for high-accuracy SOC estimation. The core innovation is a specialized pressure-aware gating mechanism designed to adaptively fuse the pressure signal with conventional electrical data. On a public dataset, our model achieved a state-of-the-art Mean Absolute Error (MAE) of 0.386%. Furthermore, we demonstrate that the gating mechanism learns a physically-plausible and interpretable strategy, dynamically adjusting the pressure signal’s influence based on its magnitude and the battery’s aging state. This study validates that the synergy of novel physical signals with efficient, interpretable architectures like Mamba presents a robust path toward next-generation Battery Management Systems. Full article

Oxidative stress overwhelms cellular antioxidant defenses, causing DNA damage and pro-tumorigenic signaling that accelerate cancer initiation and progression. Electron shuttles (ESs) from phytocompounds offer precise redox control but lack quantitative benchmarks. This study aims to give a clearer definition to electron shuttles by characterizing mulberry’s electrochemical capabilities via the three defined ES criteria and deciphering its mechanism against oxidative stress-related cancer. Using double-chambered microbial-fuel-cell power metrics, cyclic voltammetry, and compartmental fermentation modeling, we show that anthocyanin shows a significant difference (p < 0.05) in power density at ≥500 µg/mL (maximum of 2.06-fold power-density increase) and reversible redox cycling (ratio = 1.65), retaining >90% activity over four fermentation cycles. Molecular docking implicates meta-dihydroxyl motifs within the core scaffold in receptor binding, overturning the view that only ortho- and para-substituents participate in bioactivity. In vitro, anthocyanins both inhibit nitric oxide release and reduce DU-145 cell viability dose-dependently. Overall, our findings establish mulberry anthocyanins as robust electron shuttles with potential for integration into large-scale bio-electrochemical platforms and targeted redox-based cancer therapies. Full article

Accurate State of Charge (SOC) estimation is critical for optimizing the performance and longevity of lithium-ion batteries (LIBs), which are widely used in applications ranging from electric vehicles to renewable energy storage. Traditional SOC estimation methods, such as Coulomb counting and open-circuit voltage measurement, suffer from cumulative errors and slow response times. This paper proposes a novel machine learning-based approach for SOC estimation by integrating Electrochemical Impedance Spectroscopy (EIS) with the SHapley Additive exPlanations (SHAP) method, Atom Search Optimization (ASO), and Light Gradient Boosting Machine (LightGBM). This study focuses on large-capacity lithium iron phosphate (LFP) batteries (3.2 V, 104 Ah), addressing a gap in existing research. EIS data collected at various SOC levels and temperatures were processed using SHAP for feature extraction (FE), and the ASO–LightGBM model was employed for SOC prediction. Experimental results demonstrate that the proposed SHAP–ASO–LightGBM method significantly improves estimation accuracy, achieving an RMSE of 3.3%, MAE of 1.86%, and R² of 0.99, outperforming traditional methods like LSTM and DNN. The findings highlight the potential of EIS and machine learning (ML) for robust SOC estimation in large-capacity LIBs. Full article