Catalytic graphene formation in coal tar pitch- derived carbon structure in the presence of SiO2 nanoparticles

A simple and effective way to manufacture graphene from a coal tar pitch (CTP) is demonstrated. Silica (SiO₂) nanoparticles were used to modify the CTP as carbon precursor. A silica nanofiller introduced into the CTP matrix underwent carboreduction during heat treatment to 2000 °C, resulting in the formation of silicon carbide. Surfaces of SiC grains were sites for graphene formation. The influence of SiO₂ on the structure and microstructure of CTP- based carbon matrix, after annealing up to 2800 °C, was studied. Carbon samples were analyzed using X- ray Diffraction (XRD), Transmission Electron Microscopy (TEM) and Raman Spectroscopy. Crystallite sizes (L_a, L_c) and interplanar distance (d₀₀₂) were determined. The presence of SiO₂ in CTP carbon precursor favored the crystallites’ growth in the ‘a′ crystallographic graphite direction, and inhibited their growth on the ‘c′ axis. The crystallites composing of graphene layers, were characterized by an elongated dimension in the ‘a′ axis direction. Above 2000 °C silicon carbide decomposed, followed by the sublimation of silicon from the carbon matrix.     

Hydroxyl Group Separation Distances in Anti-Freeze Compounds and Their Effects on Ice Nucleation

Since the discovery of biological antifreeze glycoproteins (AFGPs), which can inhibit ice nucleation, there has been considerable interest in understanding their mechanisms and mimicking them in synthetic polymers. In this study, we used molecular dynamics simulations of modified polyvinyl alcohol (PVA) compounds to show that the hydroxyl (OH) group distance is a key factor in whether certain compounds promote or inhibit ice nucleation. A hydroxyl distance smaller than ~2.8 Å but greater than ~7.1 Å in modified PVA (MPVA) compounds was associated with the promotion of ice nucleation, while a hydroxyl group separation distance of approximately ~5.0 Å was correlated with a delay in ice nucleation, owing to changes in the energy of the system. Thus, these results may help explain some of the mechanisms of current known anti-freeze compounds and may have implications for designing new anti-freeze compounds in the future.     

Properties of Non-Aminoglycoside Compounds Used to Stimulate Translational Readthrough of PTC Mutations in Primary Ciliary Dyskinesia

Primary ciliary dyskinesia (PCD) is a rare disease with autosomal recessive inheritance, caused mostly by bi-allelic gene mutations that impair motile cilia structure and function. Currently, there are no causal treatments for PCD. In many disease models, translational readthrough of premature termination codons (PTC-readthrough) induced by aminoglycosides has been proposed as an effective way of restoring functional protein expression and reducing disease symptoms. However, variable outcomes of pre-clinical trials and toxicity associated with long-term use of aminoglycosides prompt the search for other compounds that might overcome these problems. Because a high proportion of PCD-causing variants are nonsense mutations, readthrough therapies are an attractive option. We tested a group of chemical compounds with known PTC-readthrough potential (ataluren, azithromycin, tylosin, amlexanox, and the experimental compound TC007), collectively referred to as non-aminoglycosides (NAGs). We investigated their PTC-readthrough efficiency in six PTC mutations found in Polish PCD patients, in the context of cell and cilia health, and in comparison to the previously tested aminoglycosides. The NAGs did not compromise the viability of the primary nasal respiratory epithelial cells, and the ciliary beat frequency was retained, similar to what was observed for gentamicin. In HEK293 cells transfected with six PTC-containing inserts, the tested compounds stimulated PTC-readthrough but with lower efficiency than aminoglycosides. The study allowed us to select compounds with minimal negative impact on cell viability and function but still the potential to induce PTC-readthrough.     

Efficiency optimisation of the thermal energy storage unit in the form of the ceiling panel for summer conditions

The thermal energy storage unit in the form of the ceiling panel made of the gypsum‐microencapsulated phase change material composite with internal U‐shaped channels was optimised applying previously developed 1D‐3D numerical simulator. Calculations were carried out for variable inlet velocities of air, different properties of the composite expressed by enthalpy‐temperature curves, and summer climatic conditions in Central Poland (Warsaw). Optimal working temperature ranges of the composite were determined. Moreover, studies showed that for Central Poland, composites with wide ranges of the working temperature are preferred due to significant daily variations of ambient temperature during the whole summer.     

Two implementation relations and the correctness of communicating replicated processes

This paper studies the correctness of distributed systems made up of replicated processes that communicate by message passing. Processes are described within the divergence model of CSP. The notion of correctness introduced is based on a relation that formally expresses the conformance of an implementation process with the target process it is intended to implement. A weak and a strong version of the relation are introduced, aimed at treating acyclic and cyclic process networks respectively. Both allow the study of (total) correctness and may cope with non-deterministic targets and implementations.We then show how a target process may be implemented (in the formal sense introduced) by replicating it in a set of copies, a majority of which is non-faulty.     

The Dynamic Emission Zone in Sandwich Polymer Light‐Emitting Electrochemical Cells

In light‐emitting electrochemical cells (LECs), the position of the emission zone (EZ) is not predefined via a multilayer architecture design, but governed by a complex motion of electrical and ionic charges. As a result of the evolution of doped charge transport layers that enclose a dynamic intrinsic region until steady state is reached, the EZ is often dynamic during turn‐on. For thick sandwich polymer LECs, a continuous change of the emission color provides a direct visual indication of a moving EZ. Results from an optical and electrical analysis indicate that the intrinsic zone is narrow at early times, but starts to widen during operation, notably well before the electrical device optimum is reached. Results from numerical simulations demonstrate that the only precondition for this event to occur is that the mobilities of anions (μ_a) and cations (μ_c) are not equal, and the direction of the EZ shift dictates μ_c > μ_a. Quantitative ion profiles reveal that the displacement of ions stops when the intrinsic zone stabilizes, confirming the relation between ion movement and EZ shift. Finally, simulations indicate that the experimental current peak for constant‐voltage operation is intrinsic and the subsequent decay does not result from degradation, as commonly stated.     

Identification of Wiener models for dynamic and steady‐state performance with application to solid oxide fuel cell

This work is concerned with identification of Wiener models (a linear dynamic part connected in series with a nonlinear dynamic one). A neural network with one hidden layer is used as the nonlinear block of the model, two network configurations are considered. For model identification three algorithms are described. In the first case model accuracy only in transient conditions is considered, only the dynamic data is used for model training. In the next two algorithms model accuracy in both transient and steady‐state conditions is considered, dynamic and steady‐state data sets are used. The steady‐state model errors are taken into account by an additional term in the minimized cost‐function or by additional inequality constraints. For comparison of discussed algorithms and model structures, identification of a Wiener model of a solid oxide fuel cell (SOFC) process is considered. It is shown that the best results are obtained by the algorithm 2 which minimizes at the same time both dynamic and steady‐state model errors, additional constraints used in the algorithm 3 are computationally quite demanding.