Search Results (7,111)

Phenolic compounds such as resorcinol (RS) have negative impacts on aquatic life, the environment, and human health. Thus, it is necessary to develop sensing devices for the monitoring of RS. The electrochemical method is one of the most significant approaches for the determination of toxic substances. In electrochemical methods, electrode modifiers play a vital role and affect the sensing performance of the electrochemical sensors. Thus, the selection of efficient electrode material is of great importance. In recent years, various electrode modifiers such as graphene, metal–organic frameworks (MOFs), MXenes, metal oxides, polymers, and composite materials have been extensively used for the fabrication of RS sensors. In this review, we have summarized the reported electrode modifiers for the fabrication of RS electrochemical sensors. Various electrochemical sensing techniques, including differential pulse voltammetry (DPV), square wave voltammetry (SWV), amperometry (Amp), cyclic voltammetry (CV), and linear sweep voltammetry (LSV) have been discussed. This review provides an overview of a large number of electrode modifiers for the determination of RS. The limitations, challenges, and future perspectives for RS sensors are discussed. We believe that the present review article is beneficial for the scientific community and electrochemists working on the construction of RS sensors. Full article

Changing the topography of electrodes by ultrafast laser ablation has shown great potential in enhancing electrochemical performance in lithium-ion batteries. The generation of microstructured channels within the electrodes creates shorter pathways for lithium-ion diffusion and mitigates strain from volume expansion during electrochemical cycling. The topography modification enables faster charging, improved rate capability, and the potential to combine high-power and high-energy properties. In this study, we present a preliminary exploration of this approach for sodium-ion battery technology, focusing on the impact of laser-generated channels on hard carbon electrodes in sodium-metal half-cells. The performance was analyzed by employing different conditions, including different electrolytes, separators, and electrodes with varying compaction degrees. To identify key factors contributing to rate capability improvements, we conducted a comparative analysis of laser-structured and unstructured electrodes using methods including scanning electron microscopy, laser-induced breakdown spectroscopy, and electrochemical cycling. Despite being based on a limited sample size, the data reveal promising trends and serve as a basis for further optimization. Our findings suggest that laser structuring can enhance rate capability, particularly under conditions of limited electrolyte wetting or increased electrode density. This highlights the potential of laser structuring to optimize electrode design for next-generation sodium-ion batteries and other post-lithium technologies. Full article

Seawater desalination has emerged as a crucial solution for addressing global freshwater scarcity. However, it generates significant volumes of concentrated brine waste. This brine is rich in dissolved salts and minerals, primarily, chloride (55%), sodium (30%), sulfate (8%), magnesium (4%), calcium (1%), potassium (1%), bicarbonate (0.4%), and bromide (0.2%), which are often discharged into marine environments, posing ecological challenges. This study presents a comprehensive global review of innovative technologies for recovering these constituents as valuable products, thereby enhancing the sustainability and economic viability of desalination. The paper evaluates a range of proven and emerging recovery methods, including membrane separation, nanofiltration, electrodialysis, thermal crystallization, solar evaporation, chemical precipitation, and electrochemical extraction. Each technique is analyzed for its effectiveness in isolating salts (NaCl, KCl, and CaSO₄) and minerals (Mg(OH)₂ and Br₂), with a discussion of process-specific constraints, recovery efficiencies, and product purities. Furthermore, the study incorporates a detailed techno-economic assessment, highlighting revenue potential, capital and operational expenditures, and breakeven timelines. Simulated case studies of a 100,000 m³/day seawater reverse osmosis (SWRO) facility demonstrates that a sequential brine recovery process and associated energy balances, supported by pilot-scale data from ongoing global initiatives, can achieve over 90% total salt recovery while producing marketable products such as NaCl, Mg(OH)₂, and Br₂. The estimated revenue from recovered materials ranges between USD 4.5 and 6.8 million per year, offsetting 65–90% of annual desalination operating costs. The analysis indicates a payback period of 3–5 years, depending on recovery efficiency and product pricing, underscoring the economic viability of large-scale brine valorization alongside its environmental benefits. By transforming waste brine into a source of commercial commodities, desalination facilities can move toward circular economy models and achieve greater sustainability. A practical integration framework is proposed for both new and existing SWRO plants, with a focus on aligning with the principles of a circular economy. By transforming waste brine into a resource stream for commercial products, desalination facilities can reduce environmental discharge and generate additional revenue. The study concludes with actionable recommendations and insights to guide policymakers, engineers, and investors in advancing brine mining toward full-scale implementation. Full article

Depression is becoming more common in the face of modern life’s obstacles. Antidepressants are a fast-expanding pharmaceutical category. Antidepressant residues in water must be closely monitored and kept at levels that do not endanger human health, just like those of other psychotropic medications. Additionally, research has shown that these pollutants severely hinder aquatic life’s ability to migrate, reproduce, and interact with one another when they enter natural ecosystems. Antidepressants released into the natural environment can therefore be expected to have an impact on exposed fish and other aquatic species. There is a lot of information available about how exposure affects fish, but much of it is for exposure levels higher than those seen in their natural habitats. Antidepressants can bioaccumulate in fish tissues, and some behavioral effects have been documented for exposures that are relevant to the environment. As a result, antidepressant residue removal methods must be incorporated into contemporary wastewater treatment plant technology. In addition to covering a wide range of suggested treatment options and their ecotoxicological consequences on non-target organisms, this study discusses recent efforts to accomplish this goal. First, a thorough analysis of the harmful impacts on non-target people is provided. This work describes a variety of adsorptive methods that can make use of modern materials like molecularly imprinted polymers or ion-exchange resins or can rely on well-known and efficient adsorbents like silicates or activated carbon. Although extractive methods are also taken into consideration, they are now impractical due to the lack of reasonably priced and ecologically suitable solvents. Lastly, sophisticated oxidation methods are discussed, such as electrochemical alternatives, UV and gamma radiation, and ozone therapy. Notably, some of these techniques could totally mineralize antidepressant toxicants, either alone or in combination. Lastly, the topic of biological treatment with microorganisms is covered. This method can be very specific, but it usually prevents full mineralization. Full article

Facing the increasingly scarce supply of rare-earth resources, a cobalt-doped metal–organic framework-derived carbon–metallic sulfide composite (Co-FeS₂@C) was successfully synthesized via the hydrothermal method and the following carbonization/sulfidation treatments and used for the efficient electrosorption of rare earths from aqueous solution. Comparative characterizations revealed that Co doping effectively expanded the interlayer spacing of FeS₂, introduced crystalline defects, and optimized the electronic structure, thereby synergistically enhancing active site exposure and electron transfer kinetics. In addition, the electrochemical analysis demonstrated a significant increase in the surface-controlled capacitive contribution from 57.1% to 83.3%, indicating the markedly improved electric double-layer effects and mass transport efficiency. Under the optimal conditions, the Co-FeS₂@C electrode achieved a high Yb³⁺ adsorption capacity of 129.2 mg g⁻¹ along with an exceptional cycling stability (92.63% retention after 20 cycles), substantially outperforming the undoped counterpart FeS₂ (88.4 mg g⁻¹ and 74.61%). Furthermore, the mechanistic investigations confirmed that the electrosorption process follows a monolayer physico-chemical synergistic mechanism, primarily driven by the pseudo-capacitive effect arising from the redox reaction of FeS₂ and the enhanced charge-transfer driving force resulting from the higher electronegativity of cobalt. This work provides an innovative electronic structure modulation strategy for developing the high-performance capacitive deionization electrodes for rare earth recovery via the electrosorption process. Full article

Since mechanical processing can introduce stress in the sample, electrochemical dissolution has been utilized to attain shape accuracy in certain materials. However, this technique is rarely applied to laser-repaired Ni-based single-crystal superalloys. In this work, the transpassive dissolution behaviors of an additive manufacturing-repaired Ni-based single crystal superalloy in a 10% NaNO₃ solution were investigated by comparison with the substrate. A significant disparity in dissolution rates was found between the dendritic and interdendritic regions of the substrate, resulting in a rough surface. Conversely, the dissolution of the dendritic and interdendritic regions in the cladding structure occurred nearly simultaneously, leading to a high-quality, smooth surface. This behavior was attributed to the differences in phase dissolution preferences between the substrate and the cladding structure. It indicates that electrochemical dissolution is a promising method for achieving shape accuracy in laser-clad Ni-based single-crystal superalloys. Full article

The multi-layer workpiece and multi-wire electrochemical microfabrication method (MWECM) has considerable potential in improving production efficiency and is considered a promising technology for manufacturing high-quality array microstructures. However, due to the accumulation of electrolytic by-products between workpiece layers, the machining accuracy is relatively low, which still limits its application in industrial environments. To address this issue, this article introduces a method to enhance mass transfer, which involves multi-layer workpieces and multi-wire electrochemical microfabrication, and employs horizontal electrolyte flushing (MWECMF). This innovation promotes the effective discharge of electrolytic deposits, thereby enhancing the renewal of electrolytes within the electrode gap. And use flow field simulation to optimize the interlayer spacing of workpieces and determine the optimal workpiece spacing. In addition, single factor experiments were conducted to determine the optimal processing parameters, including wire feed speed, power supply voltage, frequency, and duty cycle. Finally, at a feed rate of 1.2 µm/s, an array microstructure was successfully fabricated using a two-wire electrode setup and a four-layer workpiece configuration, achieving an overall machining rate of 9.6 µm/s. Compared to traditional tools or workpiece vibration mass transfer, the MWECMF method significantly improves the machining efficiency of wire electrochemical microfabrication (WECM). Full article

The discharge of ammonia-rich wastewater poses significant threats to water quality and ecosystem health, driving the need for efficient and sustainable treatment technologies. The electrochemical ammonia oxidation reaction (eAOR) has emerged as a promising alternative to conventional biological and physicochemical methods, offering advantages such as in situ oxidant generation, tunable product selectivity, and applicability under challenging water matrices. This comprehensive review systematically examines the mechanisms, catalyst design, and environmental factors influencing eAOR performance. Two primary pathways are detailed: direct eAOR, involving stepwise dehydrogenation of NH₃ on the electrode surface, and indirect eAOR, mediated by electrogenerated reactive chlorine species (RCS). The mechanisms—including the Oswin-Salomon and Gerischer-Mauerer pathways for direct oxidation, as well as breakpoint chlorination and radical-mediated routes for indirect oxidation—are critically discussed alongside experimental and theoretical evidence. Recent advances in electrocatalyst development are highlighted, covering noble metals, non-noble transition metal oxides, alloys, and hybrid materials, with an emphasis on enhancing activity, selectivity toward N₂, and durability. Key operational parameters such as pH, chloride concentration, and coexisting ions are analyzed for their impact on reaction kinetics and byproduct formation. Finally, the review identifies current challenges—including catalyst poisoning, toxic byproduct generation, and scalability—and outlines future research directions aimed at advancing eAOR toward energy-efficient, resource-recovering water treatment systems. Full article

Hydrogen sulfide (H₂S), a highly toxic gas, is mainly sourced from petroleum refining, natural gas purification, and coal chemical processes. It poses significant risks to human health, causes environmental pollution, and accelerates equipment corrosion. Recent studies have demonstrated that electrochemical coupling systems offer an efficient, sustainable, and cost-effective strategy for removing sulfur-containing gaseous pollutants. These systems enable the conversion of H₂S into recoverable sulfur under mild conditions, while simultaneously harnessing the chemical energy of H₂S to drive the production of higher-value products (H₂, HCOOH, CH₄, CO, H₂O₂, etc.). Therefore, electrochemical systems for sulfur recovery have received increasing attention. This review highlights the significance of electrochemical recovery of sulfur from H₂S. It summarizes the reaction pathways and mechanisms involved in anodic sulfur oxidation, critically analyzes and discusses methods for detecting sulfur oxidation products, and summarizes the latest advances in sulfur oxidation reaction (SOR) anode materials and various electrochemical coupling systems. The aim is to enhance the fundamental understanding of electrochemical sulfur recovery and to provide insights for the design of novel SOR electrodes and integrated electrochemical coupling systems. Full article

Approximately 3.8% of the global population suffers from depressive disorders, posing a substantial public health challenge exacerbated by the COVID-19 pandemic due to widespread unemployment and prolonged social isolation. The difficulty in objectively quantifying psychological states underscores the need for effective stress assessment methods. Herein, we developed a portable electrochemical cortisol sensor (PECS) for accurate mental stress assessment. The PECS consists of a screen-printed carbon electrode decorated with gold nanoparticles and a molecularly imprinted polymer (MIP) synthesized via electropolymerization. The as-prepared PECS demonstrates a wide and linear detection range from 1 fM to 1 μM, an ultra-low detection limit of 0.4112 fM and a high sensitivity of 15.518 nA∙lg(nM⁻¹)∙cm⁻². This work provides new possibility of developing soft bioelectronics for non-invasive and real-time mental health monitoring. Full article

This work presents the fabrication and analytical application of nanostructured Ni-zeolite (NiZY) and carbon nanohorns (CNHs) modified glassy carbon electrode (NiZY/CNHs-GCE) in the differential pulse voltammetric (DPV) determination of vitamin B₂ (VB₂) molecules. The synergistic combination of NiZY and CNHs significantly enhances the electrochemical performance of the sensor, as confirmed by structural, textural, morphological, and electrochemical studies. The redox behavior of VB₂ on NiZY/CNHs-GCE was found to be adsorption-controlled, involving a two-electron, two-proton reversible reduction process. Under optimized conditions, the DPV response of NiZY/CNHs-GCEs in McIlvaine buffer solution (pH 3.4) exhibited a linearity in the VB₂ concentration range of 0.01 to 0.20 mg L⁻¹ (r = 0.9993) with a detection limit of 3.2 µg L⁻¹ (8.6 × 10⁻⁹ mol L⁻¹). Furthermore, well-resolved reduction peaks of vitamins B₂ and B₉ (VB₉) enabled their simultaneous and selective detection, with linear ranges of 0.01 to 0.20 mg L⁻¹ for VB₂ and 0.01 to 0.16 mg L⁻¹ for VB₉. The proposed analytical method, characterized by high selectivity and robustness, was successfully applied in the determination of both vitamins in commercially available dietary supplements, achieving relative errors within −6.2% to 2.7%. Full article

Monitoring nitrate levels in water is critical to protect public health and ensure compliance with regulatory standards. This study provides a comprehensive evaluation of four analytical techniques—test strips, ion-selective electrodes (ISE), colorimetric methods, and titration—to assess nitrate levels in a variety of water sources, including standard solutions, rainwater, bottled water, and groundwater from both shallow and deep wells located in semi-urban regions of Saudi Arabia. Each method was assessed for sensitivity, accuracy, detection limits, reproducibility, and operational practicality. Test strips offer rapid, low-cost screening but consistently underestimate nitrate concentrations, particularly at low levels. The ISE demonstrated broad applicability and reliable performance across a wide concentration range when properly calibrated, making it suitable for both field and laboratory applications. Colorimetric methods provide excellent sensitivity for trace-level detection, whereas titration delivers the highest accuracy for high-nitrate samples despite its time-intensive nature. By calibrating and validating the methods against certified standards, we quantitatively demonstrated their reliability through statistical measures such as precision and accuracy rates. Moreover, the application of Geographic Information System (GIS) techniques in spatial analysis has revealed significant differences in the distribution of nitrates. Notably, shallow wells located in the northern regions surpass the 50 mg/L limit set by the World Health Organization (WHO), thereby indicating the presence of localized contamination hotspots. This study is among the first to systematically compare nitrate detection methods across a wide range of water types in a semi-urban area of Saudi Arabia. Building on a detailed analysis of each method, we underline the crucial need for the strategic selection of nitrate analysis techniques. This selection should be tailored to specific operational contexts, accuracy requirements, and concentration ranges to guide stakeholders towards more informed decision-making. These findings provide actionable guidance for public health officials and water managers to prioritize monitoring, safeguard drinking-water sources, and mitigate nitrate-related health risks in semi-urban communities. Full article

Accurate estimation of the state of health (SOH) of lithium-ion batteries is essential for the safe and efficient operation of electric vehicles (EVs). Conventional approaches, including Coulomb counting, electrochemical impedance spectroscopy, and equivalent circuit models, provide useful insights but face practical limitations such as error accumulation, high equipment requirements, and limited applicability across different conditions. These challenges have encouraged the use of machine learning (ML) methods, which can model nonlinear relationships and temporal degradation patterns directly from cycling data. This paper reviews four machine learning algorithms that are widely applied in SOH estimation: support vector regression (SVR), random forest (RF), convolutional neural networks (CNNs), and long short-term memory networks (LSTMs). Their methodologies, advantages, limitations, and recent extensions are discussed with reference to the existing literature. To complement the review, MATLAB-based simulations were carried out using the NASA Prognostics Center of Excellence (PCoE) dataset. Training was performed on three cells (B0006, B0007, B0018), and testing was conducted on an unseen cell (B0005) to evaluate cross-battery generalisation. The results show that the LSTM model achieved the highest accuracy (RMSE = 0.0146, MAE = 0.0118, R² = 0.980), followed by CNN and RF, both of which provided acceptable accuracy with errors below 2% SOH. SVR performed less effectively (RMSE = 0.0457, MAPE = 4.80%), reflecting its difficulty in capturing sequential dependencies. These outcomes are consistent with findings in the literature, indicating that deep learning models are better suited for modelling long-term battery degradation, while ensemble approaches such as RF remain competitive when supported by carefully engineered features. This review also identifies ongoing and future research directions, including the use of optimisation algorithms for hyperparameter tuning, transfer learning for adaptation across battery chemistries, and explainable AI to improve interpretability. Overall, LSTM and hybrid models that combine complementary methods (e.g., CNN-LSTM) show strong potential for deployment in battery management systems, where reliable SOH prediction is important for safety, cost reduction, and extending battery lifetime. Full article

The oxygen reduction reaction (ORR) is a crucial process in electrochemical systems, such as fuel cells, as it effectively converts oxygen into water, thereby contributing significantly to sustainable energy generation. In this study, copper oxide (CuO) thin films were deposited onto silver (Ag) substrates using a modified successive ionic layer adsorption and reaction (SILAR) method, followed by an investigation of their electrocatalytic performance toward ORR in an alkaline medium. Comprehensive electrochemical characterizations, including cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and open circuit potential (OCP), were employed to evaluate catalyst behaviour. Elemental analysis through energy-dispersive X-ray spectroscopy (EDX) confirmed the uniform distribution of CuO, while scanning electron microscopy (SEM) revealed a sponge-like surface morphology which potentially enhances catalytic efficiency. Moreover, EIS spectra revealed a lower charge transfer resistance for the CuO/Ag electrode (3.37 kΩ) compared to bare Ag (4.23 kΩ), reflecting improved ORR kinetics. Among different deposition cycles, 15 SILAR cycles yielded the highest current density of 0.8 mA cm⁻² at 0.60 V. Kinetic analysis revealed that the reaction is irreversible, with a lower value of Tafel slope (32 mV dec⁻¹) and high transfer coefficient (α = 0.45), indicating a concerted reduction mechanism. The ORR pathway was found to follow a four-electron (4e⁻) transfer process. Full article

The lithium-ion cell model is the heart of the battery management system—a more accurate model ensures operational safety, extends pack lifetime, and provides better tracking of battery charge and health. Catalyzed by the automotive industry’s shift towards electrification, optimal parameterization of the lithium-ion cell is of crucial importance. Two dominant methods of direct parameterization have emerged in the literature as the standard for parameter extraction of a lithium-ion equivalent circuit cell model. A direct comparison of their performance and suggestion as to the optimal method of cell parameterization has not yet been proposed; Thus, this paper aims to extract the optimal parameter set regarding the two dominant direct methods with an electrochemically based logic, compare the accuracy of cell parametrization over two transient load profiles, and ultimately suggest which method is preferable for electric vehicle applications. Additionally, this work will be conducted over multiple C-rates to quantify the robustness of each direct method of parameterization over a transient load profile. Full article