Search Results (5,790)

The MA₂Z₄ family represents a class of two-dimensional materials renowned for their outstanding mechanical properties and excellent environmental stability. By means of elemental substitution, we designed two novel phases of ScSi₂N₄, namely β₁ and β₂. Their dynamical, thermal, and mechanical stabilities were thoroughly verified through phonon dispersion analysis, ab initio molecular dynamics (AIMD) simulations, and calculations of mechanical parameters such as Young’s modulus and Poisson’s ratio. Electronic structure analysis using both PBE and HSE06 methods further revealed that both the β₁ and β₂ phases exhibit metallic behavior, highlighting their potential for battery-related applications. Based on these outstanding properties, the climbing image nudged elastic band (CI-NEB) method was employed to investigate the diffusion behavior of Li, Na, and K ions on the material surfaces. Both structures demonstrate extremely low diffusion energy barriers (Li: 0.38 eV, Na: 0.22 eV, K: 0.12 eV), indicating rapid ion migration—especially for K—and excellent rate performance. The lowest barrier for K ions (0.12 eV) suggests the fastest diffusion kinetics, making it particularly suitable for high-power potassium-ion batteries. The significantly lower barrier for Na ions (0.22 eV) compared with Li (0.38 eV) implies that both β₁ and β₂ phases may be more favorable for fast-charging/discharging sodium-ion battery applications. First-principles calculations were applied to determine the open-circuit voltage (OCV) of the battery materials. The β₂ phase exhibits a higher OCV in Li/Na systems, while the β₁ phase shows more prominent voltage for K. The results demonstrate that both phases possess high theoretical capacities and suitable OCVs. Full article

This work focused on the photocatalytic performance enhancement of titanium dioxide (TiO₂) nanotubes decorated by gold nanoparticles. The surface of the nanotubes synthesized using the anodization technique was modified with subsequent deposition of gold nanoparticles (Au-NPs) via electrophoretic deposition. The impact of electrophoretically deposited gold nanoparticles (Au-NPs) on TiO₂ nanotubes, with varying deposition times (5 min, 8 min and 12 min), was investigated in the degradation of amido black (AB) dye. The morphological analysis using scanning electron microscopy (SEM, TESCAN VEGA3, TESCAN Orsay Holding, Brno, Czech Republic) and transmission electron microscopy (TEM, JEM—100CX2, JEOL Japan). revealed a well-organized nanotubular structure of TiO₂, with a wall thickness of 25 nm and an internal diameter of 75 nm. Optical study, including photoluminescence and diffuse reflectance spectroscopy, provided evidence of charge transfer between the Au-NPs and the TiO₂-NTs. Furthermore, the photocatalytic measurements showed that the enhanced photocatalytic activity of the TiO₂-NTs resulted from successful Au deposition onto their surface, surpassing that of the pure sample. This improvement is attributed to the higher work function of gold nanoparticles, which effectively promoted the separation of photogenerated electron–hole pairs. The sample Au-NPs/TiO₂-NTs with a deposition time of 5 min exhibited the best photocatalytic efficiency, achieving an 85% degradation rate after 270 min under UV irradiation. Moreover, the enhancement obtained was also attributed to the plasmonic effect induced by Au-NPs. Kinetic investigations revealed that the photocatalytic reaction followed apparent first-order kinetics, highlighting the efficiency of Au-NPs/TiO₂-NTs as a photocatalyst for dye degradation. Full article

To address the challenges of low KCl recovery and high collector consumption during flotation at low temperature, a novel approach with utilizing a compound collector consisting of octadecylamine hydrochloride (ODA) and alcohols (butanol, octanol, and dodecanol) to enhance low-temperature KCl flotation recovery was proposed in this study. The flotation performance and underlying mechanisms of this novel amine–alcohol compound collector were investigated through combination of micro-flotation tests, contact angle measurements, and molecular dynamics simulations. The results revealed that KCl flotation recovery decreased with declining temperature using single ODA as the collector, and the maximum KCl flotation recovery was approximately 40% with an ODA concentration of 1 × 10⁻⁵ mol/L at the temperature of 0 °C. Moreover, amine–alcohol compound collector shows different KCl flotation recovery; among them, dodecanol (DOD) presents the best performance at 25 °C with an ODA concentration of 3 × 10⁻⁶ mol/L. The KCl flotation recovery initially increased and then gradually decreased with increasing the DOD concentration, and 90% KCl recovery was achieved with a DOD concentration of 1.5 × 10⁻⁵ mol/L (DOD:ODA = 5:1 in mole) under 25 °C. Furthermore, this compound collector exhibited high selectivity for KCl/NaCl flotation. Mechanism studies indicated that the trend in contact angle changes on the KCl crystal surface closely mirrored the trend in flotation recovery. Molecular dynamics simulations demonstrated that at 0 °C, the presence of DOD resulted in a higher diffusion coefficient for ODA molecules compared to the system without DOD. Additionally, the water molecules in System 3 exhibited a lower diffusion coefficient and a greater number of hydrogen bonds. This novel compound collector offers a potential solution for improving KCl recovery and reducing ODA consumption during low-temperature flotation. It holds significant theoretical and practical implications for advancing low-temperature KCl flotation technology. Full article

Fuel combustion is a crucial process in energy utilization. As a key bulk transport mechanism, Stefan flow significantly affects heat and mass transfer during char combustion. However, its physical nature and engineering implications have long been underestimated, and no systematic review has been conducted. This paper presents a comprehensive review of Stefan flow in char combustion, with a focus on its impact on mass transfer and combustion behavior under both air-fuel and oxy-fuel conditions. It also highlights the critical role of Stefan flow in enhancing energy conversion efficiency and optimizing carbon capture processes. The analysis reveals that Stefan flow has been widely neglected in traditional combustion models, resulting in significant errors in calculated mass transfer coefficients (up to 21% in air-fuel combustion and as high as 74% in oxy-fuel combustion). This long-overlooked deviation severely compromises the accuracy of combustion efficiency predictions and model reliability. In oxy-fuel combustion, the gasification reaction (C + CO₂ = 2CO) induces a much stronger outward Stefan flow, reducing CO₂ transport by up to 74%, weakening local CO₂ enrichment, and substantially increasing the energy cost of carbon capture. In contrast, the oxidation reaction (2C + O₂ = 2CO) results in only an 18% reduction in O₂ transport. Stefan flow hinders the inward mass transfer of O₂ and CO₂ toward the char surface and increases heat loss during combustion, resulting in reduced reaction rates and lower particle temperatures. These effects contribute to incomplete fuel conversion and diminished thermal efficiency. Simulation studies that neglect Stefan flow produce significant errors when predicting combustion characteristics, particularly under oxy-fuel conditions. The impact of Stefan flow on energy balance is more substantial in the kinetic/diffusion-controlled regime than in the diffusion-controlled regime. This review is the first to clearly identify Stefan flow as the fundamental physical mechanism responsible for the differences in combustion behavior between air-fuel and oxy-fuel environments. It addresses a key gap in current research and offers a novel theoretical framework for improving low-carbon combustion models, providing important theoretical support for efficient combustion and clean energy conversion. Full article

Generative model-assisted design has become a trend, providing a new paradigm for knitted fabric image generation. The FLUX diffusion model was chosen to generate images in this study and was compared to other generative models. In order to effectively apply the large model to specialized verticals, an efficient fine-tuning method, low-rank adaptation, was used. Experiments showed that the method allows a pre-trained model to stably generate knitted fabric images in batches through easily understandable text prompts. The generated images have clear textures and correct structures, and can display the surface characteristics of knitted fabrics generated by using different yarn specifications and yarn bristles. Moreover, the unit tissue structural similarity index measure (SSIM) is 0.6528, which is very similar to real fabrics. This research expands the application of fabric generation in the field of deep learning. This method is highly efficient, low-cost, and capable of stably simulating knitted fabrics, which can be used to rapidly expand the image design materials of knitted fabrics. Full article

Layered intercalating V₂O₅ (vanadium pentoxide) is a durable battery-type electrode material exploited in supercapacitors. The advancement of V₂O₅ nanomaterials synthesized from non-aqueous organic solvents holds significant potential for energy storage applications. Liquid-phase synthesis of orthorhombic V₂O₅ cathode material corroborated its compatibility with quartet glycols and allowed examination of their explicit roles in faradic charge storage efficacy. V₂O₅ was found to be an intercalative material in all the quartet glycols. The crystalline, rod-like morphology and monodisperse V₂O₅ electrode were ascribed to the effects of ethylene, diethylene, triethylene, and tetraethylene glycols. Notable differences were observed in the electrochemical analysis of the prepared V₂O₅ (EV, DV, TV, and TTV). In a three-electrode cell setup, the DV electrode demonstrated a superior specific capacity of 460.2 C/g at a current density of 1 A/g. From the Trasatti analysis, the DV electrode exhibited 961.53 C/g of total capacitance, comprising a diffusion-controlled contribution of 898.19 C/g and a surface-controlled contribution of 63.34 C/g. The aqueous asymmetric device DV//AC exhibited a maximum energy density of 65.72 Wh/kg at a power density of 1199.97 W/kg. The glycol-derived electrodes were anticipated to bepromising materials for supercapacitors and have the potential to meet electrochemical energy needs. Full article

Vanadium-based electrode materials are limited in practical applications, due to their low energy density, cycling instability, and poor electrochemical stability. To address these limitations, a wood-derived vanadium oxide (VO_x) electrode was developed through sol–gel assembly followed by thermal annealing, in which VO_x aerogel formed within the vertically aligned wood channels, resulting in a continuous porous network to mitigate particle aggregation and enhance ion diffusion. After thermal annealing at 800 °C, V⁵⁺ partially converts to V⁴⁺, forming a mixed-valence heterostructure that significantly increases the density of redox-active sites and facilitates efficient charge transfer. The optimized VO_x@Wood-800 °C (VOW-800) electrode exhibits a high specific capacitance of 317.8 F g⁻¹ at 2 mA cm⁻² and a specific surface area of 111.22 m⁻² g⁻¹, attributed to the synergistic effects of the mixed-valence structure and the enhanced ion accessibility provided by the wood-derived porous framework. This approach offers a promising pathway for developing vanadium-based electrodes with improved charge storage capacity and interface stability. Full article

This study explores the enhancement of fluoride adsorption using biochar derived from the brown macroalga Sargassum polycystum, which was treated with iron oxide (Fe₃O₄). The macroalgal biomass underwent pyrolysis at 400 °C, followed by Fe₃O₄ impregnation, to improve surface functionality and create active sites for fluoride ion binding. Various factors affecting fluoride removal were systematically examined. A maximum fluoride removal effectiveness of 90.2% was attained under ideal circumstances (pH 2, 60 mg adsorbent dose, 30 mg/L fluoride concentration, and 150 min contact duration). Adsorption isotherm analysis showed that the Langmuir model provided a better fit (R² = 0.998) than the Freundlich model (R² = 0.941), with a maximum adsorption capacity (qₘ) of 3.41 mg/g, indicating monolayer adsorption on a homogeneous surface. Kinetic modeling revealed that the pseudo-second-order model best described the adsorption process (R² = 0.9943), suggesting chemisorption as the dominant mechanism, while the intraparticle diffusion model also showed a good fit (R² = 0.9524), implying its role in the rate-limiting step. Surface complexation, facilitated by the enhanced surface area and porosity of the iron-modified biochar, was identified as the primary mechanism of fluoride ion interaction. This study highlights the potential of Fe₃O₄-modified macroalgal biochar as an effective and sustainable solution for fluoride remediation in contaminated water sources. Full article

Monitoring of laser-based processes is essential for ensuring the quality of produced surface structures and for maintaining the process stability and reproducibility. Optical methods based on scatterometry are attractive for industrial monitoring as they are fast, non-contact, non-destructive, and can resolve features down to the sub-microscale. Here, Laser-Induced Periodic Surface Structures (LIPSS) are produced on stainless steel using ultrashort laser pulses in combination with a polygon scanning system. After the process, the fabricated LIPSS features are characterized by microscopy methods and with an optical setup based on scatterometry. Images of the diffraction patterns are collected and the intensity distribution analyzed and compared to the microscopy results in order to estimate the LIPSS height, spatial period, and regularity. The resulting analysis allows us to study LIPSS formation development, even when its characteristic diffraction pattern gradually changes from a double-sickle shape to a diffuse cloud. The scatterometry setup could be used to infer LIPSS height up to 420 nm, with an estimated average error of 7.7% for the highest structures and 11.4% in the whole working range. Periods estimation presents an average error of ~5% in the range where LIPSS are well-defined. In addition, the opening angle of the LIPSS was monitored and compared with regularity measurements, indicating that angles exceeding a certain threshold correspond to surfaces where sub-structures dominate over LIPSS. Full article

Intermediate-temperature solid oxide fuel cells (IT-SOFCs) have attracted attention due to their potential to overcome the trade-off between the performance and lifetime of SOFC devices. However, the guiding principle for effective material design, which can reduce operating temperatures and overcome performance decreases caused by excessive overpotential on the anode surface, has not been clearly established. In the present work, we studied the reported Schottky anomaly, which has been observed exclusively in yttria-stabilized zirconia (YSZ). To investigate this phenomenon, a small amount (less than 1200 ppm) of trivalent cations (Rh³⁺ or Fe³⁺), chemically similar to Y³⁺ in Y₂O₃, was doped onto the YSZ surface in the anode layer. Then, the current density observed from the SOFC device at 973 K was found to be nine-times higher than the SOFC device with an undoped anode. The surface first-principles calculations in the present work indicate that this performance enhancement is caused by the delocalized electrons induced by trivalent cation doping in the vicinity of the three-phase boundary and the promotion of surface oxygen diffusion in YSZ. Based on all experimental data, the effective material design guiding principle was obtained for utilizing the unique physical property of YSZ for applications such as IT-SOFCs. Full article

Deep shale gas reservoirs are vital sources of unconventional natural gas and present unique challenges for exploration and development due to their multiscale flow characteristics and elastoplastic deformation behavior of reservoir rocks. Accurately predicting permeability in these reservoirs is crucial. This study introduces a novel model utilizing fractal theory and a thick-walled cylinder model to characterize stress-dependent apparent gas permeability. The model incorporates various flow mechanisms, including viscous flow, transition flow, Knudsen diffusion, surface diffusion, real gas effects, and gas slip effects. It enables predictions of how permeability changes with elastoplastic behavior and affects the pore volume fractions of different flow mechanisms. Experimental validation during elastic and elastoplastic deformations confirms the model’s accuracy, with each parameter having clear physical significance. Key findings reveal that, at the same effective stress, apparent gas permeability increases with pore radius fractal dimension, temperature, and Young’s modulus, while decreasing with capillary tortuosity fractal dimension. Additionally, during plastic deformation, greater magnitudes of plastic strain lead to more pronounced changes in apparent gas permeability compared to elastic deformation. These insights emphasize the importance of incorporating elastoplastic behavior in studies of deep shale gas reservoirs. Full article

This work presents a comprehensive evaluation of corrosion progression in DH36 naval steel through the integration of electrochemical impedance spectroscopy (EIS), weight loss, scanning electron microscopy (SEM), and advanced magnetic non-destructive techniques under artificial seawater (ASW, ASTM D1141) and natural marine conditions. Quantitative correlations are established between corrosion layer growth, electrochemical parameters, and magnetic permeability, demonstrating the magnetic sensor’s capacity for the real-time, non-invasive assessment of marine steel degradation. Laboratory exposures reveal a rapid initial corrosion phase with the formation of lepidocrocite and goethite, followed by the densification of the corrosion product layer and a pronounced decline in corrosion rate, ultimately governed by diffusion-controlled kinetics. Notably, changes in magnetic permeability closely track both the thickening of non-magnetic corrosion products and microstructural deterioration, with declining μmax and increased hysteresis widths (FWHM) sensitively indicating evolving surface conditions. A direct comparison with in situ marine immersion at Rafina confirms that the evolution of corrosion morphology and the corresponding magnetic response are further modulated by biofilm development, which exacerbates the attenuation of measured surface permeability and introduces greater variability linked to biological activity. These findings underscore the robustness and diagnostic potential of magnetic non-destructive sensors for the predictive, condition-based monitoring of naval steels, bridging laboratory-controlled observations and complex real-world environments with high quantitative fidelity to corrosion kinetics, phase evolution, and microstructural transformations, thus guiding the strategic deployment of protection and maintenance regimens for naval fleet integrity. Full article

In deepwater drilling operations, inhibiting methane hydrate (MH) formation is critical for wellbore flow assurance. This study synthesized a zwitterionic polymer NDAD and evaluated its hydrate inhibition performance through high-pressure reactor tests, magnetic resonance imaging (MRI), and molecular simulations. Results demonstrate that NDAD at concentrations of 1.0 wt% extends MH formation time by 4.9 times compared to conventional inhibitor PVCap. Notably, NaCl (10–15 wt%) synergistically enhances inhibition efficiency by inducing NDAD chain stretching to form physical gel networks, increasing solution viscosity by 98%. This gel structure obstructs methane–water diffusion, prolonging hydrate induction time. Response surface methodology (RSM) identifies NDAD dosage as the primary control factor for inhibition efficacy. Molecular simulations confirm that NDAD inhibits hydrate formation through dual pathways: (i) competitive hydration by ionic groups disrupting water cage structures and (ii) gel networks imposing mass transfer resistance to methane diffusion. Full article

Antibiotic resistance (AR) in environmental Escherichia coli represents a growing public health challenge. This study evaluated the prevalence of AR among E. coli isolates recovered from surface water bodies within the Ameca River basin in Jalisco, Mexico, and examined associations with anthropogenic influence and seasonal variation. Over a 1-year period, water samples were collected monthly from 16 sites, including tributaries, wetlands, and main river channels with differing degrees of urban impact. E. coli isolates were confirmed by malB gene PCR and tested for susceptibility to six antibiotics using the Kirby–Bauer disk diffusion method. High resistance frequencies were observed for ampicillin (93.9%), tetracycline (92.4%), and streptomycin (89.6%), while gentamicin exhibited the lowest resistance rate (48.1%). Resistance prevalence was significantly higher at sites adjacent to urban settlements and during the rainy season (p < 0.05). These findings underscore the influence of land use and seasonal dynamics on AR dissemination in aquatic environments and highlight the need for improved wastewater management strategies to mitigate the spread of resistant bacteria. Full article

In the context of the current global transition toward low-carbon energy, the issue of $C{O}_2$ utilization has become increasingly important. One of the most promising natural targets for $C{O}_2$ sequestration is the terrigenous sedimentary formations found in oil, gas, and coal basins. It is generally assumed that $C{O}_2$ injected into such formations can be stored indefinitely in a stable form. However, the dissolution of $C{O}_2$ into subsurface water leads to a reduction in pH, which may cause partial dissolution of the host formation, altering the structure of the subsurface in the injection zone. This process is relatively slow, potentially unfolding over decades or even centuries, and its long-term consequences require careful investigation through mathematical modeling. The geological formation is treated as a partially soluble porous medium, where the dissolution rate is governed by surface chemical reactions occurring at the pore boundaries. In this study, we present an applied mathematical model that captures the coupled processes of mass transport, surface chemical reactions, and the resulting microscopic changes in the pore structure of the formation. To ensure the model remains grounded in realistic geological conditions, we based it on exploration data characterizing the composition and microstructure of the pore space typical of the Cenomanian suite in northern Western Siberia. The model incorporates the dominant geochemical reactions involving calcium carbonate (calcite, $CaC{O}_3$), characteristic of Cenomanian reservoir rocks. It describes the dissolution of $C{O}_2$ in the pore fluid and the associated evolution of ion concentrations, specifically $H^{+}$, $C{a}^{2+}$, and $HC{O}_3^{-}$. The input parameters are derived from experimental data. While the model focuses on calcite-based formations, the algorithm can be adapted to other mineralogies with appropriate modifications to the reaction terms. The simulation domain is defined as a cubic region with a side length of 1 $\mathsf{\mu }$m, representing a fragment of the geological formation with a porosity of 0.33. The pore space is initially filled with a mixture of liquid $C{O}_2$ and water at known saturation levels. The mathematical framework consists of a system of diffusion–reaction equations describing the dissolution of $C{O}_2$ in water and the subsequent mineral dissolution, coupled with a model for surface evolution of the solid phase. This model enables calculation of surface reaction rates within the porous medium and estimates the timescales over which significant changes in pore structure may occur, depending on the relative saturations of water and liquid $C{O}_2$. Full article