Search Results (435)

The demand for clean energy to improve waste valorization and enhance resource utilization efficiency has been increasingly recognized in the last few years. In this context, the co-carbonization of different waste streams, aiming at solid fuel production, appears as a potential strategy to address the challenges of the energy transition and divert waste from landfills. In this work, refuse-derived fuel (RDF) samples were subjected to the co-carbonization process with low-quality animal fat waste in different proportions to assess the synergistic effect of the mixture on producing chars with enhanced fuel properties. Dry (DC) and hydrothermal carbonization (HTC) tests were conducted at 425 °C and 300 °C, respectively, with a residence time of 30 min. The RDF sample and produced chars with different animal fat incorporation were analyzed for their physical, chemical, and fuel properties. The results demonstrated that increasing the fat proportion in the samples leads to an increase in mass yield and apparent density of the produced chars. Furthermore, char samples with higher fat addition presented a proportional increase in high heating value (HHV). The highest values for the HHV corresponded to the char samples produced with 30% fat incorporation for both carbonization techniques (27.9 MJ/kg and 32.9 MJ/kg for dry and hydrothermal carbonization, respectively). Fat addition also reduced ash content, improved hydrophobicity in hydrochars, and lowered ignition temperature, although additional washing was necessary to reduce chlorine to acceptable levels. Furthermore, fat incorporation reduced concentrations of elements linked to slagging and fouling. Overall, the results demonstrate that incorporating 30% fat into RDF during DC or HTC is the most effective condition for producing chars with improved physical, chemical, and fuel properties, enhancing their potential as alternative solid fuels. Full article

We systematically investigate the combined impact of process variation effects (PVEs), metal gate work function fluctuation (WKF), and random dopant fluctuation (RDF) on the key electrical characteristics of sub-1-nm technology node gate-all-around silicon nanosheet complementary field-effect transistors (GAA Si NS CFETs). Through comprehensive statistical analysis, we reveal that the interplay of these intrinsic and extrinsic sources of variability induces significant fluctuations in the off-state leakage current across both N-/P-FETs in GAA Si NS CFETs. The sensitivity to process-induced variability is found to be particularly pronounced in the P-FETs, primarily due to the enhanced parasitic conduction associated with the bottom nanosheet channel. Given the correlated nature of PVE, WKF, and RDF factors, the statistical sum (RSD) of the fluctuation for each factor is overestimated by less than 50% compared with the simultaneous fluctuations of PVE, WKF, and RDF factors. Furthermore, although the static power dissipation remains relatively small compared to dynamic and short-circuit power components, it exhibits the largest relative fluctuation (approximately 82.1%), posing critical challenges for low-power circuit applications. These findings provide valuable insights into the variability-aware design and optimization of GAA NS CFET device fabrication processes, as well as the development of robust and reliable CFET-based integrated circuits for next-generation technology nodes. Full article

Modern cloud-based Internet of Things (IoT) infrastructures face increasingly sophisticated and diverse cyber threats that challenge traditional detection systems in terms of scalability, adaptability, and explainability. In this paper, we present (H-DIR)², a hybrid entropy-based framework designed to detect and mitigate anomalies in large-scale heterogeneous networks. The framework combines Shannon entropy analysis with Associated Random Neural Networks (ARNNs) and integrates semantic reasoning through RDF/SPARQL, all embedded within a distributed Apache Spark 3.5.0 pipeline. We validate (H-DIR)² across three critical attack scenarios—SYN Flood (TCP), DAO-DIO (RPL), and NTP amplification (UDP)—using real-world datasets. The system achieves a mean detection latency of 247 ms and an AUC of 0.978 for SYN floods. For DAO-DIO manipulations, it increases the packet delivery ratio from 81.2% to 96.4% (p < 0.01), and for NTP amplification, it reduces the peak load by 88%. The framework achieves vertical scalability across millions of endpoints and horizontal scalability on datasets exceeding 10 TB. All code, datasets, and Docker images are provided to ensure full reproducibility. By coupling adaptive neural inference with semantic explainability, (H-DIR)² offers a transparent and scalable solution for cloud–IoT cybersecurity, establishing a robust baseline for future developments in edge-aware and zero-day threat detection. Full article

The development of high-performance solid electrolytes is critical to advancing solid-state lithium-ion batteries (SSBs), with lithium lanthanum zirconium oxide (LLZO) emerging as a leading candidate due to its chemical stability and wide electrochemical window. In this study, we systematically investigated the effects of cation dopants, including aluminum (Al³⁺), tantalum (Ta⁵⁺), gallium (Ga³⁺), and rubidium (Rb⁺), on the structural, electronic, and ionic transport properties of LLZO using density functional theory (DFT) and ab initio molecular dynamics (AIMD) simulations. It appeared that, among all simulated results, Al-LLZO exhibits the highest ionic conductivity of 1.439 × 10⁻² S/cm with reduced activation energy of 0.138 eV, driven by enhanced lithium vacancy concentrations and preserved cubic-phase stability. Ta-LLZO follows, with a conductivity of 7.12 × 10⁻³ S/cm, while Ga-LLZO and Rb-LLZO provide moderate conductivity of 3.73 × 10⁻³ S/cm and 3.32 × 10⁻³ S/cm, respectively. Charge density analysis reveals that Al and Ta dopants facilitate smoother lithium-ion migration by minimizing electrostatic barriers. Furthermore, Al-LLZO demonstrates low electronic conductivity (1.72 × 10⁻⁸ S/cm) and favorable binding energy, mitigating dendrite formation risks. Comparative evaluations of radial distribution functions (RDFs) and XRD patterns confirm the structural integrity of doped systems. Overall, Al emerges as the most effective and economically viable dopant, optimizing LLZO for scalable, durable, and high-conductivity solid-state batteries. Full article

Parametric changes in the first coordination shell (FCS) of a vitreous metallic Pd_42.5Cu₃₀Ni_7.5P₂₀ alloy are analysed, aiming to confirm the identification of the glass transition temperature (T_g) via processing of XRD patterns utilising radial and pair distribution functions (RDFs and PDFs) and their evolution with temperature. The Wendt–Abraham empirical criterion of glass transition and its modifications are confirmed in line with previous works, which utilised the kink of the temperature dependences of the minima and maxima of both the PDF and the maxima of the structure factor S(q). Massive fluctuations are, however, identified near the T_g of the derivatives of the minima and maxima of the PDF and maxima of S(q), which adds value to understanding the glass transition in the system as a true second-order-like phase transformation in the non-equilibrium system of atoms. Full article

Soil nematodes are essential components of the soil food web and are widely recognised as key bioindicators of soil health because of their sensitivity to environmental factors and disturbance. In agriculture, many studies have documented the effects of fertilisation on nematode communities and explored their role in nutrient cycling. Despite this, a key gap in knowledge still exists regarding how fertilisation-induced changes in nematode communities modify their role in nutrient cycling. We reviewed the literature on the mechanisms by which nematodes contribute to nutrient cycling and on how organic, inorganic, and recycling-derived fertilisers (RDFs) impact nematode communities. The literature revealed that the type of organic matter and its C:N ratio are key factors shaping nematode communities in organically fertilised soils. In contrast, soil acidification and ammonium suppression have a greater influence in inorganically fertilised soils. The key sources of variability across studies include differences in the amount of fertiliser applied, the duration of the fertiliser use, management practices, and context-specific factors, all of which led to differences in how nematode communities respond to both fertilisation regimes. The influence of RDFs on nematode communities is largely determined by the fertiliser’s origin and its chemical composition. While fertilisation-induced changes in nematode communities affect their role in nutrient cycling, oversimplifying experiments makes it difficult to understand nematodes’ functions in these processes. The challenges and knowledge gaps for further research to understand the effects of fertilisation on soil nematodes and their impact on nutrient cycling have been highlighted in this review to inform sustainable agricultural practices. Full article

A Roman dominating function f of a graph $G=(V,E)$ assigns labels from the set $\{0,1,2\}$ to vertices such that every vertex labeled 0 has a neighbor labeled 2. The weight of an RDF f is defined as $w\left(f\right)={\sum }_{v\in V}f\left(v\right)$, and the Roman domination number, ${\gamma }_R\left(G\right)$, is the minimum weight among all RDFs of G. This paper studies the domination and Roman domination numbers in Cartesian bundles of cycles. Furthermore, the constructed optimal patterns improve known bounds and suggest even better bounds might be achieved by combining patterns, especially for bundles involving shifts of order $4k$ and $5k$. Full article

In the landslide chain from pre-disaster conditions to landslide mitigation and recovery, time is an important factor in understanding the geological hazards process and managing landsides. Static knowledge graphs are unable to capture the temporal dynamics of landslide events. To address this limitation, we propose a systematic framework for constructing a multi-temporal knowledge graph of landslides that integrates multi-source temporal data, enabling the dynamic tracking of landslide processes. Our approach comprises three key steps. First, we summarize domain knowledge and develop a temporal ontology model based on the disaster chain management system. Second, we map heterogeneous datasets (both tabular and textual data) into triples/quadruples and represent them based on the RDF (Resource Description Framework) and quadruple approaches. Finally, we validate the utility of multi-temporal knowledge graphs through multidimensional queries and develop a web interface that allows users to input landslide names to retrieve location and time-axis information. A case study of the Zhangjiawan landslide in the Three Gorges Reservoir Area demonstrates the multi-temporal knowledge graph’s capability to track temporal updates effectively. The query results show that multi-temporal knowledge graphs effectively support multi-temporal queries. This study advances landslide research by combining static knowledge representation with the dynamic evolution of landslides, laying the foundation for hazard forecasting and intelligent early-warning systems. Full article

Current treatment methods for desulfurization wastewater in the ship exhaust gas cleaning (EGC) system face several problems, including process complexity, unstable performance, large spatial requirements, and high energy consumption. This study investigates rotating dynamic filtration (RDF) as an efficient treatment approach through experimental testing, theoretical analysis, and pilot-scale validation. Flux increases with temperature and pressure but decreases with feed concentration, remaining unaffected by circulation flow. For a small membrane (152 mm), flux consistently increases with rotational speed across all pressures. For a large membrane (374 mm), flux increases with rotational speed at 300 kPa but firstly increases and then decreases at 100 kPa. Filtrate turbidity in all experiments complies with regulatory standards. Due to the unique hydrodynamic characteristics of RDF, back pressure reduces the effective transmembrane pressure, whereas shear force mitigates concentration polarization and cake layer formation. Separation performance is governed by the balance between these two forces. The specific energy consumption of RDF is only 10–30% that of cross-flow filtration (CFF). Under optimized pilot-scale conditions, the wastewater was concentrated 30-fold, with filtrate turbidity consistently below 2 NTU, outperforming CFF. Moreover, continuous operation proves more suitable for marine environments. Full article

Municipal solid waste (MSW) and refuse-derived fuel (RDF) incineration generate over 20 million tons of residues annually in the EU. These include bottom ash (IBA), fly ash (FA), and air pollution control residues (APCr), which pose significant environmental challenges due to their leaching potential and hazardous properties. While these residues contain valuable metals and reactive mineral phases suitable for carbonation or alkaline activation, chemical, techno-economic, and policy barriers have hindered the implementation of sustainable, full-scale management solutions. Accelerated carbonation technology (ACT) offers a promising approach to simultaneously sequester CO₂ and enhance residue stability. This review provides a comprehensive assessment of waste incineration residue carbonation, covering 227 documents ranging from laboratory studies to field applications. The analysis examines reactor designs and process layouts, with a detailed classification based on material characteristics, operating conditions, investigated parameters, and the resulting pollutant stabilization, CO₂ uptake, or product performance. In conclusion, carbonation-based approaches must be seamlessly integrated into broader waste management strategies, including metal recovery and material repurposing. Carbonation should be recognized not only as a CO₂ sequestration process, but also as a binding and stabilization strategy. The most critical barrier remains chemical: the persistent leaching of sulfates, chromium(VI), and antimony(V). We highlight what we refer to as the antimony problem, as this element can become mobilized by up to three orders of magnitude in leachate concentrations. The most pressing research gap hindering industrial deployment is the need to design stabilization approaches specifically tailored to critical anionic species, particularly Sb(V), Cr(VI), and SO₄²⁻. Full article

The Internet is not just used for communication, transactions, and cloud storage; it also serves as a massive knowledge store where both people and machines can create, analyze, and use data and information. The Semantic Web was designed to enable machines to interpret the meaning of data, facilitating more informed and autonomous decision-making. The foundation of the Semantic Web is the Resource Description Framework (RDF). The standard RDF is limited to representing simple binary relationships in the form of the $<subjectpredicateobject>$ triple. In this paper, we present a new data model called BiTemporal RDF (BiTRDF), which adds valid time and transaction time to the standard RDF. Our approach treats temporal information as references instead of attributes, simplifying the semantics while enhancing the model’s expressiveness and consistency. BiTRDF treats all resources and relationships as inherently bitemporal, enabling the representation and reasoning of complex temporal relationships in RDF. Illustrative examples demonstrate the model’s support for type propagation, domain-range inference, and transitive relationships in a temporal setting. While this work lays a theoretical foundation, future research will address implementation, query language support, and compatibility with RDF streams and legacy systems. Full article

The substituent effects on crystal stacking topology and stability of the 5,5-dinitro-2H,2H-3,3-bi-1,2,4-triazole (DNBT) and its three energetic cocrystals with 1,3,5-trinitrobenzene (TNB), 2,4,6-trinitrotoluene (TNT), and picric acid (PA) were systematically investigated through combined density functional theory (DFT) calculations and classical molecular dynamics (MD) simulations. The interaction mechanism and detonation performance of the three energetic cocrystals were implemented to the electrostatic potential (ESP), Hirshfeld surface analysis, radial distribution function (RDF), binding energy, and detonation parameters. In contrast to N-H⋯O interactions in DNBT, three cocrystals exhibited more distinctly weak C-H⋯O intermolecular hydrogen bonds and NO₂-π stacking interactions to stabilize the lattice. Notably, the highest binding energy of PA/DNBT shows the largest stability and lowest impact sensitivity is related to the more intermolecular interactions. Although the introduction of substituents slightly affects the crystal density of DNBT crystals, it significantly reduces the impact sensitivity. Moreover, the balanced detonation performance and impact sensitivity of DNBT-based cocrystals make it a candidate to expand the applications of DNBT crystals. These findings contribute to a broadened understanding of construction and design strategies for the energy release mechanisms of energetic compounds with the azoles ring family. Full article

In architectural heritage conservation, fragmented data practices and heterogeneous formats hinder knowledge extraction, limiting the translation of raw data into actionable conservation insights. This study proposes a knowledge-centric framework integrating smart data methodologies to bridge this gap. The framework synergizes Heritage Building Information Modeling (HBIM), semantic knowledge graphs, and knowledge bases, prioritizing three interconnected dimensions: geometric digitization through 3D laser scanning and parametric HBIM reconstruction, semantic enrichment of historical texts via NLP and rule-based entity extraction, and knowledge graph-driven discovery of spatiotemporal patterns using Neo4j and ontology mapping. Validated through dual case studies—the Historical Educational Sites in South China (humanistic narratives) and the Dong ethnic drum towers (structural logic)—the framework demonstrates its capacity to automate knowledge generation, converting 20.5 GB of multi-source data into 2652 RDF triples that interconnect 1701 nodes across HBIM models and archival records. By enabling real-time visualization of semantic relationships (e.g., educator networks, mortise-and-tenon typologies) through graph queries, the system enhances interdisciplinary collaboration. Furthermore, the proposed smart data framework facilitated the generation of domain-specific knowledge through systematic data valorization, yielding actionable insights for architectural conservation practice. This research redefines conservation as a knowledge-to-action paradigm, where smart data methodologies unify tangible and intangible heritage values, fostering data-driven stewardship across cultural, historical, and technical domains. Full article

Most modified asphalts require high-temperature shearing and prolonged mixing to achieve a uniform structure, often resulting in substantial exhaust gas pollution. This study explores the utilization of polyurethane (PU) as a warm mix asphalt modifier, leveraging its favorable compatibility with asphalt at lower temperatures to mitigate emissions. To address the inherent limitations of PU-modified asphalt mixtures, namely, poor low-temperature performance and susceptibility to water damage, silane coupling agents (SCAs) are introduced to reinforce the asphalt–aggregate interfacial strength. At the microscopic level, the optimal PU content (20.8%) was determined through analysis of micro-viscosity and radial distribution functions (RDFs). SCA effects on interfacial properties were assessed using adhesion work, adhesion depth, and interfacial thermal stability. At the macroscopic level, performance metrics—including strength, high-temperature resistance, low-temperature resistance, and water stability—were evaluated against a benchmark hot mix SBS-modified asphalt mixture. The results indicate that PU-modified asphalts exhibit superior high-temperature performance and strength but slightly lower low-temperature performance and insufficient water stability. The addition of SCAs improved both low-temperature and water stability attributes, enabling the mixtures to meet specification requirements. The simulation results suggest that KH-550, which chemically reacts with isocyanate groups (-OCN) in PU, exhibits a better interfacial reinforcement effect than KH-570. Therefore, KH-550 is recommended as the preferred SCA for PU-modified asphalt mixtures in practical applications. Full article

n-Octanol and related ether alcohols are studied via molecular dynamics (MD) simulations using the two classical all-atom force fields OPLS-AA and CHARMM. The ether alcohols studied possess one ether functionality separated by varying n carbon atoms from the hydroxy group to elucidate how the positioning of the ether functionality affects intra- and intermolecular hydrogen bonding and, in turn, the physical properties of the studied alcohols. Important general trends observed from simulations with both force fields include the following: Intramolecular hydrogen bonding is majorly present in 3-butoxypropanol and 4-propoxybutanol (n = 3 and 4) while being only marginally present for 5-ethoxypentanol and 6-methoxyhexanol (n = 5 and 6) and absent in 1-hexyloxymethanol and 2-pentyloxyethanol (n = 1 and 2). The intramolecular hydrogen bonds formed by 3-butoxypropanol and 4-propoxybutanol are among the most stable ones of all present hydrogen bonds. Intermolecular hydrogen bonding is stronger between hydroxy groups (OH-OH) than between hydroxy and ether groups (OH-OE). An increased temperature causes a reduction in intermolecular OH-OH and OH-OE hydrogen bonding but a slight increase in intramolecular hydrogen bonding. A reduction in end-to-end distances at a higher temperature is also observed for all studied alcohols, which is likely a reflection of increased dihedral bond rotations. Hydrogen bonding extends mostly between just two molecules while hydrogen bonding networks are rare but do exist, involving, in some instances, up to 30 hydrogen bonds. Regardless of force field and temperature, the obtained radial distribution functions (RDFs) mostly show the same features at same distances that only vary in their intensity. 1-hexyloxymethanol forms a very specific and stable intermolecular double OH-OE hydrogen-bonded dimer. Similar double-hydrogen-bonded dimers can be found for the ether alcohols but are only significantly present for 2-pentyloxyethanol. Overall, the main difference between OPLS-AA and CHARMM is their quantitative prediction of the present hydrogen bonding speciation largely due to the stiffer dihedral potentials in OPLS-AA compared to the CHARMM force field. The simulations indicate that (a) the variations in densities are correlated to the reduced packing efficiency caused by intramolecular hydrogen bonding, (b) self-diffusion correlates with the stability of the intermolecular hydrogen bonds, and (c) the presence of hydrogen-bonded networks, although small in numbers, affect the viscosity. Full article