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Power quality enhancement of renewable energy systems using a hybrid orangutan optimization algorithm and continuous spiking graph neural network with series active power filter
Interconnected renewable energy systems (RES) often experience power quality (PQ) issues, such as harmonics and voltage disturbances. Nevertheless, conventional Series Active Power Filter (SAPF) control schemes have disadvantages, such as slow adaptation and reduced accuracy in a fluctuating renewable environment. To overcome these limitations, this work proposes a hybrid adaptive SAPF-based PQ optimization technique. The proposed method combines the Orangutan Optimization Algorithm (OOA) and Continuous Spiking Graph Neural Network (CSGNN), referred to as the OOA-CSGNN method. Reduction of total harmonic distortion (THD), increase of PQ, and stabilize of voltage profiles in interconnected RES are the goals of the proposed technique. The OOA offers the best SAPF control parameters to maximize convergence and dynamic tracking, and the CSGNN is effective to predict the compensation signals using graph-based spiking computations. The suggested technique is implemented in MATLAB and evaluated against existing approaches, such as the Gorilla Troops Algorithm (GTA), Genetic Algorithm (GA), Adaptive Bald Eagle Optimization Algorithm (ABE-OA), Artificial Neural Network (ANN), and Convolutional Neural Network (CNN). The proposed OOA-CSGNN approach achieves a load voltage THD of 0.11% under steady-state operating conditions after SAPF compensation, while maintaining voltage THD well within IEEE-519 limits during transient disturbances such as voltage sag, swell, and dip. These results demonstrate the efficiency and robustness of the proposed hybrid architecture for PQ optimization in renewable-integrated systems. 2026 Elsevier Ltd -
Experimental investigation of plain and nano-graphene oxide mixed dielectric for sustainable EDM of Nimonic alloy using Cu and Brass electrode: A comparative study
The current research investigates the machinability of a novel Nimonic alloy through electro-discharge machining by assessing Material Removal Rate, Tool Wear Rate and Surface Roughness. The machining was conducted using plain dielectric and Graphene Oxide (GO) nanoparticles (5 g/l) mixed dielectric considering both Copper and Brass electrode. The novelity lies when machining with nano GO mixed dielectric. It was observed that the use of Copper electrode in machining of the alloy in nano GO mixed dielectric results in superior quality machining, demonstrating enhanced performance. The key findings include the identification of optimal parameters, where Vg of 70 V, Ton of 200 s, Fp of 0.5 kgf/mm2 maximize MRR (16.231 mm3/min) and minimize TWR (0.0062 mm3/min) and SR (5.1423 m). The microstructural study of the machined surface and sustainability study along with the detailed comparative analysis of responses assures the superiority of machining in Nano GO mixed dielectric-Cu electrode environment. 2024 Elsevier Ltd -
Redox-active tetra-amino cobalt phthalocyanine electrocatalyst for sustainable electrochemical synthesis of 2-(pyridin-4-yl)-1H-benzo[d]imidazole
An electrocatalyst bearing a cobalt phthalocyanine derivative was developed by modifying carbon fibre paper electrode with polythiophene-3-acetic acid (pTAA) and further immobilizing tetra-amino cobalt phthalocyanine (TACoPc). The electrode was topographically and electrochemically characterized to validate its surface modification and functional suitability. This energy efficient electrocatalyst (CFP-TAA-TACoPc) was explored, for the sustainable synthesis of 2-(pyridin-4-yl)-1 H -benzo[ d ]imidazole at 1.35 V, with 87.6 1.267 % product yield at ambient conditions. o -phenylenediamine and pyridine-4-carboxaldehyde were used as starting materials, with ethanol as solvent, and lithium perchlorate as supporting electrolyte, using a three-electrode system, in a single compartment cell. The benzimidazole derivative was observed to crystallize out after completion of the reaction, negating the need for any further purification and was characterized using 1HNMR and GCMS. This work highlights the potential of electrochemical strategies as a sustainable and efficient alternative to conventional methods for heterocyclic synthesis. 2026 Elsevier B.V. -
Hemin-functionalised conducting polymer as a unique host matrix for the electrochemical synthesis of benzothiazole derivatives: A sustainable approach
An electrocatalyst based on the non-toxic and biologically derived metalloporphyrin hemin, immobilized on poly 3,4-diaminobenzoic acid (PDABA) was utilized for the sustainable electrochemical synthesis of benzothiazole derivatives. Electrochemical and topographical attributes of the electrocatalyst were analyzed critically using a ferricyanide probe, electrochemical impedance spectroscopy (EIS), X-ray photoelectron spectroscopy (XPS), optical profilometry, FTIR, and FE-SEM techniques. The modified electrode was employed for the electrochemical synthesis of benzothiazole derivatives using various aromatic aldehydes and 2-aminothiophenol. The reactions were performed in a three-electrode system, at oxidation potentials derived from cyclic voltametric elucidations, using lithium perchlorate as the supporting electrolyte and ethanol as the solvent. The products obtained were crystallized, purified and confirmed with the help of 1H-NMR spectroscopy, showing yields ranging from 78-92 %. The hemin based heterogenous electrocatalyst enhances the efficacy of the reaction by reducing reaction time, and negating tedious work-up procedures, thereby making the method highly facile and environmentally benign. 2025 -
10-camphor sulfonic acid: A simple and efficient organocatalyst to access anti-SARS-COV-2 Benzoxanthene derivatives
10-Camphor sulfonic acid (10-CSA) has gained popularity as an organocatalyst due to its broad range of solubility and user-friendliness. Affordable multicomponent reactions (MCRs) for the preparation of benzoxanthenes (4a-4 h) (5a-5i) are presented in this work. Extensive investigations and records have been conducted on the diverse biological features exhibited by xanthenes and benzoxanthenones, such as their antiviral, antibacterial, and anti-inflammatory capabilities.Using ?-naphthol, dimedone, and aldehydes, we demonstrate a cost-effective and environmentally friendly catalytic method. Under ideal circumstances, the 10-CSA catalyzes one-pot reaction, procuring impressive amounts of benzoanthenes (8595 %). All the synthesized compounds were characterized by 1H NMR and 13C NMR. A wide variety of suitable chemicals, simple work-up procedures, and solvent-free synthesis outperforms numerous existing methods for procuring biologically relevant benzoxanthene derivatives are some of the interesting features of this organocatalyzed bronsted acid process. Therefore this synthesis is industrially inevitable. Furthermore, computational studies such as molecular docking and ADMET data analysis were performed on a number of the synthesized benzoxanthene molecules. This has led to the identification of the most potent synthetic against the SARS-CoV-2 spike protein. Additionally, to mimic how medicinal compounds interact to target proteins, computational docking and dynamics techniques were used. These studies showed that, in terms of binding affinity and other crucial traits, 4a, 4b, and 5a are potential possibilities. Overall, the current study should be of great help in the development of benzoxanthene analogs which can be potential drugs for treatment of COVID-19. 2024 Elsevier B.V. -
Manganese telluride quantum dot decorated 3D printed structures for dye-degradation
The disastrous result of fast industrialization and uncontrolled industrial effluent discharge is the lack of fresh water. Scholars have endeavored to extract water from heavily contaminated industrial effluent by creating several materials capable of effective and environmental friendly treating of tainted water. In the subject of water treatment, three-dimensional (3D) printed complex architecture has shown to be an emerging technique. Recently, nanomaterials have reformed filter technology because of their improved morphological characteristics. The current study explores the uses of two-dimensional (2D) Manganese Telluride (MnTe2) quantum dots (QDs) to decorate the 3D printed architecture for wastewater treatment. The photocatalytic performance of the QDs decorated 3D printed structures was demonstrated through the degradation of organic dyes (methylene blue (MB) and methyl orange (MO) dye) in both dark and light exposure conditions. The coated structures exhibited the ability to adsorb the organic pollutant and clean the contaminated water. We observe ?78 % degradation efficiency for MB and ?48 % for MO in dye concentrations of 10 mg/100 ml. A colorimetric detection method was used for real-time detection of degradation efficacy. The obtained results indicated that QDs decorated 3D printed system can be a significant system for wastewater treatment. 2025 -
Mathematical and computational analysis of a fractional-order drug abuse model with nonlinear incidence and logistic growth
This paper presents a novel mathematical model for analyzing the dynamics of drug addiction using a fractional-order system based on the LiouvilleCaputo derivative. The proposed model incorporates a nonlinear saturated incidence rate, logistic growth in the addiction compartments, and seven interconnected subpopulations representing different stages of drug use and recovery, including relapse and awareness. We conduct a rigorous mathematical analysis to establish the existence, uniqueness, positivity, and boundedness of solutions, ensuring the epidemiological and physical validity of the model. The basic reproduction number R0 is derived, and the local and global stability of the equilibrium points is analyzed. A major contribution of this work is the application of a new domain decomposition spectral method based on second-kind Dickson polynomials, combined with the quasilinearization technique, to efficiently solve the complex nonlinear system. The convergence of the numerical method is theoretically validated. Numerical simulations are provided to illustrate the model's dynamics and to explore the impact of various parameters and intervention strategies. Compared to existing models, this study offers an improved framework for understanding memory-dependent behavior in addiction dynamics and introduces a computationally efficient approach to solve fractional-order systems with high accuracy. 2025 International Association for Mathematics and Computers in Simulation (IMACS) -
Electrochemical cobalt extraction from grinding sludge for supercapacitor applications via hydro- and solvometallurgical processes
Cobalt is a critical material for energy storage applications, including supercapacitors, but its supply is constrained by geopolitical and environmental challenges. This study presents a sustainable approach for cobalt recovery from cemented tungsten carbide grinding sludge via deep eutectic solvents (DESs) and evaluates the electrochemical performance of the recovered materials in supercapacitors. Electrochemical extraction was optimized at 4 V and 10 mA/cm2, achieving a cobalt concentration of 2900 mg/L in the DES. The cobalt was then recovered as cobalt oxalate via solvometallurgical (Route 1) and hydrometallurgical (Route 2) processes and subsequently calcined into cobalt oxide. Characterization revealed that the solvometallurgical route yielded finer, porous particles with enhanced electrochemical properties. The recovered cobalt oxalate and cobalt oxide were utilized in supercapacitor electrodes, demonstrating superior electrochemical performance when combined with activated carbon (AC). Supercapacitors incorporating cobalt oxide from route 1 with AC achieved a specific capacitance of 95 F/g, outperforming cobalt oxalate-based electrodes (89 F/g) at 1 mA/g. The AC-modified electrodes exhibited improved energy and power densities, with stable capacitance retention over 1000 cycles. Comparative analysis with direct deposition methods highlighted the multistep recovery process as a promising route for scalable cobalt recycling. This study underscores the potential of DES-based electrochemical extraction as an environmentally friendly alternative for critical metal recovery, aligning with circular economy principles and sustainable energy storage solutions. 2025 The Authors -
Characterization of Erd?s matrices by their zero entries
An Erd?s matrix E is a bistochastic matrix whose sum of squares of entries (Frobenius norm squared) equals its maxtrace (maximum value of the trace of ?E, as ? varies over permutation matrices). We characterize all Erd?s E by the patterns of their zero entries; showing that each such skeleton has at most one E. We present an algorithm to find all n Erd?s matrices, which finds them up to n?5 quickly and also size n=6. We further show some presently known RCDS matrices (E in which the trace of ?E remains constant across all the permutations that avoid every zero-entry position in E) to be Erd?s. 2026 Elsevier Inc. -
Tri-projection gated cross-modal fusion for robust multilingual emotion recognition
Existing multimodal approaches in emotion recognition (ER) rely on static or pairwise fusion strategies. These systems do not adequately address the challenges in real-world conversational systems, which require resilience to both multilingual code-switching and variable reliability of multiple modalities. We propose a transformer-based tri-modal emotion identification framework with a novel Tri-Projection Gated Cross-Modal Fusion (T-GCMF) module the first multimodal emotion recognition architecture explicitly designed for code-switched conversational input. T-GCMF simulates tri-modal interactions by explicitly calculating modality-specific confidence and cross-modal consistency, allowing for dynamic suppression of unreliable modalities during inference. Acoustic and visual cues are retrieved using CNNLSTM and deep CNN encoders, respectively. Textual representations are generated using XLM-RoBERTa to handle code-switched language reliably. We introduce Hinglish-MELD, the first multimodal emotion recognition dataset with aligned text, audio, and visual streams containing code-switched conversational content, filling a critical gap in the literature. With an accuracy of 88.3% and an F1-score of 87.0, the suggested confidence-aware fusion technique greatly surpasses unimodal, monolingual, and non-gated multimodal baselines. These findings demonstrate T-GCMF as a successful approach for emotion recognition in linguistically heterogeneous, real-world interactive systems and emphasize the significance of confidence-driven tri-modal integration. 2026 -
A novel wide slice kronecker forward fractional network for osteoporosis detection using knee X-ray image
Osteoporosis is an asymptomatic and progressive skeletal disorder that maximizes the risk of fractures in people aged 50 to 60. Early and accurate detection is critical, yet challenging, due to the fine structural changes in bone that are often difficult to identify in routine medical images. Knee X-rays are commonly used diagnostic tools, but interpreting them for osteoporosis detection remains complex because of variations in bone geometry and trabecular patterns. To solve these challenges, the novel Wide Slice Kronecker Forward Fractional Network (WKFF-Net) is developed to detect osteoporosis efficiently. Initially, the input image is taken from the database for detection. Here, the denoising process is done using the Non-Local Means (NLM) filter, and the Otsu thresholding method is considered for the segmentation process. Further, a template search method is used for analyzing the femur geometry. Next, features, like spatial, adaptive Local Binary Patterns (aLBP), Convolutional Neural Networks (CNN), and medical-level features, are extracted, and osteoporosis detection is accomplished by the hybrid WKFF-Net model that integrates Deep Kronecker Network (DKN), Wide Slice Residual Network (WISeR), and fractional calculus. The experimental results obtained by the WKFF-Net are 90.868% accuracy, 92.876% True Positive Rate (TPR), 87.766% True Negative Rate (TNR), 89.888% precision, and 91.357% F1-score, for 90% of the training samples. 2026 Elsevier B.V. -
Adaptive optimization with reinforcement learning for high utility itemset extraction
Extraction of High Utility Itemsets (HUI) plays a vital role in data mining that comprises several techniques developed to address it efficiently. However, when dealing with large itemsets and diverse items in a dataset, the problem's search space becomes notably complex and expansive. This makes the task of identifying HUIs more computationally expensive and time-consuming. In this paper, a novel Optimized Coverage list unit utilities-based High Utility Itemset (OCHUI) extraction approach is introduced for High Utility Itemset extraction. The extraction of high utility patterns and the extraction of qualified high utility itemsets are the two main processes in the suggested method. In the first step, high utility patterns are identified by mining metrics such as Redefined transaction-weighted utility, positive and negative Unit profit, Purchase quantity, and Coverage (RUPC) from the dataset. In the second step, qualified high utility itemsets are obtained optimally using an adaptive optimization algorithm called Cuckoo search Assisted Ant colony Optimization with Reinforcement Learning (CAAO-RL) is proposed. The Reinforcement Learning (RL) uses the On and Off policy method to intelligently leverage the tuning parameter of optimization. The RUPC model obtained the pattern score of 13600, runtime rate of 10.256 s and memory usage of 198 MB, respectively. 2025 Elsevier B.V. -
A statistical approach to study anatomical changes of pink guava cultivar (Psidium guajava L. cv Arka Kiran) during its ripening at the room temperature storage
The ripening of climacteric fruit like guava is a complex process that is highly coordinated with its cellular backbone. In the present study, we combined microscopy, spectrophotometry, and statistical analysis to evaluate the anatomical changes in the pink variety of guava during five ripening stages (pre-ripe, ripe, color-turn, half over-ripe, and over-ripe) during its storage at room temperature (282 C). The cholorophyll content of the peel, as determined by the measurement of chlorophyll a, b, and total chlorophyll, showed a significant decrease during the maturation process (4.05, 4.53, and 8.62 ?g/cm2, respectively, in the pre-ripe stage to not detectable in the over-ripe stage). Gradual loss of integrity of the fruit pulp (pericarp) from the preserved bee-hive structure to cell mass was also monitored by studying the cellular anatomy with brightfield and scanning electron microscopy. The epidermal thickness and width of the cortical parenchyma cells revealed statistical differences from the initial pre-ripe stage to the final full-ripe stage. Finally, based on the cellular dimensions, multivariate analysis using PCA (Principal Component Analysis) tool grouped the stages into three clusters, namely, pre-ripe: ripe, color-turn: half-over ripe, and over-ripe stages. In conclusion, this study provided significant insights into cultivar-specific anatomical changes in guava fruit, with potential for future research to develop variants with longer post-harvest storage life. 2024 The Author(s) -
Dual strategy for enhanced photocatalytic degradation of tetracycline: Phosphorus doping and cobalt boride co-catalyst loading on g-C3N4
Despite being promising for the removal of ever-growing pharmaceutical contamination from water, the g-C3N4 photocatalyst still faces roadblocks to implementation due to its intrinsic properties, for example, the limited visible light absorption, reduced charge separation capacity, and low mobility of photo-excited electrons. Doping with non-metals and loading with the co-catalyst is an effective approach to overcome the abovementioned limitations for the g-C3N4 photocatalyst. Herein, both these strategies are integrated in cobalt-boride loaded on phosphorous-doped g-C3N4 (CoB/P-g-C3N4) by facile chemical fabrication routes. Detailed morphological, structural, chemical, and spectroscopic analyses demonstrated that phosphorus doping effectively reduces the bandgap of g-C3N4 to absorb more visible light. Uniformly distributed CoB-nanoparticles create local Schottky barriers that trap photo-generated electrons from g-C3N4 to suppress charge carrier recombination. The optimized CoB/P-g-C3N4 photocatalyst produces ~35 times higher degradation rate constant than the pristine g-C3N4 for the photocatalytic removal of tetracycline antibiotics from water under visible light irradiation. Combining these advantageous features with cost-effective and stable elements, CoB/P-g-C3N4 offers an optimal solution for tuning the intrinsic electronic structure and surface reactivity of g-C3N4, making it highly effective for various photocatalytic applications. 2025 Elsevier Ltd -
Aggressive driving and ADHD symptoms in young male drivers: Examining the roles of personality traits and driving anger
Introduction Aggressive driving behaviors are linked to attention-deficit/hyperactivity disorder (ADHD) symptoms, yet the moderating roles of personality traits and driving anger remain underexplored, particularly among two-wheeler riders in low- and middle-income countries (LMICs). This study examined associations between aggressive driving violations and ADHD symptom severity, focusing on neuroticism and driving anger as moderators. Methods A cross-sectional survey was conducted with 150 male postgraduate two-wheeler riders in India. ADHD symptoms were assessed using the Adult ADHD Self-Report Scale, aggressive driving violations via the Extended Driver Behaviour Questionnaire, driving anger using the Deffenbacher Driving Anger Scale, and personality traits through the 10-item Big Five Inventory. Multiple regression and moderation analyses were performed. Results Aggressive driving violations significantly predicted ADHD symptom severity (p < .001), independent of driving anger and neuroticism. A marginal interaction with neuroticism (p = .068) suggested a stronger association at lower neuroticism levels. Driving anger did not significantly moderate this relationship. Age and helmet non-use were also independently associated with ADHD symptoms (p = .045 and p = .024, respectively). Conclusions Aggressive driving violations show a stable association with ADHD symptom severity in young male two-wheeler riders in an LMIC context, with preliminary evidence for neuroticism as a moderator. These findings underscore the need for personality-informed interventions addressing self-regulatory and behavioral aspects of driving behavior in ADHD populations. 2025 Elsevier Ltd. -
Hybrid bimetallic sulfide (FeCoS)-doped conductive polymer as efficient oxygen evolution reaction electrocatalyst for direct seawater electrolysis
Seawater electrolysis is critical for sustainable hydrogen production, especially in regions facing freshwater scarcity. However, chloride ions compete through parasitic reactions, such as the chlorine evolution reaction, creating a serious challenge that reduces catalytic activity and durability. Herein, a hybrid electrocatalyst composed of FeCoS embedded in a polyaniline matrix (FCS-PANI) is synthesized using a simple hydrothermal method. This fabricated composite combines the benefits of the high catalytic activity of FeCoS and the corrosion resistance of the conductive polymer (PANI). Structural analysis establishes the formation of a uniform nanocomposite with strong metalsulfur and metalnitrogen interactions. Advanced oxygen evolution reaction (OER) performance with a low overpotential of 327?mV at 30?mA?cm?2 and a Tafel slope of 38.67?mV dec?1 is achieved through electrochemical testing in alkaline seawater. High stability, low degradation (0.3?mV?h?1) over 500?h of operation, and 99.97% hydrogen purity are observed upon integration into an anion exchange membrane water electrolyzer (AEMWE), indicating its practical potential for seawater electrolysis. 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Nanoarchitechtonics of high surface area carbon material for coin cell supercapacitor application
Advancing energy storage systems thrive on innovative electrode materials, balancing sustainable synthesis with enhanced electrochemical performance. In the present work, a feasible approach for developing a carbon derivative exhibiting all the promising features of a superior electrode material is reported. Nitrogen and Sulfur are strategically incorporated into the carbonaceous material along with Potassium-based activation, such that additional pseudocapacitance, along with an enhanced surface area are achieved. Carbon derived from charcoal is co-functionalised with Nitrogen and Sulfur via a two-step pyrolysis technique, resulting in a material that exhibits improved surface area of 1488.8m2g?1 and enhanced electrochemical performance. It showcases a gravimetric capacitance of 689Fg?1 and 295Fg?1 at 1Ag?1, corresponding to the three and two-electrode setups respectively. A gravimetric capacitance of 425Fg?1 is maintained at a high current density of 50Ag?1 with a capacitance retention of 61.6 %. A sustained energy density of 20.50W h kg?1 at a power density of 3.1kWkg?1 is achieved by this material with a stability of 94 % for 5000 cycles at 2Ag?1. In addition, coin cells fabricated with the as-prepared material demonstrated the real-world feasibility by illuminating LEDs of different colors. 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Evaluating the electrochemical performance of single and multiple heteroatom doped carbon black from waste tires for supercapacitor application
With the growing emphasis laid on the research related to energy storage systems, the need for cost-effective and efficient materials is quintessential. The present work reports a comprehensive study and a promising strategy to enhance the electrochemical behaviour of Carbon Black derived from waste tires by the incorporation of heteroatoms such as Nitrogen and Sulfur into the system. The study investigates the electrochemical performance of Carbon Black with single doping, and further examines the enhanced performance with co-doping. While the Nitrogen-doped Carbon Black exhibits a specific capacitance of 97.63F/g, the Sulfur doped Carbon Black exhibits 141.8F/g and the co-doped Carbon Black exhibits an enhanced specific capacitance of 233F/g at a current density of 1 A/g in the two-electrode system. A significant improvement in the specific surface area is achieved in the materials with post-doping techniques. Furthermore, the co-doped Carbon Black provides superior electrochemical behaviour with sustained energy density of 30Wh/kg even at a higher power density of 5.6kW/kg with an improved cyclic stability of 91% over 5000 cycles. Thus, effective valorization of Carbon Black recovered from waste tires enables the development of efficient and affordable electrode material for the fabrication of supercapacitors. 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
One dimensional NiMn2O4 nanofibrous architectures for symmetric supercapacitor device
In this study, NiMn2O4 nanofibers are synthesized using an electrospinning method. The NiMn2O4 nanofiber films, coated on stainless-steel substrates, are electrochemically characterized in different electrolytes, including KCl, KOH, NaOH, and Na2SO4. The study explores how the choice of electrolyte influences the specific capacitance, galvanostatic charge-discharge behavior, cycle stability, and capacitance retention of the NiMn2O4 nanofiber electrodes. NiMn2O4 electrodes in KOH exhibit superior performance at a scan rate of 5 mV/s, with an areal capacitance of 2125 F/g. The higher capacitance in KOH is attributed to its high ionic conductivity and efficient ion mobility. Additionally, the NiMn2O4 nanofiber electrodes demonstrate excellent cycle stability, with 76.38 % capacitance retention in 1 M KOH. These results suggest that 1D NiMn2O4 nanofiber electrodes deliver superior electrochemical performance in KOH compared to other aqueous electrolytes, highlighting their potential for future electrochemical energy storage applications. Furthermore, the flexible symmetric supercapacitor device shows excellent flexibility and electrochemical stability, with specific energy of 660 Wh/kg and specific power of 140 kW/kg obtained at a current density of 2 mA/cm2. These findings indicate that 1D NiMn2O4 nanofibers, particularly in 1 M KOH, are promising candidates for high-performance supercapacitor applications, paving the way for advancements in electrochemical energy storage devices. 2025 Elsevier B.V. -
Synergistic enhancement of bifunctionality in Ni-doped VO2 (B) nanostructures: A pathway for improved water electrocatalysis
The global energy demand led to the exploration of techniques to produce green hydrogen, such as water electrolysis, as a future fuel for energy management. However, the efficiency of hydrogen evolution (HER) during this electrocatalysis is usually regulated by the proficiency of the catalyst in generating a facile oxygen evolution reaction (OER). In this work, the robust bifunctionality of Ni-doped VO2(B) as an electrocatalyst for hydrogen and oxygen evolution reactions is investigated. The optical characterization uncovered the semiconducting nature of nanoflake-like VO2(B) nanostructures. Furthermore, optimizing Ni concentration resulted in significant reduction of overpotentials from 518 mV to 289 mV for HER and from 435 mV to 404 mV for OER under a current density of 10 mA/cm2. This excellent electrochemical efficiency of the Ni-doped VO2(B) nanostructures is further showcased by the low Tafel slope values of 129 mV/dec and 99 mV/dec for HER and OER, respectively. Consistent with these findings, the materials exhibited minimal charge transfer resistance of 57.1 ?, reinforcing the superior electrocatalytic activity. Additionally, the chronopotentiometric studies confirmed the long-term stability of the nanostructures. Altogether, Ni-doped VO2(B) nanostructures can be considered as a potential electrocatalyst for overall water electrolysis, laying the foundation for a sustainable energy future. 2025 Elsevier B.V.