Search Results (1,585)

Background: Pain is a complex phenomenon characterized by unpleasant experiences with profound heterogeneity influenced by biological, psychological, and social factors. According to the National Health Interview Survey, 50.2 million U.S. adults (20.5%) experience pain on most days, with the annual cost of prescription medication for pain reaching approximately USD 17.8 billion. Theranostic pain nanomedicine therefore emerges as an attractive analgesic strategy with the potential for increased efficacy, reduced side-effects, and treatment personalization. Theranostic nanomedicine combines drug delivery and diagnostic features, allowing for real-time monitoring of analgesic efficacy in vivo using molecular imaging. However, clinical translation of these nanomedicines are challenging due to complex manufacturing methodologies, lack of standardized quality control, and potentially high costs. Quality by Design (QbD) can navigate these challenges and lead to the development of an optimal pain nanomedicine. Our lab previously reported a macrophage-targeted perfluorocarbon nanoemulsion (PFC NE) that demonstrated analgesic efficacy across multiple rodent pain models in both sexes. Here, we report PFC-free, biphasic nanoemulsions formulated with a biocompatible and non-immunogenic plant-based coconut oil loaded with a COX-2 inhibitor and a clinical-grade, indocyanine green (ICG) near-infrared fluorescent (NIRF) dye for parenteral theranostic analgesic nanomedicine. Methods: Critical process parameters and material attributes were identified through the FMECA (Failure, Modes, Effects, and Criticality Analysis) method and optimized using a 3 × 2 full-factorial design of experiments. We investigated the impact of the oil-to-surfactant ratio (w/w) with three different surfactant systems on the colloidal properties of NE. Small-scale (100 mL) batches were manufactured using sonication and microfluidization, and the final formulation was scaled up to 500 mL with microfluidization. The colloidal stability of NE was assessed using dynamic light scattering (DLS) and drug quantification was conducted through reverse-phase HPLC. An in vitro drug release study was conducted using the dialysis bag method, accompanied by HPLC quantification. The formulation was further evaluated for cell viability, cellular uptake, and COX-2 inhibition in the RAW 264.7 macrophage cell line. Results: Nanoemulsion droplet size increased with a higher oil-to-surfactant ratio (w/w) but was no significant impact by the type of surfactant system used. Thermal cycling and serum stability studies confirmed NE colloidal stability upon exposure to high and low temperatures and biological fluids. We also demonstrated the necessity of a solubilizer for long-term fluorescence stability of ICG. The nanoemulsion showed no cellular toxicity and effectively inhibited PGE2 in activated macrophages. Conclusions: To our knowledge, this is the first instance of a celecoxib-loaded theranostic platform developed using a plant-derived hydrocarbon oil, applying the QbD approach that demonstrated COX-2 inhibition. Full article

The development of technology has driven a rising need for high-accuracy and high-efficiency manufacturing of low-volume products. Incremental forming technology, characterized by die-free flexibility and low production costs, can effectively replace stamping processes for manufacturing customized small-batch products. However, high-performance aluminum alloys generally exhibit poor room-temperature plasticity but excellent high-temperature plasticity, necessitating the integration of thermal-assisted methods for manufacturing such products. However, the temperature of the forming region will excessively rise without temperature control, which will affect the forming performance of the material in hot incremental sheet forming of AA2024-T4 aluminum alloy. This study focuses on AA2024-T4 aluminum alloy and proposes a uniform temperature control method for the electric hot tube-assisted incremental sheet forming process, incorporating an adaptive fuzzy PID algorithm. The temperature difference of the forming region is lower than 6% under the various temperatures. On this basis, the forming limit angle and the microstructure state of the material are analyzed, and the grain feature of the material exhibits significantly refined grains and the uniform fine grain distribution under 180 °C with the temperature control of the adaptive fuzzy PID algorithm. Full article

In recent years, the persistent emergence of novel infectious pathogens (epitomized by the global coronavirus disease-2019 (COVID-2019) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)) has propelled nucleic acid testing (NAT) into an unprecedented phase of rapid development. As a key technology in modern molecular diagnostics, NAT achieves precise pathogen identification through specific nucleic acid sequence recognition, establishing itself as an indispensable diagnostic tool across diverse scenarios, including public health surveillance, clinical decision-making, and food safety control. The reliability of NAT systems fundamentally depends on reference materials (RMs) that authentically mimic the biological characteristics of natural viruses. This critical requirement reveals significant limitations of current RMs in the NAT area: naked nucleic acids lack the structural authenticity of viral particles and exhibit restricted applicability due to stability deficiencies, while inactivated viruses have biosafety risks and inter-batch heterogeneity. Notably, pseudovirus has emerged as a novel RM that integrates non-replicative viral vectors with target nucleic acid sequences. Demonstrating superior performance in mimicking authentic viral structure, biosafety, and stability compared to conventional RMs, the pseudovirus has garnered substantial attention. In this comprehensive review, we critically summarize the engineering strategies of pseudovirus platforms and their emerging role in ensuring the reliability of NAT systems. We also discuss future prospects for standardized pseudovirus RMs, addressing key challenges in scalability, stability, and clinical validation, aiming to provide guidance for optimizing pseudovirus design and practical implementation, thereby facilitating the continuous improvement and innovation of NAT technologies. Full article

Enhanced Geothermal Systems (EGS) require thermochemically stable proppant materials capable of sustaining fracture conductivity under harsh subsurface conditions. This study systematically investigates the response of commercial proppants to coupled thermo-hydro-chemical (THC) effects, focusing on chemical stability and microstructural evolution. Four proppant types were evaluated: an ultra-low-density ceramic (ULD), a resin-coated sand (RCS), and two quartz-based silica sands. Experiments were conducted under simulated EGS conditions at 130 °C with daily thermal cycling over a 25-day period, using diluted site-specific Utah FORGE geothermal fluids. Static batch reactions were followed by comprehensive multi-modal characterization, including scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS), X-ray diffraction (XRD), and micro-computed tomography (micro-CT). Proppants were tested in both granular and powdered forms to evaluate surface area effects and potential long-term reactivity. Results indicate that ULD proppants experienced notable resin degradation and secondary mineral precipitation within internal pore networks, evidenced by a 30.4% reduction in intragranular porosity (from CT analysis) and diminished amorphous peaks in the XRD spectra. RCS proppants exhibited a significant loss of surface carbon content from 72.98% to 53.05%, consistent with resin breakdown observed via SEM imaging. While the quartz-based sand proppants remained morphologically intact at the macro-scale, SEM-EDS revealed localized surface alteration and mineral precipitation. The brown sand proppant, in particular, showed the most extensive surface precipitation, with a 15.2% increase in newly detected mineral phases. These findings advance understanding of proppant–fluid interactions under low-temperature EGS conditions and underscore the importance of selecting proppants based on thermo-chemical compatibility. The results also highlight the need for continued development of chemically resilient proppant formulations tailored for long-term geothermal applications. Full article

In the rapidly evolving field of biomedical engineering, hydrogels have emerged as highly versatile biomaterials that bridge biology and technology through their high water content, exceptional biocompatibility, and tunable mechanical properties. This review provides an integrated overview of both natural and synthetic hydrogels, examining their structural properties, fabrication methods, and broad biomedical applications, including drug delivery systems, tissue engineering, wound healing, and regenerative medicine. Natural hydrogels derived from sources such as alginate, gelatin, and chitosan are highlighted for their biodegradability and biocompatibility, though often limited by poor mechanical strength and batch variability. Conversely, synthetic hydrogels offer precise control over physical and chemical characteristics via advanced polymer chemistry, enabling customization for specific biomedical functions, yet may present challenges related to bioactivity and degradability. The review also explores intelligent hydrogel systems with stimuli-responsive and bioactive functionalities, emphasizing their role in next-generation healthcare solutions. In modern medicine, temperature-, pH-, enzyme-, light-, electric field-, magnetic field-, and glucose-responsive hydrogels are among the most promising “smart materials”. Their ability to respond to biological signals makes them uniquely suited for next-generation therapeutics, from responsive drug systems to adaptive tissue scaffolds. Key challenges such as scalability, clinical translation, and regulatory approval are discussed, underscoring the need for interdisciplinary collaboration and continued innovation. Overall, this review fosters a comprehensive understanding of hydrogel technologies and their transformative potential in enhancing patient care through advanced, adaptable, and responsive biomaterial systems. Full article

The treatment of contaminants from road infrastructure poses significant challenges due to their variable composition and the high concentrations of chloride ions, heavy metals, and oil-derived substances. Traditional methods for protecting groundwater environments are often insufficient. A promising alternative is permeable reactive barrier (PRB) technology, which utilizes recycled materials and construction waste as reactive components within the treatment zone of the ground. This paper delves into the potential of employing a composite (MIX) consisting of modified construction aggregate (as recycled material) and activated carbon (example of reactive material) to address environmental contamination from a mixture of heavy metals and chloride. The research involved chemical modifications of the road aggregate, activated carbon, and their composite, followed by laboratory tests in glass reactors and non-flow batch tests to evaluate the kinetics and chemical equilibrium of the reactions. The adsorption process was stable and conformed to the pseudo-second-order kinetics and Langmuir, Toth, and Redlich–Peterson isotherm models. Studies using MIX from a heavy metal model solution showed that monolayer adsorption was a key mechanism for removing heavy metals, with strong fits to the Langmuir (R² > 0.80) and Freundlich models, and optimal efficiencies for Cd and Ni (R² > 0.90). The best fit, at Cd, Cu, Ni = 0.96, however, was with the Redlich–Peterson isotherm, indicating a mix of physical and chemical adsorption on heterogeneous surfaces. The Toth model was significant for all analytes, fitting Cl and Cd well and Pb and Zn moderately. The modifications made to the composite significantly enhanced its effectiveness in removing the contaminant mixture. The test results demonstrated an average reduction of chloride by 85%, along with substantial removals of heavy metals: lead (Pb) by 90%, cadmium (Cd) by 86%, nickel (Ni) by 85%, copper (Cu) by 81%, and zinc (Zn) by 79%. Further research should focus on the removal of other contaminants and the optimization of magnesium oxide (MgO) dosage. Full article

The study focuses on optimizing the Fused Deposition Modeling (FDM) process by implementing a cost-efficient support structure strategy. The main objective is to develop a systematic approach for analyzing structural and technological parameters considering print time, material consumption, and surface quality. The study focus is on manually designed support structures as an alternative to automatic generation, allowing for precise control over print settings. The methodology includes comparative analysis of various support strategies using a Prusa MK3S+ printer under standardized conditions. Statistical and visual evaluations confirm that the designed support structures reduce print time by up to 59 min while maintaining comparable material use and superior surface finish. The findings offer a practical framework for optimizing 3D printing processes, reducing waste, and enhancing efficiency in prototyping and small-batch production. Full article

This work investigates, for the first time, the application of a modified natural magnetite material with 35% of lanthanum for phosphorus (P) recovery from synthetic and actual wastewater under both static (batch) and dynamic (continuous stirred tank reactor (CSTR)) conditions. The characterization results showed that the natural feedstock mainly comprises magnetite and kaolinite. Moreover, the lanthanum-modified magnetite (La-MM) exhibited more enhanced textural, structural, and surface chemistry properties than the natural feedstock. In particular, its surface area (82.7 m² g⁻¹) and total pore volume (0.160 cm³ g⁻¹) were higher by 86.6% and 255.5%, respectively. The La-MM efficiently recovered P in batch mode under diverse experimental settings with an adsorption capacity of 50.7 mg g⁻¹, which is significantly greater than that of various engineered materials. It also maintained high efficiency even when used for the treatment of actual wastewater, with an adsorption capacity of 47.3 mg g⁻¹. In CSTR mode, the amount of P recovered from synthetic solutions and real wastewater decreased to 33.8 and 10.2 mg g⁻¹, respectively, due to the limited contact time. The phosphorus recovery process involves mainly electrostatic attraction over a wide pH interval, complexation, and precipitation as lanthanum phosphates. This investigation indicates that lanthanum-modified natural feedstocks from magnetite deposits can be regarded as promising materials for P recovery from aqueous solutions. Full article

The dichromate ion (Cr₂O₇²⁻), a highly toxic chromium VI species, is widely used in industrial processes, generating serious environmental problems when released into water bodies. This investigation proposes the use of a functionalized polymer as an adsorbent material for its removal in the aqueous phase. Poly(butyl methacrylate) (PBMA) was synthesized and modified by impregnation with resorcinarenes derived from long-chain aliphatic aldehydes. To improve the affinity for the dichromate, the resorcinarenes were functionalized with sulfomethyl groups by treatment with Na₂SO₃. The resulting matrices were characterized using IR-ATR, ¹H-NMR, and ¹³C-NMR, and their adsorbent performance was evaluated via UV-Vis spectroscopy in batch extraction assays. The results showed that the functionalized polymer exhibited a higher adsorption capacity than the base polymer, reaching up to 81.1% removal at pH 5.0 in one hour. These results highlight the potential of PBMA as an effective support and raise a promising research perspective for functionalized resorcinarenes in the development of new materials for the treatment of contaminated water. Full article

Air quality monitoring IoT is one of the approaches to achieving a sustainable future. However, the large area of IoT and the high number of monitoring microsites pose challenges for device maintenance to guarantee quality of service (QoS) in monitoring. This paper proposes a novel maintenance programming model for a large-area IoT containing 1500 monitoring microsites. In contrast to classic device maintenance, the addressed programming scenario considers the division of appropriate microsites into batches, the determination of the batch maintenance date, vehicle routing for the delivery of maintenance services, and a set of hard constraints such as QoS in air quality monitoring, the maximum number of labor working hours, and an upper limit on the total CO₂ emissions. Heuristics are proposed to generate the batches of microsites and the scheduled maintenance date for the batches. A genetic algorithm is designed to find the shortest routes by which to visit the batch microsites by a fleet of vehicles. Simulations are conducted based on government open data. The experimental results show that the maintenance and transportation costs yielded by the proposed model grow linearly with the number of microsites if the fleet size is also linearly related to the microsite number. The mean time between two consecutive cycles is around 17 days, which is generally sufficient for the preparation of the required maintenance materials and personnel. With the proposed method, the decision-maker can circumvent the difficulties in handling the hard constraints, and the allocation of maintenance resources, including budget, materials, and engineering personnel, is easier to manage. Full article

This paper presents an integrated computational framework for predicting temperature fields in glulam beam–column connections under fire conditions, combining finite element modeling, automated parametric analysis, and deep learning techniques. A high-fidelity heat transfer finite element model was developed, incorporating the anisotropic thermal properties of wood and temperature-dependent material behavior, validated against experimental data with strong agreement. To enable large-scale parametric studies, an automated Abaqus model modification and data processing system was implemented, improving computational efficiency through the batch processing of geometric and material parameters. The extracted temperature field data was used to train a DeepONet neural network, which achieved accurate temperature predictions (with a L2 relative error of 1.5689% and an R² score of 0.9991) while operating faster than conventional finite element analysis. This research establishes a complete workflow from fundamental heat transfer analysis to efficient data generation and machine learning prediction, providing structural engineers with practical tools for the performance-based fire safety design of timber connections. The framework’s computational efficiency enables comprehensive parametric studies and design optimizations that were previously impractical, offering significant advancements for structural fire engineering applications. Full article

In this study, an efficient and cost-effective nanocomposite material based on Opuntia ficus indica (cactus) powder modified with iron oxide nanoparticles was developed as an adsorbent for the removal of methylene blue (MB), a common water pollutant. The nanocomposite was synthesized through the co-precipitation method of Fe²⁺ and Fe³⁺ ions and characterized using Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) coupled with energy-dispersive X-ray spectroscopy (EDS) and thermogravimetric analysis (TGA). Batch adsorption experiments were conducted over 24 h, varying different operational conditions, such as pH, temperature and initial pollutant concentration. Furthermore, a Box–Behnken design was employed to develop an empirical model for predicting removal efficiency and optimizing the adsorption conditions. The effects of adsorption variables including contact time (1–60 min), initial MB concentration (20–100 mg/L), pH (2–12), adsorbent dosage (2–6 g/L) and temperature (25–55 °C) on the removal capacity were examined. Under optimal conditions, the maximum removal efficiency of MB reached approximately 96%, with a maximum adsorption capacity of 174 mg/g, as predicted by the Langmuir model. The synthesized cactus/iron oxide nanocomposite demonstrated significant potential as an adsorbent for treating MB-contaminated water. Full article

SiC MOSFETs are becoming increasingly popular due to their superior material properties, but they lack the required reliability and ruggedness for safe applications. One of the biggest challenges in short-circuit (SC) reliability of the commercial devices and hence in the SC protection circuit design is the variability of SC withstand time (SCWT) among the devices from the same vendor, even with the same lot and batch number. In this work, a novel SC screening methodology has been presented to remove devices with lower SCWT from a pool of devices without damaging the reliable ones. The SC screening methodology has been developed using Sentaurus TCAD simulation, which is further verified using commercial devices. This work can potentially reduce field failure and, as a result, can enhance the reliability of the SiC MOSFETs in real-world applications. Full article

The reprocessing of metallurgical wastes to recover much-needed metals such as copper not only ensures an adequate supply of metals but also contributes to the cleaning of the environment. A copper smelter in Namibia accumulated significant amounts of spent refractory bricks that are enriched with metal values including copper. This supposedly waste material can potentially serve as a supplement to the ore concentrate, as a smelter feedstock for this toll smelter. Representative samples of crushed bricks, designated as Sample 1 and Sample 2, were used for mineralogical characterisation and flotation test work. The assays for Sample 1 and Sample 2 were 14% Cu and 18% Cu, respectively. Microscopy results identified various copper phases including metallic Cu, bornite, malachite and chalcopyrite. Batch flotation tests were conducted to investigate the effect of grind size (P₈₀ of 53, 75 and 106 μm), pulp pH (natural pulp pH, 10, 10.5 and 11) and collector (potassium amyl xanthate, PAX) dosage (70, 100 and 130 g/t) on the recovery of copper, concentrate grade and weight recovery. In some tests, a co-collector (dithiophosphate, DTP) and sulphidiser (Na₂S) were also added in the quest to maximise the recovery of copper. Based on the test conditions investigated in this study, the grind size is the key variable affecting the recovery of copper. The best copper recovery of 86% (with a weight recovery in the range of 42 to 45% (w/w) and concentrate grade of 37% Cu) was achieved for the finest grind size of 53 μm. The reagent suite that yielded the best recovery was 70 g/t PAX with no addition of the sulphidiser while the pH was 10. There is scope for developing the process routes to recover other valuable metals such as iron, lead and zinc that are also in the spent bricks, as well as potential reuse of the spent bricks (after recovering valuable metals) to make new refractory bricks. Full article

To ensure the inherent safety of fine chemical nitration processes, the nitration reaction of benzotriazole ketone was selected as the research object. The thermal decomposition and reaction characteristics of the nitration system were studied using a combination of differential scanning calorimetry (DSC), reaction calorimetry (RC1), and accelerating rate calorimetry (ARC). The results showed that the nitration product released 455.77 kJ/kg of heat upon decomposition, significantly higher than the 306.86 kJ/kg of the original material, indicating increased thermal risk. Through process hazard analysis based on GB/T 42300-2022, key parameters such as the temperature at which the time to maximum rate is 24 h under adiabatic conditions (T_D24), maximum temperature of the synthesis reaction (MTSR), and maximum temperature for technical reason (MTT) were determined, and the reaction was classified as hazard level 5, suggesting a high risk of runaway and secondary explosion. Process intensification strategies were then proposed and verified by dynamic calorimetry: the adiabatic temperature increase (ΔT_ad) was reduced from 86.70 °C in the semi-batch reactor to 19.95 °C in the optimized continuous process, effectively improving thermal safety. These findings provide a reliable reference for the quantitative risk evaluation and safe design of nitration processes in fine chemical manufacturing. Full article