Search Results (821)

The recycling of spent lithium-ion batteries (LIBs) requires efficient and sustainable methods for recovering critical metals. In this study, the leaching behavior of LiCoO₂ cathode material obtained from spent LIBs was investigated in phosphoric acid, using copper powder recovered from waste LIBs as a reducing agent. Leaching experiments were conducted under various conditions (temperature, solid-to-liquid ratio, agitation rate) and compared with systems without copper. In the absence of copper, lithium and cobalt, recoveries after 30 min were approximately 77% and 23%, respectively. The addition of copper significantly enhanced leaching, achieving >96% recovery for both metals at 80 °C, with most extraction occurring within the first 30 min. Kinetic analysis using the shrinking core model indicated a mixed-control mechanism involving both surface chemical reaction and product layer diffusion. The calculated activation energies were 20.2 kJ·mol⁻¹ for lithium and 16.1 kJ·mol⁻¹ for cobalt. Solid residues were characterized by X-ray diffraction (XRD) and scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS). XRD results revealed that the composition of the residues varied with leaching temperature: Co₃O₄ was consistently detected, whereas Cu₈(PO₃OH)₂₍PO₄)₄·7H₂O appeared only when leaching was performed above 50 °C. Thermodynamic calculations supported the reductive role of copper and provided insight into possible reaction pathways. These findings confirm the effectiveness of copper-mediated leaching in phosphoric acid and demonstrate that temperature strongly influences residue phase evolution, thereby offering valuable guidance for the design of sustainable LIB recycling processes. Full article

Based on the two-dimensional reaction–diffusion model, the spatiotemporal dynamical characteristics of the semi-discrete pine–Monochamus alternatus system with cross-diffusion and convection effect were studied in this work. Firstly, the stability conditions of the equilibrium point were obtained through linear stability analysis and Lyapunov coefficients, as well as the Andronov–Hopf bifurcation, which explained the reason for the periodic outbursts of the Lyapunov population from a dynamic perspective. Subsequently, through the characteristic equations of the Laplace operator ${\mathrm{\nabla }}^2$ and the gradient operator ∇, the critical discrimination conditions for the occurrence of Turing instability in the system were obtained and revealed that the phenomenon of frequent damage to pine caused by the pink Monochamus is in the form of patches. Finally, the reliability of the theoretical analysis was verified through numerical simulation, and the dual effect of convection was clearly found in the system. Moderate convection can change the pattern shape, while strong convection produces a “washout effect”, completely inhibiting the formation of the pattern. This indicates that factors such as wind or the directional migration of Monochamus alternatus significantly affect the spatial distribution pattern of pests. Therefore, the theoretical research on Turing instability of models with convection terms may provide inspiration for subsequent studies. Full article

An asymmetric four-chamber redox flow desalination cell was developed to enhance ion transport and energy efficiency by controlling chamber geometry, applied voltage, and electrolyte flow rate. The design integrates thick outer redox chambers with thin desalination chambers to promote uniform redox reactions and stable mass transfer. The system operated stably for 12 h and achieved a high salt removal rate of approximately 1226 mmol·m⁻²·h⁻¹ at 1.0 V with low specific energy consumption of about 99.74 kJ·mol⁻¹, demonstrating both durable operation and highly promising desalination performance. Electrochemical impedance analysis further confirmed that increased electrolyte flow reduces charge-transfer and diffusion resistances, enabling faster ionic transport. These findings highlight the originality of the chamber-asymmetric design and its promise for compact, low-voltage redox flow systems. This work provides design guidelines for next-generation flow-based desalination systems and suggests future research directions in scaling the architecture, optimizing flow-channel geometry, and integrating higher-stability redox electrolytes for long-term practical operation. Full article

Sodium-ion batteries (SIBs) have arisen as a potential alternative to lithium-ion batteries (LIBs) as a result of the abundant availability of sodium resources at low production costs, making them in line with the United Nations Sustainable Development Goals (SDGs) for affordable and clean energy (Goal 7). The current review intends to comprehensively analyse the various modification techniques deployed to improve the performance of cathode materials for SIBs, including element doping, surface coating, and morphological control. These techniques have demonstrated prominent improvements in electrochemical properties, such as specific capacity, cycling stability, and overall efficiency. The findings indicate that element doping can optimise electronic and ionic conductivity, while surface coatings can enhance stability in addition to mitigating side reactions throughout cycling. Furthermore, morphological control is an intricate technique to facilitate efficient ion diffusion and boost the use of active materials. Statistically, the Cr-doped NaV_1−xCr_xPO₄F achieves a reversible capacity of 83.3 mAh/g with a charge–discharge performance of 90.3%. The sodium iron–nickel hexacyanoferrate presents a discharge capacity of 106 mAh/g and a Coulombic efficiency of 97%, with 96% capacity retention over 100 cycles. Furthermore, the zero-strain cathode Na₄Fe₇(PO₄)₆ maintains about 100% capacity retention after 1000 cycles, with only a 0.24% change in unit-cell volume throughout sodiation/desodiation. Notwithstanding these merits, this review ascertains the importance of ongoing research to resolve the associated challenges and unlock the full potential of SIB technology, paving the way for sustainable and efficient energy storage solutions that would aid the conversion into greener energy systems. Full article

Studies have shown that natural organic matter can regulate pollutant behavior through multiple pathways; however, research on the environmental behavior of veterinary antibiotics (VAs) in typical alkaline calcareous loess soil under the influence of exogenous organic matter remains limited. This study investigated the influence of humic acid (HA), as a representative of natural organic matter, on the sorption behavior of ciprofloxacin (CIP) in sierozem—a typical alkaline calcareous loess soil. Using the batch equilibrium method, we examined how HA affects CIP sorption under various environmental conditions to better understand the environmental fate of VAs in soil–water systems with low organic matrix content. Results showed that CIP sorption onto sierozem involved both fast and slow processes, reaching equilibrium within 2 h, with sorption capacity increasing as HA concentration increased. Kinetic data were well described by the pseudo-second-order model regardless of HA addition, suggesting multiple mechanisms governing CIP sorption, such as chemical sorption reaction, intraparticle diffusion, film diffusion, etc. Sorption decreased with increasing temperature both before and after HA amendment, indicating an exothermic process. Isotherm analysis revealed that both the Linear and Freundlich models provided excellent fits (R² ≈ 1), implying multilayer sorption dominated by hydrophobic distribution. In ion effect experiments, cations at concentrations above 0.05 mol/L consistently inhibited CIP sorption, with inhibition strength following the order: Mg²⁺ > K⁺ > Ca²⁺ > NH₄⁺, and intensifying with increasing ionic strength. However, HA addition significantly mitigated this inhibition, likely due to complexation between HA’s functional groups (e.g., carboxyl and hydroxyl) and cations, which reduced their competitive effect and enhanced CIP sorption. pH-dependent experiments indicated stronger CIP sorption under acidic conditions. HA addition increased soil acidity, further promoting CIP retention. In summary, HA enhances CIP sorption in sierozem by providing additional sorption sites and modifying soil surface properties. These findings improve our understanding of how exogenous organic matter influences the behavior of emerging contaminants such as antibiotics in soil–water systems, offering valuable insights for environmental risk assessment in semi-arid agricultural regions. Full article

Tumor angiogenesis models based on coupled nonlinear parabolic partial differential equations require solving stiff systems where explicit time-stepping methods impose severe stability constraints on the time step size. Implicit–Explicit (IMEX) schemes relax this constraint by treating diffusion terms implicitly and reaction–chemotaxis terms explicitly, reducing each time step to a single linear system solution. However, standard Gaussian elimination with partial pivoting exhibits cubic complexity in the number of spatial grid points, dominating computational cost for realistic discretizations in the range of 400–800 grid points. This work presents a CUDA-based parallel algorithm that accelerates the IMEX scheme through GPU implementation of three core computational kernels: pivot finding via atomic operations on double-precision floating-point values, row swapping with coalesced memory access patterns, and elimination updates using optimized two-dimensional thread grids. Performance measurements on an NVIDIA H100 GPU demonstrate speedup factors, achieving speedup factors from 3.5× to 113× across spatial discretizations spanning $M\in [25,800]$ grid points relative to sequential CPU execution, approaching 94.2% of the theoretical maximum speedup predicted by Amdahl’s law. Numerical validation confirms that GPU and CPU solutions agree to within twelve digits of precision over extended time integration, with conservation properties preserved to machine precision. Performance analysis reveals that the elimination kernel accounts for nearly 90% of total execution time, justifying the focus on GPU parallelization of this component. The method enables parameter studies requiring $\sim {10}^4$ PDE solves, previously computationally prohibitive, facilitating model-driven investigation of anti-angiogenic therapy design. Full article

In this paper, we study the local stability of an incommensurate fractional reaction–diffusion glycolysis model. The glycolysis process, fundamental to cellular metabolism, exhibits complex dynamical behaviors when formulated as a nonlinear reaction–diffusion system. To capture the heterogeneous memory effects often present in biochemical and chemical processes, we extend the classical model by introducing incommensurate fractional derivatives, where each species evolves with a distinct fractional order. We linearize the system around the positive steady state and derive sufficient conditions for local asymptotic stability by analyzing the eigenvalues of the associated Jacobian matrix under fractional-order dynamics. The results demonstrate how diffusion and non-uniform fractional orders jointly shape the stability domain of the system, highlighting scenarios where diffusion destabilizes homogeneous equilibria and others where incommensurate memory effects enhance stability. Numerical simulations are presented to illustrate and validate the theoretical findings. Full article

This paper addresses the asymptotic synchronization problem for networked nonlinear reaction–diffusion systems under a novel hybrid control strategy. The hybrid controller consists of two components: impulsive control and continuous feedback control. By combining the comparison principle of impulsive systems with the introduction of a time-varying function and a power exponent to flexibly adjust the system, sufficient conditions for synchronization of networked nonlinear reaction–diffusion systems are derived, ensuring that the error dynamics between the network nodes converge to zero. Numerical simulations of a representative example are presented to demonstrate the practical validity and effectiveness of the proposed theoretical control scheme, confirming that the hybrid controller successfully achieves synchronization. Full article

This study presents a novel strategy for controlling the orientation of MoS₂ films on thick metallic substrates through precise regulation of the sulfur flux alone. In contrast to previous approaches that rely on substrate modifications or complex parameter tuning, orientation control is achieved here solely by adjusting the sulfur concentration during the sulfurization of 400 nm RF-sputtered Mo films. The metallic Mo substrate also allows potential film transfer via selective etching—analogous to the graphene/Cu system—providing a viable route for device integration on arbitrary substrates. Analyses (XRD, Raman, and TEM) reveal that low sulfur flux (30–50 sccm) favors horizontal growth, whereas high flux (>300 sccm) induces vertical orientation. To rationalize this behavior, a reaction-diffusion model based on the Thiele modulus was developed, quantitatively linking sulfur flux to film orientation and identifying critical thresholds (~50 and ~300 sccm) governing the horizontal-to-vertical transition. This unified approach enables the realization of distinct MoS₂ orientations using identical materials and processes, analogous to the orientation control in graphene growth on copper. The ability to grow orientation-controlled MoS₂ on non-noble metal substrates opens new opportunities for integrating electronic (horizontal) and catalytic (vertical) functionalities, thereby advancing scalable manufacturing of TMDC-based technologies. Full article

The FitzHugh–Nagumo (FHN) equation in one dimension is solved in this paper using an improved physics-informed neural network (PINN) approach. Examining test problems with known analytical solutions and the explicit finite difference method (EFDM) allowed for the demonstration of the PINN’s effectiveness. Our study presents an improved PINN formulation tailored to the FitzHugh–Nagumo reaction–diffusion system. The proposed framework is efficiently designed, validated, and systematically optimized, demonstrating that a careful balance among model complexity, collocation density, and training strategy enables high accuracy within limited computational time. Despite the very strong agreement that both methods provide, we have demonstrated that the PINN results exhibit a closer agreement with the analytical solutions for Test Problem 1, whereas the EFDM yielded more accurate results for Test Problem 2. This study is crucial for evaluating the PINN’s performance in solving the FHN equation and its application to nonlinear processes like pulse propagation in optical fibers, drug delivery, neural behavior, geophysical fluid dynamics, and long-wave propagation in oceans, highlighting the potential of PINNs for complex systems. Numerical models for this class of nonlinear partial differential equations (PDEs) may be developed by existing and future model creators of a wide range of various nonlinear physical processes in the physical and engineering sectors using the concepts of the solution methods employed in this study. Full article

This study investigates the synchronization of coupled fractional-order Markovian reaction-diffusion neural networks (MRDNNs) with partially unknown transition rates. The novelty of this work is mainly reflected in three aspects: First, this study incorporates the Markovian switching model and reaction-diffusion term into a fractional-order system, which is a challenging and under-explored issue in existing literature, and effectively addresses the synchronization problem of fractional-order MRDNNs by introducing a continuous frequency distribution model of the fractional integrator. Second, it derives a new set of sufficient synchronization conditions with reduced conservatism; by utilizing the (extended) Wirtinger inequality and delay-partitioning techniques, abundant free parameters are introduced to significantly broaden the solution range. Third, it proposes an LMI-based optimal synchronization design by establishing an efficient offline optimization framework with semidefinite constraints, and achieves the precise solution of control gains. Finally, numerical simulations are conducted to validate the effectiveness of the proposed method. Full article

Cu-modified ferrites, prepared by solvothermal syntheses, at up to 200 °C, show the presence of copper metal particles, embedded in ferrite nanocrystalline particle agglomerates. Notably, these metallic copper micron-sized crystallites were dramatically reduced in size, down to a few tens of nanometers, when part of the copper dopant was replaced by zinc. All materials were magnetic due to the presence of the cubic spinel phase, being ferrimagnetic, measured with external fields up to 6000 Oe, showing a narrow hysteresis of 89 Oe for the largest particle size copper ferrite material of 15 nm. Superparamagnetic behavior was observed for the smallest size, e.g., 11 nm, Cu-doped and the zinc-doped, 9–10 nm average particle size ferrites. The redox activity of the materials was studied in free-radical oxidation reactions (pH 7.4, physiological and pH 8.5, optimal) by the chemiluminescent method with (i) Fenton’s reagent (^·OH, ^·OOH); (ii) H₂O₂; and (iii) O₂^·− radicals. All materials presented extremely strong inhibitory activities (converted to prooxidant only at pH 7.4 in system iii, excluding the largest isolated copper-particle-containing material, which remained inhibitory). The materials’ antimicrobial potential was checked on Gram-positive and Gram-negative bacteria, Escherichia coli ATCC 25922, and Staphylococcus aureus ATCC 25923 via two classical methods, namely the spot and well diffusion tests in agar medium. The above tests included a nanocrystalline CuO, tenorite, as a reference material too. The Daphnia magna ecotoxicity test showed that all of the investigated materials are rather toxic, and since daphnia is a key component in freshwater ecosystems, the toxicity even at low concentrations may have significant consequences for the ecological balance. This requires careful monitoring and assessment of the possible use or disposal of these nanomaterials in the environment. Full article

We present a high-speed, miniaturized, Peltier-driven thermocycler for Polymerase Chain Reaction (PCR) with heating rates of 22.25 °C/s and cooling rates of 5.30 °C/s, using a standard aluminum block (a four-well section of a 96-well plate) and laterally arranged micro-thermoelectric coolers (TECs) to induce predominantly horizontal heat flow. Simulations without copper preheating predict a cooling rate of 5.70 °C/s. Finite-element thermoelectric modeling (COMSOL 6.2) closely matches measurements. The selection of materials is guided by the introduction of the merit number G_β that balances thermal diffusivity and volumetric heat capacity, enabling consistent comparison across candidate block materials. The performance of this system is evaluated against data reported in scientific literature, encompassing both recent academic developments and selected commercial systems that employ silver components to enhance thermal conductivity. Despite aluminum’s lower thermal conductivity, our device achieves superior thermal cycling rates, demonstrating that with innovative design, less expensive materials can compete with higher-performing ones. This work includes detailed numerical simulations, comparative analyses of block materials, design considerations, fabrication methods, and experimental validation. By integrating insights from current scientific research, this study contributes to the advancement of accessible and high-performance diagnostic technologies. Full article

Phase engineering has emerged as a powerful method for manipulating the structural and electrical characteristics of nanomaterials, resulting in significant enhancements in their electrochemical performance. This paper examines the correlation among morphology, crystal phase, and electrochemical performance of nanomaterials engineered for high-performance batteries and supercapacitors. The discourse starts with phase engineering methodologies in metal-based nanomaterials, including the direct synthesis of atypical phases and phase transformation mechanisms that provide metastable or mixed-phase structures. Special emphasis is placed on the impact of these synthetic processes on morphology and surface properties, which subsequently regulate charge transport and ion diffusion during electrochemical reactions. Additionally, the investigation of phase engineering in transition metal dichalcogenide (TMD) nanomaterials highlights how regulated phase transitions and heterophase structures improve active sites and conductivity. The optimized phase-engineered ZnCo₂O₄@Ti₃C₂ composite exhibited a high specific capacitance of 1013.5 F g⁻¹, a reversible capacity of 732.5 mAh g⁻¹, and excellent cycling stability, with over 85% retention after 10,000 cycles. These results confirm that phase and morphological control can substantially enhance charge transport and electrochemical durability, offering promising strategies for next-generation batteries and supercapacitors. The paper concludes by summarizing current advancements in phase-engineered nanomaterials for lithium-ion, sodium-ion, and lithium-sulfur batteries, along with supercapacitors, emphasizing the significant relationship between phase state, morphology, and energy storage efficacy. This study offers a comprehensive understanding of the optimal integration of phase and morphological control in designing enhanced electrode materials for next-generation electrochemical energy storage systems. Full article

This paper presents the first theoretical investigation of the effect of a variable equilibrium coefficient on the steady-state transport of a binary electrolyte in a desalination channel cross-section of the electrodialyzer. To address this problem, we developed a new mathematical model in the form of a boundary value problem for an extended system of stationary Nernst–Planck–Poisson equations. We obtained a numerical solution to this problem using the finite element method. Analysis of this solution revealed that the channel cross-section has a complex structure: it is divided into seven regions dominated by different processes, and, consequently, the solution to the boundary value problem behaves differently in each of them. Existing models of the diffusion layer or channel cross-section typically assume a constant equilibrium coefficient. In this paper, we demonstrated that in the channel cross-section, the velocity change corresponding to the equilibrium constant is related not only to the field strength but also to the magnitude of the space charge. In the space-charge region, in the boundary layers near the ion-exchange membranes, intense dissociation of water molecules occurs, and the higher the equilibrium coefficient, the more intense this dissociation is. We have shown that an internal boundary layer (recombination region) arises deep within the solution, associated with the recombination reaction of H+ and OH− ions. In this study, we found that with increasing equilibrium coefficient, fluxes increase, while with increasing fluxes, the electric field strength decreases proportionally, and equilibrium is reached. We demonstrate that by calibrating a single fitting parameter in the model, the simulation results can be matched to experimental data with high accuracy. Thus, our proposed model and its numerical solution provide a completely new understanding of the ion transport process in electromembrane systems, taking into account the influence of the dissociation/recombination reaction of water molecules. Full article