The European Physical Journal Plus最新文献

Long-term, high-performance nanocatalyst development requires environmentally friendly synthesis, defect engineering, and multifunctionality. CuFe₂O₄ nanospinels were ecologically produced using phytogenic combustion and bioactive fuels derived from Plumeria rubra and Caesalpinia pulcherrima. The lattice constants were 4.46 and 4.88 Å, while the Plumeria and Caesalpinia crystallites had sizes of 11.56 and 10.82 nm, respectively. FESEM analysis revealed semi-spherical nanoparticles with diameters of 35.0 and 36.7 nm. UV–Vis spectroscopy revealed that Plumeria and Caesalpinia defects serve as mediators of strong electronic transitions. The indirect bandgap is 2.22 eV, while the direct bandgap is adjustable up to 2.60 eV. Photoluminescence emission at 486–624 nm revealed oxygen vacancies, antisite disorder, mixed-valence Cu⁺/Cu³⁺ and Fe³⁺ centres, and Jahn–Teller distortions. Electrochemical profiling revealed reversible redox processes with peak currents of 1.95 mA and −1.83 mA, providing sensitive biosensing capabilities. The CuFe₂O₄ electrode's rapid electron-transfer kinetics and numerous electroactive sites resulted in low detection limits of 0.172 μM for L-histidine and 0.329 μM for D-fructose. Plumeria nanoparticles had a higher radical-quenching efficiency (IC₅₀) of 107.42 mg mL⁻¹ in DPPH-based antioxidant tests than Caesalpinia nanoparticles (IC₅₀) of 978.16 mg mL⁻¹. After 120 min of sunlight exposure, the Plumeria catalyst reduced anthocyanin dyes by 71.84%, while the Caesalpinia catalyst reduced them by 75.86%. Kinetic analysis confirmed the pseudo-first-order behaviour at rate constants of 0.0106 and 0.0114 per minute. The two catalysts' efficiency remained between 65 and 69% after four degradation cycles. This study uses phytogenic combustion to create CuFe₂O₄ nanospinels that are defect-free, optoelectronically flexible, and catalytically stable. They are scalable nanomaterials with a wide range of beneficial properties, including antioxidant, photocatalytic, structural, optical, electrochemical, and advanced biosensing capabilities, as well as pollution degradation and multifunctional catalysis.

This study investigated the electrochemical characteristics of NdFeO₃ nanocomposite improved with added small quantity of MXene. The NdFeO₃/MXene was synthesized using a standard solve-thermal technique and analyzed using X-ray diffraction, Fourier Transform Infrared Spectroscopy, etc . The electrochemical efficiency of the composite was tested for supercapacitors (SCs). The compositive was investigated in 3 M KOH electrolytic solution where NdFeO₃/MXene was pasted on nickel foam and served as working electrode. CV revealed that NdFeO₃/MXene has reached the capacitance of 1148.12 F g⁻¹ (5 mV s⁻¹). GCD research revealed that NdFeO₃ nanoparticles along with NdFeO₃/MXene nanocomposite had capacitance values of 703.17 F g⁻¹ as well as 1315.06 F g⁻¹ at 1 A g⁻¹. The NdFeO₃/MXene indicated that greater E_d along with P_d is 17.99 Wh kg⁻¹, 510 W kg⁻¹. After 4700 cycles, the material containing NdFeO₃/MXene nanocomposite remained stable. Chrono test confirmed high stability of composite material. The electrochemical investigation of generated NdFeO₃ nanocomposite shown that addition of MXene caused in a hybrid capacitive nature, as the suggested NdFeO₃/MXene can be used as SCs electrodes in energy storage. The NdFeO₃/MXene nanocomposite exhibits excellent electrochemical performance as compared to previously reported perovskite–MXene, due to its optimized hetero-interface, greater electrical conductivity, as well as abundant redox active site. The incorporation of NdFeO₃ enhanced pseudo-capacitive behavior, while MXene provides quick electron transport pathway, resulting in higher specific capacitance, outstanding rate capability, and cyclic stability to earlier perovskite–MXene.

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This study presents the first systematic molecular dynamics investigation of polyethylene (PE) and polypropylene (PP) nanocomposites reinforced with randomly functionalized single-walled carbon nanotubes (SWCNTs). Armchair (8,8) and zigzag (14,0) SWCNTs with nearly identical diameters (10 Å) were functionalized with hydrogen and fluorine atoms at 5–25% functionalization levels and incorporated into polymer matrices at 10% volume fraction. Representative volume elements (RVEs) were subjected to tensile loading simulations up to failure using Tersoff and Dreiding potentials to quantify Young’s modulus, maximum stress, failure strain, strain energy, and toughness. Results demonstrate that increasing functionalization consistently reduces mechanical properties across all systems, with Young’s modulus decreasing from range of 60–70 GPa to the range of 40–50 GPa and maximum stress declining from around 11 GPa. Zigzag SWCNTs generally outperformed armchair configurations in stiffness and strength, while armchair SWCNTs exhibited superior strain capacity. PE-based nanocomposites showed slightly better performance than PP-based systems for certain properties. Although CNT–polymer nanocomposites have been widely studied, a systematic comparison of randomly applied hydrogen and fluorine functionalization in both PE and PP matrices has not been conducted before. Comprehensive comparative analysis between functionalization types, polymer matrices, and nanotube chiralities provides essential design guidelines for optimizing nanocomposite performance in various applications.

In this paper, a secure image hashing algorithm is proposed for content authentication. A novel algorithm termed Robust Feature-Guided Gridded Region Localization is designed first. This algorithm is utilized to locate highly discriminative regions with both robustness and uniform distribution. Then, the local and global structural features are extracted in parallel from these regions by employing spatial-topological kernel principal component analysis and rapid structure-preserving two-dimensional principal component analysis, and are subsequently combined to form the intermediate hash. To enhance security, a two-dimensional tent cubic coupling mapping with hyperchaos is further proposed to encrypt the hash. Experimental results demonstrate that the proposed algorithm possesses good robustness and discriminative properties when compared with recent baseline algorithms.

In the region of superheavy nuclei, where experimental data are scarce, theoretical calculations of separation energies and masses are vital for understanding their properties and potential stability. In this work, we calculate the proton and neutron separation energies for superheavy nuclei in the framework of a two-body model. To this aim, we first consider a nucleus as a two-body system, so using the Schrödinger equation in the presence of a nonrelativistic potential including the magnetic moments and Coulomb interactions, we determine the mass equation of the nuclei, analytically. Having the analytical solutions, we compute the ground-state mass of superheavy nuclei including Rf, Db, Sg, Bh, Hs, Mt, Ds, and Rg as well as the one- and two-nucleon separation energies. Our theoretical results are compared with the existing experimental data.

Background

In audio and speech signal processing, speech enhancement is thought of as a significant task. Speech improvement intends to improve the accessibility and excellence of an audio signal that has been weakened by ambient noise. The research on speech enrichment is the toughest process because of the degree of degradation of the speech signals. Diverse strategies for speech improvement are used based on the type of weakening and noise in the speech signal. As a result, the research in this area is still difficult, particularly when handling reverberation and extremely irregular noise. In this study, an enhanced speech enhancement framework is created using optimized deep learning techniques to improve both the quality and clarity of speech signals. At first, the required speech signal is collected from online resources. Further, the collected speech signal is directly passed to atrous convolution-based adaptive Trans-UNet (ACAT-UNet) with a novel loss function to attain the enhanced speech signal. Here, the loss function is incorporated with the deep learning model to enhance speech intelligibility. Furthermore, the speech enhancement performance of the ACAT-UNet is enhanced by fine-tuning the hyperparameters using the Updated Randomized Variable-based Aquila Optimizer (URVAO). The efficacy of the recommended speech improvement system is evaluated by conducting extensive simulations and experiments by contrasting it with other existing SE techniques. The numerical findings revealed that the suggested approach attained a root mean square error (RMSE) value of 0.226779.

In the present work, we intend to study the Ramsauer–Townsend effect in the scattering of muon by light and heavy nuclei. This scattering provides a precise probe of nuclear charge and matter distributions, playing a critical role in testing nuclear structure models and refining fundamental interaction theories. For our purpose, we investigate the scattering of muon in the framework of generalized uncertainty principle (GUP). We first derive the modified nonrelativistic and relativistic wave equations due to the minimal length in the GUP framework and then determine the wave function of the incident particle by applying the scattering potential due to the nuclear mean field. In the following, we calculate the transmission and reflection probabilities from the square potential well. Finally, the Ramsauer–Townsend effect will be studied, and it will be shown that some exotic phenomena occur in this framework, which cannot be explained by conventional quantum mechanics.

A single-degree-of-freedom periodically forced oscillator with coupled clearance and friction nonlinearities is investigated. By analyzing the phase-space conditions governing free sliding, impact, and stick motion, and employing associated Poincaré maps, the dynamics of stick–slip periodic motions are systematically characterized. Particular emphasis is placed on the distribution and transition of periodic motions in the two-parameter space. The occurrence of bursting oscillations in the low-frequency region is revealed and the influence of key structural parameters on stick–slip behavior is examined. The results indicate that stick–slip motion predominantly occurs in regions characterized by low-frequency and small-clearance. Under the induction of grazing bifurcations, the transition toward stick motion is marked by an increase in the number of impacts, a decrease in impact velocity, and a contraction of the frequency band. The transitions between adjacent periodic motions are primarily governed by the synergistic effects of grazing, saddle-node, and sliding bifurcations. Owing to the irreversibility of the transition paths, multi-stability regions emerge, including co-existing states induced by grazing-(saddle-node), grazing-sliding, and doubling-sliding bifurcations. Furthermore, the increase in damping ζ suppresses multi-impact motions, resulting in improved system smoothness and stability along with reduced structural wear; however, it concurrently induces a rise in energy consumption.

Electromagnetic induction is crucial for understanding the heart’s electrical and chemical dynamics and detecting functional abnormalities. In this study, we examine a modified FitzHugh-Nagumo (FHN) model incorporating standard diffusion and a feedback gain parameter. Through multiple-scale expansion, we derive a cubic-quintic complex Ginzburg-Landau (CQCGL) equation governing action potential dynamics, and we construct traveling wave solutions using a modified Hirota bilinear method (HBM). The feedback gain markedly affects action potentials: (i) On the left side, it reduces amplitude, period, and depolarization/repolarization duration before the transition region. (ii) On the right side, it produces a quasi-periodic structure at (k_{0}=,0.64), favoring rhythm stabilization. Modulational instability (MI) analysis shows that values of (k_{0}) below or above 0.64 destabilize the system. Numerical simulations closely match the analytical results, confirming the model’s validity. Biologically, these findings highlight electromagnetic induction as a key modulator of cardiac function, influencing action potentials through ion-channel regulation and gap junction coupling, and shaping arrhythmia dynamics.

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