Search Results (4,903)

For optimizing the operational efficiency and productivity within blast furnace processes, a profound understanding of the viscous flow characteristics of CaO–SiO₂–MgO–Al₂O₃–B₂O₃ slag systems is of paramount importance. In this study, we conducted a comprehensive investigation into the influence of the CaO/SiO₂ and MgO/Al₂O₃ ratios on the viscosity, break point temperature (T_Br), and activation energy (E_η) of low boron-bearing high-alumina slag. Concurrently, we elucidated the underlying mechanisms through which these ratios affect the viscous behavior of the slag by employing a combination of analytical techniques, including X-Ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), and thermodynamic modeling using the Factsage software. The experimental findings reveal that, as the CaO/SiO₂ ratio increases from 1.10 to 1.30, the slag viscosity at 1773 K decreases from 0.316 Pa·s to 0.227 Pa·s, while both the T_Br and E_η exhibit an upward trend, rising from 1534 K and 117.01 kJ·mol⁻¹ to 1583 K and 182.86 kJ·mol⁻¹, respectively. Conversely, an elevation in the MgO/Al₂O₃ ratio from 0.40 to 0.65 results in a reduction in slag viscosity at 1773 K from 0.290 Pa·s to 0.208 Pa·s, accompanied by a decrease in T_Br from 1567 K to 1542 K. The observed deterioration in slag flow properties can be attributed to an enhanced polymerization degree of complex viscous structural units within the slag matrix. Ultimately, our study identifies that an optimal viscous performance of the slag is achieved when the CaO/SiO₂ ratio is maintained at 1.25 and the MgO/Al₂O₃ ratio is maintained at 0.55, providing valuable insights for the rational design and control of blast furnace slag systems. Full article

Lithium-ion batteries are extensively used for energy storage in renewable, electronic, and automotive applications. However, once their electrical capacity is exhausted, they become hazardous waste that requires energy-intensive recycling processes. This study investigates the thermodynamic and exergetic behavior of LiMn₂O₄-based lithium-ion batteries subjected to controlled electrical overvoltage from renewable energy sources, aiming to quantify their potential for thermal energy generation and recovery. A detailed mathematical model was developed to describe the coupled heat transfer and electrochemical phenomena occurring during overvoltage conditions, and experimental validation was performed under various voltage levels and charging states. Energy and exergy analyses were applied to determine the configuration yielding the highest conversion efficiency for both new and aged cells. The maximum thermal energy efficiency reached 81% for new batteries and 4% for used batteries, while the corresponding exergetic efficiencies were 5% and 1.6%, respectively. Although this study does not propose the immediate large-scale reuse of spent batteries as thermal devices, the results provide quantitative insight into irreversible energy conversion processes and highlight their potential contribution to waste heat recovery and energy optimization strategies in sustainable industrial systems. This thermodynamic framework offers a novel approach for valorizing end-of-life batteries within circular energy models, reducing environmental impact, and advancing the integration of renewable energy-driven heat recovery technologies. Full article

The photocatalytic activity of Bi₂WO₆ Aurivillius phase has been widely exploited for the degradation of a wide range of gaseous and aqueous molecules, as well as microorganisms, under the influence of visible irradiation. Strategies for the development of doped and co-doped bismuth tungstate materials require the thermodynamic data on this phase. The heat capacity of bismuth tungstate, Bi₂WO₆, was investigated using a DSC microcalorimeter on polycrystalline powder samples in the temperature range from 313 to 1103 K (40–830 °C) in two separate runs. The samples were synthesized by solid-state reaction from pure binary oxides at 1033 K (760 °C) in a platinum crucible with cover. The high temperature C_p(T) data were fitted by the Maier–Kelley equation and, from this relation, the standard molar heat capacity of γ-Bi₂WO₆ polymorph was estimated to be at 298.15 K 176.8 ± 3.9 J·K⁻¹·mol⁻¹. A reversible second-order transition of Bi₂WO₆ phase was observed in the experimental temperature range, with a peak close to 940 K (667 °C). Additionally, the extrapolation of C_p(T) to 0 K was proposed using a method based on the multiple Einstein model. Thermodynamic properties (heat capacity C_p(T), entropy S°(T), enthalpy H°(T), Gibbs energy G°(T)) of crystalline γ-Bi₂WO₆ were calculated in the temperature range of 298.15–1123 K (25–850 °C). Full article

The removal of phytotoxins from herbal preparations is important due to evidence linking exposure to aristolochic acid I (AAI), a toxin found in Aristolochiaceae species, with certain kidney diseases. This study evaluates the effectiveness of activated carbon (AC) in removing AAI from aqueous solutions and determines the optimal conditions for the process, which are necessary for accurate kinetic, thermodynamic, and equilibrium analyses. After establishing the best conditions for the adsorption reaction (pH > 6; solid/liquid ratio (S:L) = 0.1 g adsorbent: 25 mL AAI solution; contact time 120 min; temperature = 298 K, AAI initial concentration (Ci) = 150 mg/L), a maximum adsorption capacity of 10.67 mg/g was obtained. Quantitative analysis of AAI was performed using UV-VIS spectrophotometry. Experiments on kinetics, thermodynamics, and adsorption isotherms were carried out. The findings showed that the process adheres to pseudo-second-order kinetics and is spontaneous and endothermic and takes place at the interface between the adsorbent and adsorbate. The equilibrium data fits the Sips isotherm model with a regression coefficient close to 1. The findings indicate that AC is an effective material for the removal of AAI by adsorption from an aqueous solution. Full article

This study provides a comprehensive analysis of lemon peel (LP) combustion behaviour using combined physicochemical characterization and non-isothermal thermogravimetric kinetics. To achieve this, LP was characterized for its proximate and ultimate composition, with its structure analysed via FTIR, XRD, and SEM. Thermogravimetric analysis (TGA) was then performed at high heating rates (20–80 K min⁻¹) to investigate combustion stages, and kinetic and thermodynamic parameters were determined using six model-free and one model-fitting method. The results revealed a high heating value (23.02 MJ kg⁻¹) and high volatile matter (73.2 wt%), establishing LP’s significant energy potential. TGA displayed four distinct decomposition stages corresponding to dehydration, pectin/hemicellulose, cellulose, and lignin/char combustion. Kinetic analysis yielded activation energies that varied with conversion, peaking at approximately 304 kJ mol⁻¹, and a three-dimensional diffusion (D3) mechanism was identified as the rate-limiting step. In conclusion, while its high energy content and low nitrogen (1.26 wt%) and sulphur (0.20 wt%) content make LP an attractive low-emission biofuel, its viability is challenged by a high potassium concentration in the ash (34.8 wt% K₂O), posing a severe risk of slagging. This study provides the comprehensive combustion kinetic data for LP at high heating rates, which is essential for designing appropriate energy conversion technologies and ash management strategies. Full article

This work is a logical continuation of the study of the chemical composition of the waters of the Lovozersky district (Kola Peninsula, Russia), where an indigenous population resides. The problem statement is caused by the discovery of rare and rare earth elements in drinking water and the high rate of illness among the residents of the Lovozersky district. The goal of this work is to assess the quality of natural waters in the village of Krasnoshchelye (Kola Peninsula, Russia) and compare it with the composition of other waters in the Kola Peninsula, taking into account sanitary standards (maximum permissible concentrations) and biologically significant concentrations. As a result, the chemical composition of surface and groundwater was studied, their quality was characterized, and the forms of element migration in the “solution–crystalline substance” system in water and the human body (using the stomach as an example) were examined. The results of studies of drinking water in the village of Krasnoshchelye indicate that the macro-(Ca, Mg, Na, K) and microelement (Co, Cu, Mn, Ni, V, Zn, Cr) composition has lower concentrations in terms of biological significance for the elemental balance of humans than the recommended levels for them. The exceptions are the elements U, Th, and Y, whose concentrations are several times higher than their lower limits of biologically significant concentrations. In the human body, within the “water–gastric juice” system, the forms of the migration of elements and newly formed phases depend not only on the acidity of the stomach but also on the amount of gastric juice, which are individual characteristics of a person and their age. It has been established that well water contains rare elements and up to 50 µg L⁻¹ of rare earth elements, and changes in their migration forms can lead to accumulation in the human body and become a cause of diseases of the nervous system and other organs. Full article

An intracellular α-glucosidase was isolated and purified from a Pseudanabaena sp. cyanobacterial strain. Before the enzyme purification, the optimal cultural conditions were determined. Optimal culture conditions (15 g/L maltose, 2 g/L yeast extract, 23 ± 1 °C) yielded 3.3 g/L of biomass and 2186 U/L of α-glucosidase in a lab-scale bioreactor. The purified enzyme displayed a molecular mass of 52 kDa with optimum activity at 40 °C and pH 7.0, and maintained stability within an acidic and neutral range of pH 4.0 to 7.0. Enzyme activity was affected by both the concentration and interaction time of the metal ions and chelator. Kinetic constants of K_m, V_max, and k_cat for the hydrolysis of pNPG were determined as 2.0 Mm, 2.9 μmol min⁻¹, and 14.86 min⁻¹, respectively. The activation energy (E_a) was 24.2 kJ mol⁻¹ and the thermodynamic parameters of enthalpy (ΔH^*), entropy (ΔS^*) of activation, Gibbs free energy (ΔG^*), free energy of substrate binding (ΔG^*_E-S), and transition state formation (ΔG^*_Ε-Τ) were 21.6, −116, 57.8, −22.2, and −41.2 kJ mol⁻¹, respectively. Moreover, the thermodynamic parameters for thermal inactivation of the enzyme were ΔH^*= 131 kJ mol⁻¹, 105 ≤ ΔS^* ≤ 108 kJ mol⁻¹, and 96 ≤ ΔG^* ≤ 98 kJ mol⁻¹, while the thermal inactivation energy (E_(a)d) was determined to be 133 kJ mol⁻¹. This is the first detailed investigation concerning the characterization of α-glucosidase derived from cyanobacteria. The presented enzymatic characteristics provide a valuable predictive model for identifying suitable applications. Full article

The increasing need for high-resolution, real-time radiative transfer (RT) modeling in climate science, remote sensing, and planetary exploration has exposed limitations of traditional solvers such as the Discrete Ordinate Radiative Transfer (DISORT) and Rapid Radiative Transfer Model for General Circulation Models (RRTMG), particularly in handling spectral complexity, non-local thermodynamic equilibrium (non-LTE) conditions, and computational scalability. Quantum-Inspired Neural Radiative Transfer (QINRT) frameworks, combining tensor-network parameterizations and quantum neural operators (QNOs), offer efficient approximation of high-dimensional radiative fields while preserving key physical correlations. This review highlights the advances of QINRT in enhancing spectral fidelity and computational efficiency, enabling energy-efficient, real-time RT inference suitable for satellite constellations and unmanned aerial vehicle (UAV) platforms. By integrating physics-informed modeling with scalable neural architectures, QINRT represents a transformative approach for next-generation Earth-system digital twins and autonomous climate intelligence. Full article

This study synthesizes three new composites: chitin-cross-linked poly(ortho-phenylenediamine)-grafted silicon dioxide (CT-PoPD-grafted SiO₂), chitosan-cross-linked PoPD-grafted SiO₂ (CS-PoP-grafted SiO₂), and guar-gum-cross-linked PoPD-grafted SiO₂ (GG-PoPD-grafted SiO₂). These biopolymer-based materials were developed as cost-effective, biocompatible adsorbents with increased surface area for removing Acid Red 1 AR1) and Crystal Violet (CV) dyes. Structural and morphological analyses through Fourier-transform infrared spectroscopy, X-ray diffraction, and X-ray photoelectron spectroscopy (XPS) confirmed their successful synthesis. Adsorption studies were conducted under various conditions, including adsorbent dosage, pH, temperature, and contact time. Among the composites, GG-PoPD-grafted SiO₂ demonstrated superior performance, achieving 99.1% and 95.6% removal of AR1 and CV, respectively. Kinetic analysis revealed a pseudo-second-order model, while thermodynamic results indicated a spontaneous and endothermic adsorption process. In conclusion, the GG-PoPD-grafted SiO₂ composite exhibits significant potential as an effective and sustainable material for wastewater treatment. Full article

The primary objective of this research is to simplify and make the industrial manufacturing process of coated maraging steels more economical by combining the advantages of additive manufacturing with simultaneous bulk (aging) and surface (nitriding) treatment in an effective manner. With this aim, preliminary experiments were performed that demonstrated the hardness (and related microstructure) of an as-built MS1 maraging steel, produced by selective laser melting (SLM), is comparable to that of the bulk maraging steel products treated by conventional solution annealing. The direct aging of the solution-annealed and as-built 3D printed maraging steel resulted in similar hardness, indicating that the kinetics of the precipitation hardening process are identical for the steel in both conditions. This assumption was strengthened by a thermodynamic analysis of the kinetics and determination of the activation energy for precipitation hardening using Differential Scanning Calorimetry (DSC) measurements. Industrial target experiments were performed on duplex-coated SLM-printed MS1 steel specimens, which were simultaneously aged and salt-bath nitrided, followed by PVD coating with three different ceramic layers: DLC, CrN, and TiN. For reference, similar duplex-coated samples were used, featuring a bulk Böhler W720 maraging steel substrate that was solution annealed, precipitation hardened, and salt-bath nitrided in separate steps, following conventional procedures. The technological parameters (temperature and time) of the simultaneous nitriding and aging process were optimized by modeling the phase transformations of the entire heat treatment procedure using DSC measurements. A comparison was made based on the in-depth hardness profile estimated by the so-called expanding cavity model (ECM), demonstrating that the hardness of the surface layer of the coated composite material systems is determined solely by the type of the coatings and does not influenced by the type of the applied substrate materials (bulk or 3D printed) or its heat treatment (whether it is a conventional, multi-step treatment or a simultaneous nitriding + aging process). Based on the research work, a proposal is suggested for modernizing and improving the cost-effectiveness of producing aged, duplex-treated, wear-resistant ceramic-coated maraging steel. Full article

This study investigates three distinct charged gravastar models within the framework of $f\left(T\right)$ modified gravity, considering the functional forms $f\left(T\right)=T$, $f\left(T\right)=a+bT$, and $f\left(T\right)=T^2$. Inspired by the Mazur–Mottola conjecture, we propose these models as singularity-free alternatives to black holes, each characterized by a three-region structure: (i) an interior de Sitter core, (ii) an intermediate thin shell composed of ultrarelativistic matter, and (iii) an exterior region described by the Reisner Nordstrom solution and other novel spherically symmetric vacuum solutions. We derive a complete set of exact, singularity-free solutions for the charged gravastar configuration, demonstrating their mathematical consistency and physical viability in the context of alternative gravity theories. Notably, the field equations governing the thin shell are solved using an innovative approach based on Killing vector symmetries, eliminating the need for approximations commonly employed in prior studies. Furthermore, we analyze key physical properties of the thin shell, including its proper length, entropy distribution, and energy content. A thorough examination of the energy conditions reveals the thermodynamic stability and viability of these models. Our results contribute to the growing body of work on exotic compact objects and provide new insights into the interplay between modified gravity, electromagnetism, and non-singular black hole alternatives. Full article

This review surveys recent progress in hybrid artificial intelligence (AI) approaches for gas turbine intelligent digital twins, with an emphasis on models that integrate physics-based simulations and machine learning. The main contribution is the introduction of a structured classification of hybrid AI methods tailored to gas turbine applications, the development of a novel comparative maturity framework, and the proposal of a layered roadmap for integration. The classification organizes hybrid AI approaches into four categories: (1) artificial neural network (ANN)-augmented thermodynamic models, (2) physics-integrated operational architectures, (3) physics-constrained neural networks (PcNNs) with computational fluid dynamics (CFD) surrogates, and (4) generative and model discovery approaches. The maturity framework evaluates these categories across five criteria: data dependency, interpretability, deployment complexity, workflow integration, and real-time capability. Industrial case studies—including General Electric (GE) Vernova’s SmartSignal, Siemens’ Autonomous Turbine Operation and Maintenance (ATOM), and the Electric Power Research Institute (EPRI) turbine digital twin—illustrate applications in real-time diagnostics, predictive maintenance, and performance optimization. Together, the classification and maturity framework provide the means for systematic assessment of hybrid AI methods in gas turbine intelligent digital twins. The review concludes by identifying key challenges and outlining a roadmap for the future development of scalable, interpretable, and operationally robust intelligent digital twins for gas turbines. Full article

Chlorpyrifos (CHP) is a persistent organophosphate pesticide whose presence in water poses serious ecological and health risks. Here, we report a sustainable adsorbent obtained by high-temperature carbonization of immature walnuts (Juglans regia). The adsorbent’s structure, surface chemistry, and charge properties were comprehensively characterized using FTIR, SEM-EDX, zeta potential measurement, BET analysis, and XPS. The synthesis yielded a mesoporous carbon material with a BET surface area of 303 m² g⁻¹. Its performance in CHP removal was assessed under batch and dynamic conditions. Adsorption followed pseudo-second-order kinetics (k₂ = 0.122 mg min⁻¹ g⁻¹; contact time 0–120 min). Isotherm experiments performed at 20, 25, and 30 °C, with equilibrium data best described by the Langmuir and Sips models, reaching a maximum capacity of 43.2 mg g⁻¹. Thermodynamic analysis indicated a spontaneous and endothermic process. The adsorbent demonstrated selectivity for CHP over chlorpyrifos-oxon (CPO) in binary mixtures, retained its efficiency over at least ten regeneration cycles with ethanol, and removed up to 90% of CHP toxicity, as measured by acetylcholinesterase inhibition. Dynamic filtration confirmed its applicability under flow conditions. These findings demonstrate that the investigated adsorbent is an effective, reusable, and selective adsorbent, offering a low-cost and eco-friendly approach to pesticide removal from contaminated waters. Full article

Bio-waste from potato shell agro-waste-based photocatalyst is introduced using potato shell integrated with Fe₃O₄ nanoparticles as a novel photocatalyst for photo-Fenton oxidation reaction. The catalyst was prepared via thermal activation of biochar, followed by co-precipitation of magnetite nanoparticles, resulting in a stable and reusable material. X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques augmented with the energy dispersive X-ray spectroscopy (EDX) analysis with elemental mapping were used to assess the prepared sample. The prepared material, PtS200–Fe₃O₄, is then applied for oxidizing Procion Blue dye using biochar-supported magnetite catalyst. The oxidation process was evaluated under varying operational parameters, including pH, temperature, catalyst loading, oxidant dosage, and dye concentration. Results revealed that the system achieved complete dye removal within 20 min at 60 °C and pH 3, demonstrating the strong catalytic activity of the composite. Furthermore, the kinetic modeling is evaluated and the data confirmed that the degradation followed first-order kinetics. Also, the thermodynamic parameters indicated low activation energy with PtS200–Fe₃O₄ composite in advanced oxidation processes. The system sustainability is also assessed, and the reusability test verified that the catalyst retained over 70% efficiency after six consecutive cycles, highlighting its durability. The study confirms the feasibility of using biochar-supported magnetite as a cost-effective, eco-friendly, and efficient catalyst for the treatment of textile effluents and other dye-contaminated wastewater. Full article

The two-star random graph is the simplest exponential random graph model with nontrivial interactions between the graph edges. We propose a set of auxiliary variables that control the thermodynamic limit where the number of vertices N tends to infinity. Such ’master variables’ are usually highly desirable in treatments of ‘large N’ statistical field theory problems. For the dense regime when a finite fraction of all possible edges are filled, this construction recovers the mean-field solution of Park and Newman, but with explicit control over the $1/N$ corrections. We use this advantage to compute the first subleading correction to the Park–Newman result, which encodes the finite, nonextensive contribution to the free energy. For the sparse regime with a finite mean degree, we obtain a very compact derivation of the Annibale–Courtney solution, originally developed with the use of functional integrals, which is comfortably bypassed in our treatment. Full article