Metal-Bound Methisazone; Novel Drugs Targeting Prophylaxis and Treatment of SARS-CoV-2, a Molecular Docking Study

SARS-CoV-2 currently lacks effective first-line drug treatment. We present promising data from in silico docking studies of new Methisazone compounds (modified with calcium, Ca; iron, Fe; magnesium, Mg; manganese, Mn; or zinc, Zn) designed to bind more strongly to key proteins involved in replication of SARS-CoV-2. In this in silico molecular docking study, we investigated the inhibiting role of Methisazone and the modified drugs against SARS-CoV-2 proteins: ribonucleic acid (RNA)-dependent RNA polymerase (RdRp), spike protein, papain-like protease (PlPr), and main protease (MPro). We found that the highest binding interactions were found with the spike protein (6VYB), with the highest overall binding being observed with Mn-bound Methisazone at −8.3 kcal/mol, followed by Zn and Ca at −8.0 kcal/mol, and Fe and Mg at −7.9 kcal/mol. We also found that the metal-modified Methisazone had higher affinity for PlPr and MPro. In addition, we identified multiple binding pockets that could be singly or multiply occupied on all proteins tested. The best binding energy was with Mn–Methisazone versus spike protein, and the largest cumulative increases in binding energies were found with PlPr. We suggest that further studies are warranted to identify whether these compounds may be effective for treatment and/or prophylaxis.     

Catalytic upgrading of 4-methylaniosle as a representative of lignin-derived pyrolysis bio-oil: Process evaluation and optimization via coupled application of design of experiment and artificial neural networks

Catalytic upgrading of 4-methylanisole as a representative of lignin-derived pyrolysis bio-oil was investigated over Pt/γ-Al₂O₃ catalyst. The catalytic upgrading process was conducted at different operating condition to determine the detailed reactions network. Additionally, artificial neural network and design of experiment were applied by feeding the reaction temperature, operating pressure and space velocity to predict 4-methylanisole conversion, main products selectivity, reactions rate and reactions network. The main products of 4-methylanisole upgrading were toluene, phenol derivatives, cyclohexanone, 4-methylcyclohexanone, and 2-tert-butyl-4-methylphenol. The major classes of reactions during the upgrading process were hydrogenolysis, hydrodeoxygenation, alkylation, and hydrogenation. For optimization of experimental data obtained at suggested conditions by design of experiment, the response surface methodology was applied. Artificial neural network model was used to investigate the kinetics behavior of the system due to the complex nature of system. A combination of the response surface methodology, artificial neural network, and design of experiment has revealed its ability to solve a quadratic polynomial model. The coefficients of determination were close to 1, and the mean square error of the artificial neural network model was close to 0 which showed the high accuracy of model predictions. It was inferred that during the upgrading process of 4-methylanisole, increasing temperature and pressure and setting space velocity at the minimum value are the reasons to come close to the optimum reaction rate. The comparison of experimental results with simulated data from the artificial neural network and the response surface methodology models illustrated that the developed model can create an applicable situation for practical design of large-scale production of valuable fuels from renewable resources.     

Properties of Coated Controlled Release Diammonium Phosphate Fertilizers Prepared with the Use of Bio-based Amino Oil

In an effort to enhance the efficiency of fertilizer use and minimize their negative impact on the environment, a novel biomass-based, functional controlled-release fertilizer was used to improve nutrient use efficiency and increase crop production systems for more sustainable agriculture practices. Here, bio-based amino-oil (Priamine) mixtures were proposed as an outer coating with different layers for the control of phosphorus release from diammonium Phosphate (DAP). These hydrophobic coatings conferred excellent barrier properties and flexibility to coatings. The morphological characterization of the coated fertilizer was performed by scanning electronic microscopy (SEM), electronic diffraction X-ray (EDX) and mapping, and revealed the formation of a cohesive film and a good adhesion between DAP fertilizer and coating film. The release rate of nutrients (phosphate) in water was investigated by UV–Vis spectrophotometer. The effect of coating thickness was investigated on release time and diffusion coefficient of phosphor release in distilled water. Release time increased with the coating thickness. The diffusion coefficient of nutrient release decreased with the coating thickness. Compared with uncoated granule which is totally solubilized after less than 2 hours, the P release profiles of the coated granules reached the equilibrium stage approximately after 98 and 126 hours when the DAP is coated with only Priamine single-layer (1L) and double-layer (2L), respectively. Moreover, the strategy adopted has successfully provided a very slow release and long-term availability of nutrient sources with bio-based coating oil compared to uncoated fertilizer (DAP) and therefore exhibited promising application for sustainable development of modern agriculture and circular economic.     

Battery Recovery-Aware Optimization for Embedded System Communications

Wireless Personal Communications - In this paper, we consider a point-to-point wireless communications for embedded battery powered systems. We aim to provide an optimal use of all the usable...     

High-efficient multifunctional self-heating nanocomposite-based MWCNTs for energy applications

Self-heating of nanocomposite materials based on the joule heating effect is suitable for numerous engineering applications. In this study, a high-efficiency self-heating nanocomposite, using high conductive multi-walled carbon nanotubes (MWCNTs)-based phenolic resin, was fabricated with a hot press method. The microstructure and the thermal stability of self-heating nanocomposite were studied by X-ray diffraction, scanning electronic microscopy, and thermogravimetric tests. Electromechanical and thermal performance tests were conducted to investigate their potential as a self-heating application. Results showed that the compressive strength, modulus, and the piezo-resistive behaviour were higher after adding MWCNTs to the phenolic resin, indicating better load transfer and self-damage sensing as well. Moreover, at 4.0 wt% of MWCNTs concentration, the electrical conductivity of a self-heating nanocomposite showed a higher value of 13.26 S/m which was also found to be proportionally increased with the thickness of the samples, it was ≈25.5 and ≈12.8 S/m for 10 and 3 mm, respectively. In addition, a steady-state temperature of ≈110°C could be reached at low applied volts (8 V) as well as its heating performance was significantly dependent on the input power and the thickness of the sample. This is also confirmed by statistical results between the sample with thicknesses of 3 and 10 mm in terms of power consumption with P value ≈ .0001. Furthermore, the influence of Joule heating was estimated analytically based on the one-dimensional heat transfer equation in companying with other previous models. The estimated distributed temperatures values were in good agreement with the experimental results. The self-heating nanocomposite described in this study has the potential to be used in various industrial applications and a wide range of sectors due to its ability to self-damage sensing, easy fabrication, and high heating efficiency at low power consumption.     

Performance improvement of supercritical carbon dioxide power cycles through its integration with bottoming heat recovery cycles and advanced heat exchanger design: A review

In this article, the performance improvement of supercritical carbon dioxide (sCO₂) Brayton cycles through heat recovery and advanced heat exchanger (HX) design is reviewed. The configuration of sCO₂ cycles and the bottleneck of the design of an efficient sCO₂ cycle is first evaluated. It was found that heat rejected in the precooler is a large waste that could potentially enhance the overall sCO₂ system performance. Then integration of the absorption cycle, organic Rankine cycle, and thermal desalination plant to the sCO₂ cycle to recover the waste thermal energy is reviewed and discussed. Results showed that these bottoming heat recovery cycles could substantially improve the overall sCO₂ system efficiency. The combined system of sCO₂/absorption chiller, sCO₂/ORC increases the cycle efficiency to about 78% and 79%, respectively. Also, a combined system of sCO₂/desalination produces about 200 000 m³/day with a cost of less than $1.0/m³. Based on the review, the evaluation criteria are proposed for decision-makers. Another bottleneck of the design of the sCO₂ system is the HXs (recuperators) used in the sCO₂ cycle which are relatively large and negatively affect the cycle compactness and performance. Therefore, various types of recuperators proposed and designed for sCO₂ cycles are reviewed and evaluated. This review highlights the need for further research to enhance heat recovery, reduce the cost of bottoming cycles, and improve the design of HXs.     

Efficient analysis of parametric sensitivity and uncertainty of fuel cell models with application to SOFC

Sensitivity analysis (SA) and uncertainty quantification (UQ) are used to assess and improve engineering models. SA of fuel cell models can be challenging because of the large number of design parameters to optimize. Following the regular approach of manually testing the fuel cell outputs under changing each design parameter one at a time can be tedious. In this work, a framework of SA and UQ methods is applied with a purpose of efficiently analysing fuel cell models. The SA and UQ methods are also compared to increase the confidence in the results. In this methodology, all design parameters and their effects can be analysed in an integrated form, where model variance, sensitivity, linearity/nonlinearity, parameter interactions, and importance ranking can be assessed. This paper highlights and compares between local SA (one-at-a-time linear perturbation), parameter screening (Morris screening), variance decomposition (Sobol indices), and regression-based SA. For UQ, stochastic methods (Monte Carlo sampling) and deterministic methods (using SA profiles) are used. All methods are applied to solid oxide fuel cell (SOFC) to analyse the power output and system efficiency under 21 uncertain design parameters. Using different methods, the uncertainty in the SOFC responses (maximum power and efficiency) is about 11%, when the current density is about 13 200 A m⁻². In addition, analysis shows that operating temperature (T), length of grain contact (X), grain size (D_s), porosity (ϵ), and electrolyte thickness (L_e) contribute to more than 97% of the SOFC's maximum power variance, with individual contributions as follows: 63.3%, 13.1%, 12.5%, 5.4%, and 3.6%, respectively. The previous conclusions are subjective to the simplified SOFC model used in this study to demonstrate the methods. Benchmarking the UQ methods in capturing the response uncertainty and the SA methods in raking the design parameters demonstrate very good agreement between them. The methods applied in this paper can be used to achieve a comprehensive mathematical understanding of more advanced fuel cell or energy models, which can lead to better performance.     

Cathodic activation of synthesized highly defective monoclinic hydroxyl-functionalized ZrO2 nanoparticles for efficient electrochemical production of hydrogen in alkaline media

The high electrochemical stability of Zirconia (ZrO₂) at high potentials strongly suggested it as an alternative to carbon supports, which experience reduced efficiency due to some corrosion problems particularly during prolonged electrocatalysis activity. However, the use of ZrO₂ was limited by its low electrical conductivity and surface area. In this work, we developed a methodology for synthesizing monoclinic ZrO₂ NPs with increased surface area and improved electrical/electrocatalytic characteristics without using any carbon-based co-support material or any metallic nanoparticles. In this context, for the first time, highly defective hydroxyl-functionalized ZrO₂ NPs (designated here as ZT NPs) were prepared by a hydrothermal route in the presence of sodium tartrate as a mineralizer. XRD analysis demonstrated that the produced zirconia was semicrystalline microspheres, consisting of monoclinic ZrO₂ NPs with high lattice defects. The addition of tartrate ions decreased the crystallite size and increased the defects and microstrain. At the same time, the alkaline hydrogen evolution reaction (HER) catalytic activity of ZrO₂ NPs was significantly increased when using sodium tartrate as mineralizer; the overpotential required to obtain 10 mA cm⁻² (η₁₀) dropped down from 490 to merely 235 mV, while an exchange current density (j_o) increased 12 times to 0.22 mA cm⁻². The presence of structural defects (revealed by XRD) and the increased number of active surface sites contending O-H groups (evidenced from ATR-FTIR and XPS) as well as the enhanced electrochemical active surface area (confirmed from double-layer capacitance measurements) were the main reasons behind the high catalytic performance. The ZrO₂ NPs catalytic activity increased even further during the long-term stability tests under severe cathodic conditions (ZT*, ZrO₂ NPs obtained after the long-term stability, has j_o = 0.47 mA cm⁻² and η₁₀ = 140 mV), approaching the activity of Pt/C catalyst. This process was assisted by mineralizer removal from the catalyst (testified by XPS). Our studies revealed that ZT* are characterized by larger electroactive surface area and more structure defects compared to ZT, where surface area and microstrains resulting from surface hydroxylation open cavities in zirconia structure.     

Optimizing Radiographic Sensitivity in the In-Service Testing of Pipes

Russian Journal of Nondestructive Testing - In the in-service radiographic testing of water-filled pipes, the interaction of radiation with water diminishes the quality of the transmitted radiation...