Search Results (1,600)

This study presents a simulation-based damage modeling and fatigue risk assessment of a reusable ceramic matrix composite thruster designed for short-duration, green bipropellant propulsion systems. The thruster is constructed from a fiber-reinforced ultra-high temperature ceramic matrix composite composed of zirconium diboride, silicon carbide, and carbon fibers. Time-resolved thermal and structural simulations are conducted on a validated thruster geometry to characterize the severity of early-stage thermal shock, stress buildup, and potential degradation pathways. Unlike traditional fatigue studies that rely on empirical fatigue constants or Paris-law-based crack-growth models, this work introduces a simulation-derived stress-margin envelope methodology that incorporates ±20% variability in temperature-dependent material strength, offering a physically grounded yet conservative risk estimate. From this, a normalized risk index is derived to evaluate the likelihood of damage initiation in critical regions over the 0–10 s firing window. The results indicate that the convergent throat region experiences a peak thermal gradient rate of approximately 380 K/s, with the normalized thermal shock index exceeding 43. Stress margins in this region collapse by 2.3 s, while margin loss in the flange curvature appears near 8 s. These findings are mapped into green, yellow, and red risk bands to classify operational safety zones. All the results assume no active cooling, representing conservative operating limits. If regenerative or ablative cooling is implemented, these margins would improve significantly. The framework established here enables a transparent, reproducible methodology for evaluating lifetime safety in ceramic propulsion nozzles and serves as a foundational tool for fatigue-resilient component design in green space engines. Full article

Superhydrophobic and superoleophilic nanofibrous or microfibrous membranes are regarded as ideal oil/water separation materials owing to their controllable porosity, superior separation efficiency, and ease of operation. However, developing efficient, scalable, and environmentally friendly strategies for fabricating such membranes remains a significant challenge. In this study, isotactic polypropylene (iPP) fibrous membranes with morphologies ranging from ellipsoidal stacking to microfiber stacking were successfully fabricated via a multistage stretching extrusion and leaching process using in situ microfibrillar composites (MFCs). The results establish a significant relationship between microfiber morphology and membrane oil adsorption performance. Compared with membranes formed from high-aspect-ratio microfibers, those comprising short microfibers feature larger pores and a more open structure, which enhances their oil adsorption capacity. Among the fabricated membranes, the iPP membrane with an ellipsoidal stacking morphology exhibits optimal performance, achieving a porosity of 65% and demonstrating both hydrophobicity and superoleophilicity, with a silicone oil adsorption capacity of up to 312.5%. Furthermore, this membrane shows excellent reusability and stability over ten adsorption–desorption cycles using chloroform. This study presents a novel approach leveraging in situ microfibrillar composites to prepare high-performance oil/water separation membranes in this study, underscoring their considerable promise for practical use. Full article

Heavy metal contamination in natural waters and soils poses a significant environmental challenge, necessitating efficient and sustainable water treatment solutions. This study presents the computational design of low-density polyethylene (LDPE) films functionalized with iron oxide (Fe₃O₄) nanoparticles (NPs) for enhanced water purification applications. Composite materials containing 5%, 10%, and 15% were synthesized and characterized in terms of adsorption efficiency, surface morphology, and reusability. Advanced molecular modeling using BIOVIA Pipeline was employed to investigate charge distribution, functional group behaviour, and atomic-scale interactions between polymer chains and metal ions. The computational results revealed structure–property relationships crucial for optimizing adsorption performance and understanding geochemically driven interaction mechanisms. The LDPE/Fe₃O₄ composites demonstrated significant removal efficiency of Cu²⁺ and Ni²⁺ ions, along with favourable mechanical properties and regeneration potential. These findings highlight the synergistic role of mineral–polymer interfaces in water remediation, presenting a scalable approach to designing multifunctional polymeric materials for environmental applications. This study contributes to the growing field of polymer-based adsorbents, reinforcing their value in sustainable water treatment technologies and environmental protection efforts. Full article

Steel pickling sludge serves as a valuable iron source for synthesizing Fe-based catalysts in heterogeneous advanced oxidation processes (AOPs). Here, MoS₂@CoFe₂O₄ catalyst derived from steel pickling sludge was prepared via a facile solvothermal approach and utilized to activate peroxymonosulfate (PMS) for tetracycline hydrochloride (TCH) degradation. Comprehensive characterization using scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XRD) confirmed the supported microstructure, composition, and crystalline structure of the catalyst. Key operational parameters—including catalyst dosage, PMS concentration, and initial pH—were systematically optimized, achieving 81% degradation efficiency within 30 min. Quenching tests and EPR analysis revealed ∙SO₄^‒ as the primary oxidative species, while the catalyst maintained high stability and reusability across cycles. TCH degradation primarily occurs through hydroxylation, decarbonylation, ring-opening, and oxidation reactions. This study presents a cost-effective strategy for transforming steel pickling sludge into a high-performance Fe-based catalyst, demonstrating its potential for practical AOP applications. Full article

In an era of exponential data growth, ensuring high data quality has become essential for effective, evidence-based decision making. This study presents a structured and comparative review of the field by integrating data classifications, quality dimensions, assessment methodologies, and modern software tools. Unlike earlier reviews that focus narrowly on individual aspects, this work synthesizes foundational concepts with formal frameworks, including the Findable, Accessible, Interoperable, and Reusable (FAIR) principles and the ISO/IEC 25000 series on software and data quality. It further examines well-established assessment models, such as Total Data Quality Management (TDQM), Data Warehouse Quality (DWQ), and High-Quality Data Management (HDQM), and critically evaluates commercial platforms in terms of functionality, AI integration, and adaptability. A key contribution lies in the development of conceptual mappings that link data quality dimensions with FAIR indicators and maturity levels, offering a practical reference model. The findings also identify gaps in current tools and approaches, particularly around cost-awareness, explainability, and process adaptability. By bridging theory and practice, the study contributes to the academic literature while offering actionable insights for building scalable, standards-aligned, and context-sensitive data quality management strategies. Full article

Cloudy huyou juice is increasingly popular for its unique flavor, but flocculent precipitation after cold storage and thawing affects its sensory quality and increases production costs. This study optimized the clarification of thawed cloudy huyou juice using a composite of carboxymethyl chitosan (CC) and sodium alginate (SA), prepared via ionic and covalent crosslinking. The composite was characterized by SEM, FTIR, and thermal analysis. Transmittance was used to evaluate clarification performance. The effects of dosage, adsorption time, and temperature were first assessed through single-factor experiments, followed by optimization using a Box–Behnken response surface methodology. The composite significantly improved clarity (p < 0.05), reaching 85.38% transmittance under optimal conditions: 22 mg dosage, 80 min time, and 38 °C. The composite dosage and temperature were the most influential factors. Reusability tests showed declining performance, with the transmittance dropping to 57.13% after five cycles, likely due to incomplete desorption of adsorbed compounds. These results suggest that the CC-SA composite is an effective and reusable clarifying agent with potential for industrial applications in turbid fruit juice processing. Full article

An anion exchange-assisted technique was used for the synthesis of platinum-decorated SnO₂ supports, providing nanocatalysts with enhanced activity for the reduction of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP). In this study, a series of SnO₂ supports, namely SnA (synthesized almost at room temperature), SnB (hydrothermally treated at 180 °C), and SnC (annealed at 600 °C), are systematically investigated, all loaded with 1 mol% Pt from H₂PtCl₆ under identical mild conditions. The chloride ions from the SnCl₄ precursors were efficiently removed via a strong-base anion exchange reaction, resulting in highly dispersed, crystalline ~5 nm cassiterite SnO₂ particles. All Pt/SnO₂ composites displayed mesoporous structures with type IVa isotherms and H₂-type hysteresis, with SP1a (Pt on SnA) exhibiting the largest surface area (122.6 m²/g) and the smallest pores (~3.5 nm). STEM-HAADF imaging revealed well-dispersed PtOx domains (~0.85 nm), while XPS confirmed the dominant Pt⁴⁺ and Pt²⁺ species, with ~25% Pt⁰ likely resulting from photoreduction and/or interactions with Sn–OH surface groups. Raman spectroscopy revealed three new bands (260–360 cm⁻¹) that were clearly visible in the sample with 10 mol% Pt and were due to the vibrational modes of the PtOx species and Pt-Cl bonds introduced due the addition and hydrolysis of H₂PtCl₆ precursor. TGA/DSC analysis revealed the highest mass loss for SP1a (~7.3%), confirming the strong hydration of the PtOx domains. Despite the predominance of oxidized PtOx species, SP1a exhibited the highest catalytic activity (k_app = 1.27 × 10⁻² s⁻¹) and retained 84.5% activity for the reduction of 4-NP to 4-AP after 10 cycles. This chloride-free low-temperature synthesis route offers a promising and generalizable strategy for the preparation of noble metal-based nanocatalysts on oxide supports with high catalytic activity and reusability. Full article

A facile method was adopted to fabricate β-C₃N₄, and it was then doped with manganese and tellurium to obtain novel 10%MnTeO₃@β-C₃N₄ (10%MnTe@β) and 20%MnTeO₃@β-C₃N₄ (20%MnTe@β) nanohybrids. The β-C₃N₄, 10%MnTe@β, and 20%MnTe@β showed surface areas of 85.86, 97.40, and 109.54 m² g⁻¹, respectively. Using ciprofloxacin (CIP) as a pollutant example, 10%MnTe@β and 20%MnTe@β attained equilibrium at 60 and 45 min with q_t values of 48.88 and 77.41 mg g⁻¹, respectively, and both performed better at pH = 6.0. The kinetic studies revealed a better agreement with the pseudo-second-order model for CIP sorption on 10%MnTe@β and 20%MnTe@β, indicating that the sorption was controlled by a liquid film mechanism, which suggests a high affinity of CIP toward 10%MnTe@β and 20%MnTe@β. The sorption equilibria outputs indicated better alignment with the Freundlich and Langmuir models for CIP removal by 10%MnTe@β and 20%MnTe@β, respectively. The thermodynamic analysis revealed that CIP removal by 10%MnTe@β and 20%MnTe@β was exothermic, which turned more spontaneous as the temperature decreased. Applying 20%MnTe@β as the best sorbent to groundwater and seawater spiked with CIP resulted in average efficiencies of 94.8% and 91.08%, respectively. The 20%MnTe@β regeneration–reusability average efficiency was 95.14% within four cycles, which might nominate 20%MnTe@β as an efficient and economically viable sorbent for remediating CIP-contaminated water. Full article

Nanomaterials possess unique physicochemical properties that position them as promising candidates for environmental remediation, particularly in the removal of persistent organic pollutants (POPs) from aqueous systems. Their high surface area, tunable functionality, and strong adsorption capabilities have attracted significant attention. In this context, this paper reviews the mechanisms of nanomaterial-based POP decontamination, also providing a critical overview of the limitations and challenges in applying these methods. Specifically, issues of stability, reusability, and aggregation are discussed, which can lead to performance decay during repeated use. In addition, the practical application requires nanocomposites to enable efficient separation and mitigate agglomeration. Environmental concerns also arise from nanomaterials’ fate, transport, and potential toxicity, which may impact aquatic ecosystems and non-target organisms. When checking for large-scale application feasibility, impurities typically add to production costs, recovery problems, and general infrastructure limitations. In addition to these points, there are no standard guidelines or clear risk assessment procedures for registering a product. Unprecedented cross-disciplinary research between natural, human, and technological studies and outreach programs is needed to facilitate the development and diffusion of the results. The barriers will eventually be breached to move from laboratory success in developing the desperately needed new water purification technologies to field-ready water treatment solutions that can address the global POP contamination problem. Full article

It is well established that effective management and restoration of freshwater ecosystems is often limited by the availability of reusable data. Although numerous public, private, and nonprofit organizations collect data from freshwater ecosystems, much of what is collected remains inaccessible or unusable by Rights holders and end users (including researchers, practitioners, community members, and decision-makers). In Canada, the federal government plans to improve freshwater data sharing practices through the newly formed Canada Water Agency, which is currently drafting a National Freshwater Data Strategy. Our study aimed to support these efforts by synthesizing insights from the technology sector, where data management and sharing practices are more mature. We interviewed 12 experts from the technology sector, asking them for advice on how to improve data sharing practices in the freshwater science sector. Using a Reflexive Thematic Analysis of participants’ responses to semi-structured interview questions, we identified nine broad recommendations. Recommendations centred on motivating open data sharing, promoting data reuse through data licences, training and skill building, and developing standards and digital solutions that enable data discovery, accessibility, interoperability, and reuse. These recommendations can support the numerous initiatives that are working to improve access to high-quality freshwater data and help address the pressing crisis of global freshwater ecosystem degradation. Full article

The increasing presence of ECs in aquatic environments has drawn significant attention to the need for innovative, accessible, and sustainable solutions in wastewater treatment. This review provides a comprehensive overview of the use of agricultural residues—often discarded and undervalued—as raw materials for the development of efficient bioadsorbents. Based on a wide range of recent studies, this work presents various types of materials, such as rice husks, sugarcane bagasse, and açaí seeds, that can be transformed through thermal and chemical treatments into advanced bioadsorbents capable of removing pharmaceuticals, pesticides, dyes, and in some cases, even addressing highly persistent pollutants such as PFASs. The main objectives of this review are to (1) assess agricultural-residue-derived bioadsorbents for the removal of ECs; (2) examine physical and chemical modification techniques that enhance adsorption performance; (3) evaluate their scalability and applicability in real-world treatment systems. The review also highlights key adsorption mechanisms—such as π–π interactions, hydrogen bonding, and ion exchange—alongside the influence of parameters like pH and ionic strength. The review also explores the kinetic, isothermal, and thermodynamic aspects of the adsorption processes, highlighting both the efficiency and reusability potential of these materials. This work uniquely integrates microwave-assisted pyrolysis, magnetic functionalization, and hybrid systems, offering a roadmap for sustainable water remediation. Finally, comparative performance analyses, applications using real wastewater, regeneration strategies, and the integration of these bioadsorbents into continuous treatment systems are presented, reinforcing their promising role in advancing sustainable water remediation technologies. Full article

Addressing the urgent need for lightweight and reusable energy-absorbing materials in aviation impact resistance, this study introduces an innovative multi-directional braided metamaterial design enabled by 4D printing technology. This approach overcomes the dual challenges of intricate manufacturing processes and the limited functionality inherent to traditional textile preforms. Six distinct braided structural units (types 1–6) were devised based on periodic trigonometric functions (Y = A sin(12πX)), and integrated with shape memory polylactic acid (SMP-PLA), thereby achieving a synergistic combination of topological architecture and adaptive response characteristics. Compression tests reveal that reducing strip density to 50–25% (as in types 1–3) markedly enhances energy absorption performance, achieving a maximum specific energy absorption of 3.3 J/g. Three-point bending tests further demonstrate that the yarn amplitude parameter A is inversely correlated with load-bearing capacity; for instance, the type 1 structure (A = 3) withstands a maximum load stress of 8 MPa, representing a 100% increase compared to the type 2 structure (A = 4.5). A multi-branch viscoelastic constitutive model elucidates the temperature-dependent stress relaxation behavior during the glass–rubber phase transition and clarifies the relaxation time conversion mechanism governed by the Williams–Landel–Ferry (WLF) and Arrhenius equations. Experimental results further confirm the shape memory effect, with the type 3 structure fully recovering its original shape within 3 s under thermal stimulation at 80 °C, thus addressing the non-reusability issue of conventional energy-absorbing structures. This work establishes a new paradigm for the design of impact-resistant aviation components, particularly in the context of anti-collision structures and reusable energy absorption systems for eVTOL aircraft. Future research should further investigate the regulation of multi-stimulus response behaviors and microstructural optimization to advance the engineering application of smart textile metamaterials in aviation protection systems. Full article

Ontologies are essential tools for representing, organizing, and sharing knowledge across various domains. This study presents a methodology for ontology construction supported by large language models (LLMs), with an initial application in the automotive sector. Specifically, a user preference ontology for adaptive interfaces in autonomous machines was developed using ChatGPT-4o. Based on this case study, the results were generalized into a reusable methodology. The proposed workflow integrates classical ontology engineering methodologies with the generative and analytical capabilities of LLMs. Each phase follows well-established steps: domain definition, term elicitation, class hierarchy construction, property specification, formalization, population, and validation. A key innovation of this approach is the use of a guiding table that translates domain knowledge into structured prompts, ensuring consistency across iterative interactions with the LLM. Human experts play a continuous role throughout the process, refining definitions, resolving ambiguities, and validating outputs. The ontology was evaluated in terms of logical consistency, structural properties, semantic accuracy, and inferential completeness, confirming its correctness and coherence. Additional validation through SPARQL queries demonstrated its reasoning capabilities. This methodology is generalizable to other domains, if domain experts adapt the guiding table to the specific context. Despite the support provided by LLMs, domain expertise remains essential to guarantee conceptual rigor and practical relevance. Full article

To enhance the accuracy and reliability of large language models (LLMs) in regulatory question-answering tasks, this study addresses the complexity and domain-specificity of regulatory texts by designing a retrieval-augmented generation (RAG) testing framework. It proposes a dimensionality reduction-based semantic similarity measurement method and a retrieval optimization approach leveraging information reasoning. Through the construction of the technical route of the intelligent knowledge management system, the semantic understanding capabilities of multiple mainstream embedding models in the text matching of financial regulations are systematically evaluated. The workflow encompasses data processing, knowledge base construction, embedding model selection, vectorization, recall parameter analysis, and retrieval performance benchmarking. Furthermore, the study innovatively introduces a multidimensional scaling (MDS) based semantic similarity measurement method and a question-reasoning processing technique. Compared to traditional cosine similarity (CS) metrics, these methods significantly improved recall accuracy. Experimental results demonstrate that, under the RAG testing framework, the mxbai-embed-large embedding model combined with MDS similarity calculation, Top-k recall, and information reasoning effectively addresses core challenges such as the structuring of regulatory texts and the generalization of domain-specific terminology. This approach provides a reusable technical solution for optimizing semantic matching in vertical-domain RAG systems, particularly for MDSs such as law and finance. Full article

Data is the starting point for generating information and knowledge in the decision-making process. Open data, which is information disclosed free of charge through open licenses and reusable formats, has great potential for value creation. Therefore, the objective of this research is to evaluate Spanish autonomous communities’ open data initiatives in a category of information of vital importance: housing. The methodology employed was a population analysis of datasets labeled as housing, followed by a necessary data cleansing process due to the identification of various errors, which reduced the number of labeled datasets from 1000 to 599. Only 12 of the 17 autonomous communities provided this type of information. The analysis of the results reveals that autonomous communities’ approaches to open data initiatives are highly heterogeneous and that the supply is irregular, with the Basque Country accounting for 70% of the datasets considered in the research. The creation of an indicator that equally assesses the existence of information and file formats (breadth and reusability) continues to identify the Basque Country as the undisputed leader, with Catalonia and Cantabria in second and third place, the only autonomous communities to exceed 50 points out of a possible 100. The study concludes by highlighting that the lack of uniformity in the formulation and implementation of open data policies will limit the use of information and, consequently, its value. Therefore, a series of recommendations is issued in this regard. Full article