A novel ceramic matrix composite based on YNbO4–TiO2 for microwave applications

This work presents the dielectric properties of YNbO₄ (YNO)–TiO₂ composites in the microwave range. X-ray diffraction analysis demonstrates that the addition of TiO₂ to YNO results in the formation of a Y(Nb_0.5Ti_0.5)₂O₆ phase. In the microwave range, the values of permittivity and dielectric loss did not present major changes with the increment of TiO₂. Moreover, the addition of TiO₂ results in an improvement in the thermal stability of YNO, with YNO63 demonstrating a resonant frequency of ?8.96 ppm.°C^?1. We utilised numerical simulations to evaluate the behaviour of these materials as dielectric resonator antennae and it is found that they exhibit a reflection coefficient below ?10 dB at the resonant frequency, with a realised gain of 4.94 – 5.76 dBi, a bandwidth of 665–1050 MHz and a radiation efficiency above 84%. Our results indicate that YNO–TiO₂ composites are interesting candidates for microwave operating devices.     

Validation of scientific topic models using graph analysis and corpus metadata

Probabilistic topic modeling algorithms like Latent Dirichlet Allocation (LDA) have become powerful tools for the analysis of large collections of documents (such as papers, projects, or funding applications) in science, technology an innovation (STI) policy design and monitoring. However, selecting an appropriate and stable topic model for a specific application (by adjusting the hyperparameters of the algorithm) is not a trivial problem. Common validation metrics like coherence or perplexity, which are focused on the quality of topics, are not a good fit in applications where the quality of the document similarity relations inferred from the topic model is especially relevant. Relying on graph analysis techniques, the aim of our work is to state a new methodology for the selection of hyperparameters which is specifically oriented to optimize the similarity metrics emanating from the topic model. In order to do this, we propose two graph metrics: the first measures the variability of the similarity graphs that result from different runs of the algorithm for a fixed value of the hyperparameters, while the second metric measures the alignment between the graph derived from the LDA model and another obtained using metadata available for the corresponding corpus. Through experiments on various corpora related to STI, it is shown that the proposed metrics provide relevant indicators to select the number of topics and build persistent topic models that are consistent with the metadata. Their use, which can be extended to other topic models beyond LDA, could facilitate the systematic adoption of this kind of techniques in STI policy analysis and design.

     

Modernization of Air Supply Unit for Oxidation Towers Used in Bitumen Production

Chemical and Petroleum Engineering - The hydrodynamics of oxidation towers used for bitumen production were studied using a model tower having transparent walls. Experiments were carried out in two...     

Two-step sinter-crystallization of K2O–CaO–P2O5–SiO2 (45S5-K) bioactive glass

Bioactive glasses and glass-ceramics (GCs) effectively regenerate bone tissue, however most GCs show improved mechanical properties. In this work, we developed and tested a rarely studied bioactive glass composition (24.4K₂O-26.9CaO-46.1SiO₂-2.6P₂O₅ mol%, identified as 45S5-K) with different particle sizes and heating rates to obtain a sintered GC that combines good fracture strength, low elastic modulus, and bioactivity. We analyzed the influence of the sintering processing conditions in the elastic modulus, Vickers microhardness, density, and crystal phase formation in the GC. The best GC shows improved properties compared with its parent glass. This glass achieves a good densification degree with a two-step viscous flow sintering approach and the resulting GC shows as high bioactivity as that of the standard 45S5 Bioglass®. Furthermore, the GC elastic modulus (56 GPa) is relatively low, minimizing stress shielding. Therefore, we unveiled the glass sintering behavior with concurrent crystallization of this complex bioactive glass composition and developed a potential GC for bone regeneration.     

Structural Aspects of P2-Type Na0.67Mn0.6Ni0.2Li0.2O2 (MNL) Stabilization by Lithium Defects as a Cathode Material for Sodium-Ion Batteries

A known strategy for improving the properties of layered oxide electrodes in sodium-ion batteries is the partial substitution of transition metals by Li. Herein, the role of Li as a defect and its impact on sodium storage in P2-Na_0.67Mn_0.6Ni_0.2Li_0.2O₂ is discussed. In tandem with electrochemical studies, the electronic and atomic structure are studied using solid-state NMR, operando XRD, and density functional theory (DFT). For the as-synthesized material, Li is located in comparable amounts within the sodium and the transition metal oxide (TMO) layers. Desodiation leads to a redistribution of Li ions within the crystal lattice. During charging, Li ions from the Na layer first migrate to the TMO layer before reversing their course at low Na contents. There is little change in the lattice parameters during charging/discharging, indicating stabilization of the P2 structure. This leads to a solid-solution type storage mechanism (sloping voltage profile) and hence excellent cycle life with a capacity of 110 mAh g^-1 after 100 cycles. In contrast, the Li-free compositions Na_0.67Mn_0.6Ni_0.4O₂ and Na_0.67Mn_0.8Ni_0.2O₂ show phase transitions and a stair-case voltage profile. The capacity is found to originate from mainly Ni³⁺/Ni⁴⁺ and O^2-/O^2-δ redox processes by DFT, although a small contribution from Mn⁴⁺/Mn⁵⁺ to the capacity cannot be excluded.     

QoS metrics-in-the-loop for endowing runtime self-adaptation to robotic software architectures

Multimedia Tools and Applications - The design of robots capable of operating autonomously in changing and unstructured environments, requires using complex software architectures in which,...     

As the number falls,alternatives to the Hagberg–Perten falling number method: A review

This review examines the application, limitations, and potential alternatives to the Hagberg–Perten falling number (FN) method used in the global wheat industry for detecting the risk of poor end-product quality mainly due to starch degradation by the enzyme α-amylase. By viscometry, the FN test indirectly detects the presence of α-amylase, the primary enzyme that digests starch. Elevated α-amylase results in low FN and damages wheat product quality resulting in cakes that fall, and sticky bread and noodles. Low FN can occur from preharvest sprouting (PHS) and late maturity α-amylase (LMA). Moist or rainy conditions before harvest cause PHS on the mother plant. Continuously cool or fluctuating temperatures during the grain filling stage cause LMA. Due to the expression of additional hydrolytic enzymes, PHS has a stronger negative impact than LMA. Wheat grain with low FN/high α-amylase results in serious losses for farmers, traders, millers, and bakers worldwide. Although blending of low FN grain with sound wheat may be used as a means of moving affected grain through the marketplace, care must be taken to avoid grain lots from falling below contract-specified FN. A large amount of sound wheat can be ruined if mixed with a small amount of sprouted wheat. The FN method is widely employed to detect α-amylase after harvest. However, it has several limitations, including sampling variability, high cost, labor intensiveness, the destructive nature of the test, and an inability to differentiate between LMA and PHS. Faster, cheaper, and more accurate alternatives could improve breeding for resistance to PHS and LMA and could preserve the value of wheat grain by avoiding inadvertent mixing of high- and low-FN grain by enabling testing at more stages of the value stream including at harvest, delivery, transport, storage, and milling. Alternatives to the FN method explored here include the Rapid Visco Analyzer, enzyme assays, immunoassays, near-infrared spectroscopy, and hyperspectral imaging.     

Current advances concerning the most cited metal ions doped bioceramics and silicate-based bioactive glasses for bone tissue engineering

Studies related to biomaterials that stimulate the repair of living tissue have increased considerably, improving the quality of many people's lives that require surgery due to traumatic accidents, bone diseases, bone defects, and reconstructions. Among these biomaterials, bioceramics and bioactive glasses (BGs) have proved to be suitable for coating materials, cement, scaffolds, and nanoparticles, once they present good biocompatibility and degradability, able to generate osteoconduction on the surrounding tissue. However, the role of biomaterials in hard tissue engineering is not restricted to a structural replacement or for guiding tissue regeneration. Nowadays, it is expected that biomaterials develop a multifunctional role when implanted, orchestrating the process of tissue regeneration and providing to the body the capacity to heal itself. In this way, the incorporation of specific metal ions in bioceramics and BGs structure, including magnesium, silver, strontium, lithium, copper, iron, zinc, cobalt, and manganese are currently receiving enhanced interest as biomaterials for biomedical applications. When an ion is incorporated into the bioceramic structure, a new category of material is created, which has several unique properties that overcome the disadvantages of primitive material and favors its use in different biomedical applications. The doping can enhance handling properties, angiogenic and osteogenic performance, and antimicrobial activity. Therefore, this review aims to summarize the effect of selected metal ion dopants into bioceramics and silicate-based BGs in bone tissue engineering. Furthermore, new applications for doped bioceramics and BGs are highlighted, including cancer treatment and drug delivery.     

Analyzing the Conditions for the Electrolytic Formation of Ensembles from Metal Nanowires in the Pores of Track Membranes

Theoretical Foundations of Chemical Engineering - The effect of the electrolyte composition, mass-transfer conditions, pore diameter, interpore distance, and electric parameters on the formation of...