https://www.abechem.com/ Analytical and Bioanalytical Electrochemistry en daily 1 Sat, 28 Feb 2026 00:00:00 +0330 Sat, 28 Feb 2026 00:00:00 +0330 https://www.abechem.com/article_741068.html This study presents a comprehensive machine learning approach for the classification and analysis of modified carbon paste electrodes (CPE) designed for methanol fuel cell anodes. Four electrode configurations were systematically investigated: unmodified CPE, zinc-modified CPE (CPE/Zn), polymer-enhanced CPE/Zn with 1,4-cis polymyrcene (CPE/Zn/Polymer), and bio-modified CPE/Zn/Polymer/Bacteria electrodes using Escherichia coli biofilms. Advanced machine learning techniques including Convolutional Neural Networks (CNN), Random Forest, Support Vector Machines, Long Short-Term Memory networks, and Bayesian analysis were employed to analyze cyclic voltammetry data and predict electrode performance for methanol oxidation. The deep CNN achieved superior classification accuracy of 98% (AUC = 0.98) compared to Random Forest (91%) and SVM (87%). Principal Component Analysis revealed that electrode modifications systematically altered electrochemical properties, with methanol oxidation peak current and potential being the most discriminative features (47% combined importance). Autoencoder-based denoising successfully reconstructed CV curves with minimal error, while LSTM networks demonstrated predictive capability for temporal electrode behavior and methanol oxidation efficiency. The integration of machine learning with fundamental electrochemical principles provides a powerful framework for automated electrode characterization, quality control, and performance optimization in methanol fuel cell applications. https://www.abechem.com/article_741074.html Metoprolol tartrate (MET) is a selective β-adrenergic antagonist used in the treatment of cardiovascular diseases. MET overdose can affect the heart, blood pressure, breathing, and nervous system. Hence, sensitive and easy methods are required for its determination. In this work, we report a simple approach for fabrication of a bimetallic Cu/Ni modified carbon paste electrode (Cu/Ni/CPE) for electrocatalytic oxidation and determination of the metoprolol drug. At first, using the electrodeposition method, Ni was deposited on the carbon paste electrode at room temperature; then, a galvanic replacement reaction was applied for the replacement of some nickel atoms with Cu atoms. Effective parameters on electrode response to metoprolol were optimized. In optimized conditions, the bimetallic modified electrode exhibited higher electrocatalytic activity for metoprolol than a single metal modified electrode: Cu/Ni/CPE has a wider linear range and higher sensitivity to metoprolol respect to Ni/CPE. The surface of Cu/Ni/CPE was characterized by field emission scanning electron microscopy (FE-SEM) and Energy-dispersive X-ray spectroscopy (EDX). The linear dynamic range of this modified electrode for metoprolol is 1×10-5 to 7×10-4 M, and the limit of detection was determined to be 2.9 µM. Finally, this modified electrode was applied for the determination of metoprolol in human plasma and tablet samples, and acceptable results were obtained. For comparison, spectrophotometry was used as the reference method. https://www.abechem.com/article_741076.html This study introduces a novel electrochemical strategy for fabricating a robust and selective adsorptive interface by covalently grafting an azo-functionalized polymer (AZO Polymer) onto a copper electrode via diazonium chemistry for efficient Pb²⁺ removal from aqueous solutions. The synthesized poly(acrylamide-co-o-cresol) was characterized by FTIR, ¹H NMR, and XPS, confirming the successful incorporation of azo (–N=N–) and amide (–CONH₂) functionalities. Electrochemical grafting yielded a uniform, porous polymeric layer, as evidenced by SEM and N₂ physisorption, which increased the surface area and provided abundant coordination sites. The adsorption kinetics, monitored by electrochemical impedance spectroscopy (EIS) and quartz crystal microbalance (EQCM), revealed a rapid initial uptake, with Pb²⁺ removal efficiency reaching ~55% within 30 minutes and attaining a plateau of ~94% after 60 minutes (20 ppm, pH 7, 25°C). EIS analysis demonstrated a systematic increase in charge-transfer resistance (Rct) from ~820 Ω cm² to ~4650 Ω cm² over 60 minutes, correlating directly with Pb²⁺ accumulation. Remarkably, the electrode maintained >84% of its initial adsorption capacity after five consecutive adsorption–desorption cycles, demonstrating excellent reusability and interfacial stability. This work establishes electrochemically grafted AZO polymer layers as a durable, efficient, and regenerable platform for selective heavy metal remediation, merging covalent surface anchoring with tailored molecular affinity for sustainable water treatment. https://www.abechem.com/article_741077.html Among the analytical methods for measuring small amounts of metal ions, potentiometric ion-selective sensors have high speed, precision, and accuracy and are more convenient to use. On the other hand, one-pot synthesis offers an attractive and sustainable approach by reducing waste, saving time, and simplifying complex multi-step reactions. Another important advantage of one-pot synthesis lies in its improved atom economy and reduced environmental footprint. In this research, a new Ba2+ ion-extracting potentiometric sensor based on 1,2-bis(4-nitrophenyl) ethane-1,2-dione (4,4’-dinitrobenzil) (BNED) ligand was prepared. The interaction between the ligand with barium ions and other metal ions were investigated through UV-Vis spectroscopy, which indicated the selectivity for Ba2+. The optimal percentage composition for the present electrode membrane is 37:55:3:5, respectively for PVC:BA: NaTPB: BNED. This sensor has a Nernst slope of 24.9 mV/Decade in the linear range of 1-10-7 M to 1-10-2 M. The response of the electrode in the pH range of 4.0 to 10.5 is independent of the changes in the concentration of H+ ions. The designed electrode has a lifespan of about 3 months and a response time of about 25 seconds. This sensor has good selectivity for Ba2+ over various cations (alkali metals, alkaline earth metals, heavy metals and transition metals). The electrode prepared in the present study was used as a detector electrode in the measurement of Ba2+ in real samples. https://www.abechem.com/article_741078.html Green hydrogen, produced by renewable energy-powered water electrolysis, is emerging as a promising solution for global decarbonization. Green hydrogen offers a sustainable alternative to fossil fuels, reducing greenhouse gas emissions across various industries. However, several challenges, including energy efficiency, high production costs, and storage concerns, have turned out to be the major impediments to its large-scale deployment. Artificial Intelligence (AI) provides transformative opportunities to optimize green hydrogen production, improve storage techniques, and enable integration with renewable energy systems. This review explores the role of AI techniques, encompassing machine learning, reinforcement learning, and Digital Twins (DTs), in enhancing electrolyzer performance, system degradation prediction, and hydrogen distribution network management. Additional AI applications for storage material discovery, energy forecasting, and sector-level applications in transport, power, and industry are also highlighted in this review. A conceptual framework is provided to map AI models to every stage of the hydrogen value chain. Gaps in the literature and opportunities for interdisciplinary collaboration are identified toward the realization of scalable intelligent hydrogen systems. The review concludes by proposing future avenues for AI-enabled innovations, maintaining a sustainable green hydrogen economy. https://www.abechem.com/article_741082.html Zinc-ion batteries have been proposed as promising alternatives for energy storage systems owing to their high safety, low cost, and environmental compatibility. Among them, V2O5 is considered one of the most important candidates for use as a cathode in these batteries because of its high specific capacity, multiple oxidation states, and suitable layered structure. However, challenges such as low conductivity, dissolution of vanadium in aqueous electrolytes, structural changes during the charge and discharge processes, and formation of unstable by-products have limited the performance of this material. Recently, various strategies have been introduced to overcome these problems, including interlayer insertion of cations and water molecules, metal doping, surface modification with conductive coatings, and electrolyte optimization. These modifications have led to expanded interlayer spacing, improved structural stability, enhanced ionic and electronic conductivity, and ultimately increased specific capacity and cycle life in V2O5-based batteries. A review of recent research suggests that structural and compositional engineering of V2O5 could pave the way for the development of stable and high-performance cathodes and significantly support their technological development in future energy storage applications.