Search Results (430)

Magnetic gears (MGs) are attracting increasing attention in power transmission systems due to their contactless operation principles, low frictional losses, and high efficiency. However, the broad application potential of these technologies requires a comprehensive evaluation of engineering parameters, such as material selection, energy efficiency, and structural design. This review focuses solely on solid-core magnetic gear systems designed using laminated electrical steels, soft magnetic composites (SMCs), and high-saturation alloys. This review systematically examines the topological diversity, torque transmission principles, and the impact of various core materials, such as electrical steels, soft magnetic composites (SMCs), and cobalt-based alloys, on the performance of magnetic gear systems. Literature-based comparative analyses are structured around topological classifications, evaluation of material properties, and performance analyses based on losses. Additionally, the study highlights that aligning material properties with appropriate manufacturing methods, such as powder metallurgy, wire electrical discharge machining (EDM), and precision casting, is essential for the practical scalability of magnetic gear systems. The findings reveal that coaxial magnetic gears (CMGs) offer a favorable balance between high torque density and compactness, while soft magnetic composites provide significant advantages in loss reduction, particularly at high frequencies. Additionally, application trends in fields such as renewable energy, electric vehicles (EVs), aerospace, and robotics are highlighted. Full article

To reduce the carbon footprint of the concrete industry and promote a circular economy, this study explores the reuse of waste materials such as glass powder (GP) and nitrile rubber (NR) fibres in concrete. However, the inclusion of these waste materials results in lower compressive strength compared to conventional concrete, limiting their application to non-structural elements. To overcome this limitation, this study adopts the concept of confined concrete by developing concrete-filled steel tube (CFST) stub columns. In total, twelve concrete mix variations were developed, with and without steel tube confinement. GP was utilised at replacement levels of 10–30% by weight of cement, while NR fibres were introduced at 0.5% and 1% by volume of concrete. The findings demonstrate that the incorporation of GP and NR fibres leads to a reduction in compressive strength, with a compounded effect observed when both materials are combined. Steel confinement within CFST columns effectively mitigated the strength reductions, restoring up to 17% of the lost capacity and significantly improving ductility and energy absorption capacity. All CFST columns exhibited consistent local outward buckling failure mode, irrespective of the concrete mix variations. A comparison with predictions from existing design codes and empirical models revealed discrepancies, underscoring the need for refined design approaches for CFST columns incorporating sustainable concrete infill. This study contributes valuable insights into the development of eco-friendly, high-performance structural systems, highlighting the potential of CFST technology in facilitating the adoption of waste materials in the construction sector. Full article

In recent years, recovering precious and base metals such as silver and copper from end-of-life products has become a fundamental factor in the sustainable development of many countries. This not only supports environmental goals but is also a profitable economic activity. Therefore, in this study, we investigate the recovery of silver and copper from an end-of-life photovoltaic panel powder using an alternative leaching system containing sulfuric acid and ferric sulfate instead of nitric acid-based leaching systems, which are susceptible to producing hazardous gases such as NO_x. To obtain this goal, a series of experiments were designed with the Central Composite Design (CCD) approach using Response Surface Methodology (RSM) to evaluate the effect of reagent concentrations on the leaching rate. The leaching results showed that high recovery rates of silver (>85%) and copper (>96%) were achieved at room temperature using a solution containing only 0.2 M sulfuric acid and 0.15 M ferric sulfate. Analysis of variance was applied to the leaching data for silver and copper recovery, resulting in two statistical models that predict the leaching efficiency based on reagent concentrations. Results indicate that the models are statistically significant due to their high R² (0.9988 and 0.9911 for Ag and Cu, respectively) and the low p-value of 0.0043 and 0.0003 for Ag and Cu, respectively. The models were optimized to maximize the dissolution of silver and copper using Design Expert software. Full article

This study presents a progressive strength prediction model for cement paste based on the hypothesis that compressive strength is governed by the microstructural compactness of hydration products. A three-stage modeling framework was developed: (1) a semi-empirical model for pure cement paste incorporating water-to-cement ratio and paste density; (2) a density-corrected effective water–cement ratio ${\left(w/c\right)}_{eff}$ that accounts for the physical effects of mineral additives including fly ash, slag, and limestone powder; and (3) a hydration-informed strength model incorporating curing age and temperature through an equivalent hydration degree $\alpha \left(t_e\right)$. Experimental validation using over 60 cement paste mixes demonstrated high predictive accuracy, with coefficients of determination up to 0.97. The proposed model unifies the influence of binder composition, packing density, and curing conditions into a physically interpretable and practically applicable formulation. It enables early-age strength prediction of blended cementitious systems using only routine mix and density parameters, supporting performance-based mix design and optimization. The methodology provides a robust foundation for extending compactness-based modeling to more complex cementitious materials and structural applications. Full article

Achieving targeted nanoparticle (NP) size and concentration combinations in Pulsed Laser Ablation in Liquid (PLAL) remains a challenge due to the highly nonlinear relationships between laser processing parameters and NP properties. Despite the promise of PLAL as a surfactant-free, scalable synthesis method, its industrial adoption is hindered by empirical trial-and-error approaches and the lack of predictive tools. The current literature offers limited application of machine learning (ML), particularly recommender systems, in PLAL optimization and automation. This study addresses this gap by introducing a ML-based recommender system trained on a 3 × 3 design of experiments with three replicates covering variables, such as fluence (1.83–1.91 J/cm²), ablation time (5–25 min), and laser scan speed (3000–3500 mm/s), in producing magnesium nanoparticles from powders. Multiple ML models were evaluated, including K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGBoost), Random Forest, and Decision trees. The DT model achieved the best performance for predicting the NP size with a mean percentage error (MPE) of 10%. The XGBoost model was optimal for predicting the NP concentration attaining a competitive MPE of 2%. KNN and Cosine similarity recommender systems were developed based on a database generated by the ML predictions. This intelligent, data-driven framework demonstrates the potential of ML-guided PLAL for scalable, precise NP fabrication in industrial applications. Full article

The use of dry powder inhalers (DPIs) represents a cornerstone in the treatment of chronic pulmonary diseases. However, suboptimal inhalation techniques, including inadequate airflow rates, have been a persistent concern for achieving effective therapeutic outcomes, as many patients remain unaware of their insufficient inhalation performance. As an effective strategy, a digital monitoring system, coupled with dry powder inhalers (DPIs), has emerged to estimate flow profiles and provide inhalation information. The estimation could be further facilitated by the application of artificial intelligence (AI). In this work, a novel digital system to primarily monitor pressure during DPI usage was successfully designed, and advanced machine learning (ML) techniques were then employed to estimate inhalation flow profiles based on the captured data. Four optimal machine learning models were selected for subsequent inhalation parameter prediction, given their superior generalization ability. By using these models, inhalation flow profiles could be successfully estimated, with an excellent accuracy of 97.7% for Peak Inspiratory Flow Rate (PIFR) and 95.2% for inspiratory capacity (IC). In summary, the pressure-based digital monitoring system empowered by AI techniques could be successfully applied to assess inhalation flow profiles with excellent accuracy. Full article

Background/Objectives: 5-Fluorouracil (5-FU) and Irinotecan (IRT) are two of the most used chemotherapeutic agents in CRC treatment. However, achieving treatment goals has been hampered by poor drug delivery to tumor sites and associated toxicity from off-target binding to healthy cells. Though the synergism of 5-FU-IRT has provided incremental improvements in clinical outcomes, the short elimination half-life and off-target binding to healthy cells remain significant challenges. We postulated that nanoencapsulation of a combination of 5-FU and IRT in niosomes would prolong the drugs’ half-lives, while over-encapsulation lyophilized powder in Targit^® oral capsules would passively the CRC microenvironment and avoid extensive systemic distribution. Methods: Ranges of formulation and process variables were input into design of experiment (DOE Fusion One) software, to generate screening experiments. Niosomes were prepared using the thin-film hydration method and characterized by size, the polydispersity index (PDI), morphology and intrastructure, and drug loading. Blank niosomes ranged in size from 215 nm to 257 nm. Results: After loading with the 5-FU-IRT combination, the niosomes averaged 251 ± 2.20 nm with a mean PDI of 0.293 ± 0.01. The surfactant-to-cholesterol ratio significantly influenced the niosome size and the PDI. The hydrophilic 5-FU exhibited superior loading compared to the lipophilic IRT molecules, which probably competed with other lipophilic niosome components in niosomes’ palisade layers. In vitro dissolution in biorelevant media showed delayed release until lower intestinal region (IRT) or colonic region (5-FU). Conclusions: Thus, co-nanoencapsulation of 5-FU/IRT in niosomes, lyophilization, and over-encapsulation of powder in colon-specific capsules could passively target the CRC cells in the colonic microenvironment. Full article

This study describes both experimental and numerical investigations into the heat and mass transfer processes governing the vacuum freeze drying of camel milk, with a specific focus on improving the energy efficiency. A three-dimensional model was developed and solved using the finite element method to simulate temperature evolution and sublimation interface progression during drying. The numerical model was validated against experimental data, achieving strong agreement, with an $R^2$ value of 0.94. A detailed parametric analysis examined the effects of the shelf temperature, sample thickness, and chamber pressure on the drying kinetics and energy input. The results indicate that optimising these parameters can significantly reduce the energy consumption and processing time while maintaining product quality. Notably, reducing the sample thickness to 4 mm shortened the drying time by up to 40% and reduced the specific energy consumption (SEC) from 358 to 149 kWh/kg. These findings offer valuable insights for the design of more energy-efficient freeze drying systems, with implications for sustainable milk powder production and industrial-scale process optimisation. Full article

This study reports the discovery and structural characterization of a novel polymorph, designated as Form III, of Alclometasone dipropionate, a corticosteroid commonly used in the treatment of inflammatory dermatoses. Form III was obtained by modifying the crystallization conditions reported in prior art and was thoroughly characterized using Powder X-ray Diffraction (PXRD), Fourier Transform Infrared (FT-IR) spectroscopy, melting-point determination, Differential Scanning Calorimetry (DSC), Thermogravimetric Analysis (TGA), including its first derivative (DTG), optical microscopy, and Scanning Electron Microscopy (SEM). In parallel, pure Form II, previously observed only in mixtures with Form I, was successfully isolated and characterized using the same analytical techniques. Both forms were compared in terms of structural, thermal, and morphological properties. PXRD analysis revealed that Form III crystallizes in a triclinic system; FT-IR spectroscopy revealed unique vibrational signatures, and microscopy showed rod-like crystal morphology. The discovery of Form III expands the current understanding of the solid-state landscape of Alclometasone dipropionate and opens opportunities for the identification of new industrial purification methods for the compound. Full article

This study investigates the effect of boron carbide (B₄C) ceramic reinforcement on the microstructural, mechanical, electrical, and electrochemical properties of CoCrMo, Ti, and 17-4 PH alloys produced via powder metallurgy for potential biomedical applications. A systematic experimental design was employed, incorporating varying B₄C contents into each matrix through mechanical alloying, cold pressing, and vacuum sintering. The microstructural integrity and dispersion of B₄C were examined using scanning electron microscopy. The performance of the materials was evaluated using several methods, including Vickers hardness, pin-on-disk wear testing, ultrasonic elastic modulus measurements, electrical conductivity, and electrochemical assessments (potentiodynamic polarization and EIS). This study’s findings demonstrated that B₄C significantly enhanced the hardness and wear resistance of all alloys, especially Ti- and CoCrMo-based systems. However, an inverse correlation was observed between B₄C content and corrosion resistance, especially in 17-4 PH matrices. Ti-5B₄C was identified as the most balanced composition, exhibiting high wear resistance, low corrosion rate and elastic modulus values approaching those of human bone. Weibull analysis validated the consistency and reliability of key performance metrics. The results show that adding B₄C can change the properties of biomedical alloys, offering engineering advantages for B₄C-reinforced biomedical implants. Ti-B₄C composites exhibit considerable potential for application in advanced implant technologies. Full article

The rheological behavior of cementitious paste plays a pivotal role in determining the workability, pumpability, and uniformity of fresh concrete. Classical rheological models often struggle to capture the complex flocculation and hydration effects inherent in cement-based systems, and they typically depend on parameters that are difficult to measure directly, limiting their practical utility. This study presents a novel composition-based constitutive model that introduces a virtual maximum packing fraction (${\varphi }_{max}$) to account for interparticle flocculation and entrapped water effects. By establishing quantitative relationships between powder characteristics—such as particle size and specific surface area—and rheological parameters, the model enables physically interpretable and measurable predictions of yield stress and plastic viscosity. Our validation against 65 paste formulations with varying water-to-binder ratios, mineral admixture types and dosages, and superplasticizer contents demonstrates strong predictive accuracy (R² > 0.98 for plain pastes and >0.85 for blended systems). The influence of superplasticizers is effectively captured through modifications to ${\varphi }_{max}$, allowing the model to remain both robust and parameter efficient. This framework supports forward prediction of paste rheology from raw material properties, offering a valuable tool for intelligent mix design in high-performance concrete applications such as self-consolidating and 3D-printed concrete. Full article

To improve the combustion performance of boron powder, a method was developed for synthesizing boron–magnesium–titanium (B-Mg-Ti) ternary composite powders with controlled metal content. Boron–magnesium (B-Mg) base materials were first prepared via electrical explosion, followed by the incorporation of titanium powder at varying mass fractions (1 wt.%, 3 wt.%, 5 wt.%, and 7 wt.%) through mechanical ball milling. Field emission scanning electron microscopy (FE-SEM) revealed that the addition of titanium promoted a more uniform dispersion of magnesium within the boron agglomerates. Moreover, nanoscale titanium particles were observed to be embedded on the particle surfaces, confirming successful microscale composite formation. Particle size distribution was measured using a Malvern 3000 laser particle size analyzer, and results showed that the particle size of the ternary composites decreased gradually with increasing titanium content. Specific surface area was determined via the Brunauer–Emmett–Teller (BET) method, with all samples exhibiting values greater than 15 m²/g, indicating good surface reactivity. Furthermore, the rheological behavior of the B-Mg-Ti composite powders, when combined with terminal hydroxyl polybutadiene (HTPB)—a typical binder in solid propellants—was evaluated. Viscosity measurements were conducted using a rotational rheometer at constant temperatures of 20 °C and 70 °C. The results demonstrated a marked decrease in viscosity with increasing titanium content, suggesting that titanium incorporation enhances the flowability of the composite powders. This study systematically evaluated the influence of titanium content on the structural and physicochemical properties of B-Mg-Ti composite powders, thereby providing a valuable experimental foundation for the optimized design of boron-based combustion systems and the enhancement of their processing and application performance. Full article

Metal injection molding (MIM) is a current technology used to produce products with complex shapes. Despite the accumulated worldwide experience in using this technology, manufacturers sometimes fail to launch new products of proper quality. Often, this is because defects can occur at the casting stage, the prevention of which is impossible through the use of standard design and technological solutions of molds design and the experimental selection of technological modes. This study aimed to analyze the causes of such defects in the green part and optimize the mold design to ensure defect-free casting, which was impossible for the manufacturer using standard solutions. The core method used in this study was simulation modeling of the casting process. A hypotheses were selected, and an analysis of the causes of defect occurrence in casting was conducted. Simulation modeling proved that defect occurrence was due to the formation of a free melt jet and subsequent air capture by this jet. Based on modeling, different gating and feeding system designs were analyzed, which made it possible to choose a variant that provided the uniform filling of gating cavities without forming jet flows and defects. The novelty of this study lies in its optimization of the mold design to prevent free melt jetting and similar defects in other MIM products by modeling feedstock molding processes. The presented results can help enrich the knowledge base of the mold design for MIM and ensure defect-free production. Full article

The construction industry’s escalating environmental footprint, coupled with the underutilization of construction waste streams, necessitates innovative approaches to sustainable material design. This study investigates the dual functionality of recycled clay brick powder (RCBP) as both a supplementary cementitious material (SCM) and an alkali–silica reaction (ASR) inhibitor in hybrid mortar systems incorporating recycled glass (RG) and recycled clay brick (RCB) aggregates. Leveraging the pozzolanic activity of RCBP’s residual aluminosilicate phases, the research quantifies its influence on mortar durability and mechanical performance under varying substitution scenarios. Experimental findings reveal a nonlinear relationship between RCBP dosage and mortar properties. A 30% cement replacement with RCBP yields a 28-day activity index of 96.95%, confirming significant pozzolanic contributions. Critically, RCBP substitution ≥20% effectively mitigates ASRs induced by RG aggregates, with optimal suppression observed at 25% replacement. This threshold aligns with microstructural analyses showing RCBP’s Al³⁺ ions preferentially reacting with alkali hydroxides to form non-expansive gels, reducing pore solution pH and silica dissolution rates. Mechanical characterization reveals trade-offs between workability and strength development. Increasing RCBP substitution decreases mortar consistency and fluidity, which is more pronounced in RG-RCBS blends due to glass aggregates’ smooth texture. Compressively, both SS-RCBS and RG-RCBS mortars exhibit strength reduction with higher RCBP content, yet all specimens show accelerated compressive strength gain relative to flexural strength over curing time. Notably, 28-day water absorption increases with RCBP substitution, correlating with microstructural porosity modifications. These findings position recycled construction wastes and glass as valuable resources in circular economy frameworks, offering municipalities a pathway to meet recycled content mandates without sacrificing structural integrity. The study underscores the importance of waste synergy in advancing sustainable mortar technology, with implications for net-zero building practices and industrial waste valorization. Full article

With growing global concerns over sustainable wastewater treatment, there is a pressing need for low-cost, eco-friendly filtration solutions. This study conducted a life cycle assessment (LCA) to evaluate the potential of improving slow sand filtration efficiency by integrating alternative materials like clay and oyster shell powder (OSP), while minimizing the environmental footprint. Additionally, the adaptability of three-dimensional (3D) printing was explored to incorporate these materials into innovative filter designs, assessing scalability for broader wastewater applications. Ten filter configurations, including a slow sand filter (SSF) enhanced with OSP (90:10) and 3D-printed clay–OSP bricks (ratios of 90:10, 85:15, 80:20), were assessed across three sourcing distances: local (in situ), regional (161 km), and distant (1609 km). The results showed that SSFs with OSP consistently delivered lower environmental impacts, reducing freshwater ecotoxicity, eutrophication, and human toxicity by up to 4% compared to conventional SSFs, particularly when transport was minimized. Among brick-based systems, single-brick columns offered the best balance of performance and impact, while three-brick columns had the highest environmental burden, largely due to the increased electricity use. Economic analysis reinforced the environmental findings: SSFs with OSP were the most cost-effective option, followed closely by SSFs, while brick-based systems were slightly more expensive, with costs rising sharply when sourcing distances exceeded 161 km. Overall, integrating OSP into SSFs offers an optimal balance of sustainability and affordability, while single-brick columns (90:10) present a promising alternative. Future research should further optimize material blends and design configurations to align with long-term environmental and economic goals. Full article