Evolving an Accurate Decision Tree-Based Model for Predicting Carbon Dioxide Solubility in Polymers

Solubility is one of the most indispensable physicochemical properties determining the compatibility of components of a blending system. Research has been focused on the solubility of carbon dioxide in polymers as a significant application of green chemistry. To replace costly and time-consuming experiments, a novel solubility prediction model based on a decision tree, called the stochastic gradient boosting algorithm, was proposed to predict CO₂ solubility in 13 different polymers, based on 515 published experimental data lines. The results indicate that the proposed ensemble model is an effective method for predicting the CO₂ solubility in various polymers, with highly satisfactory performance and high efficiency. It produces more accurate outputs than other methods such as machine learning schemes and an equation of state approach.     

An array-compensated spherical reflector antenna for a very large number of scanned beams

There are many stringent demands imposed on the applications of spaceborne antenna systems. One of the most challenging demands is the generation of multiple beams with the ability to scan a very large number of beamwidths. Since the parabolic reflectors have limitations in this application, a 35-m spherical reflector antenna is proposed for a geostationary radar antenna at Ka-band (35.6 GHz) due to its inherent capability of scanning the beams to very large number of beamwidths. The utility of using planar array feeds for correcting spherical phase aberrations is investigated to overcome the performance degradation effects. Two different methodologies are developed for the array excitation coefficients determination based on phase conjugate matching and the results are compared. Using the compensating feed array, the radiation characteristics of the compensated spherical reflector are simulated for no scan and large scan cases and the results are compared with the uncompensated case to show performance improvement. In order to demonstrate the technological readiness of the concept a 1.5-m breadboard model is designed to be built for experimental measurements. Some important mechanical design tolerances and realistic array feed topologies are investigated. The antenna concept developed in this paper is advocated to be used in the next generation of geostationary satellite antenna systems for remote sensing radar applications.     

Weekly storage of coolness in heavy brick and adobe walls

Weekly storage of coolness in heavy walls (walls with large thermal inertia or large characteristic time constants or low Fourier numbers) was investigated numerically by considering one-dimensional heat conduction through the walls. The study consisted of first analyzing the heat flow through a single wall and considering various boundary conditions on the inside. The boundary conditions were: constant inside air tempeture throughout the day, variable inside air temperature on a 24-hour cycle, and variable inside air temperature on a 48-hour cycle. Next, the heat flow through walls was studied through a thermal network analysis of a simple building. In this case it was assumed that the ambient air temperature (following a periodic distribution) was increased suddenly and followed this new distribution for many days thereafter.It was concluded that walls with high thermal inertia or time constant can store coolness for several days. The larger the time constant of the wall (for example adobe as compared with brick) the longer it takes for the wall temperature to reach a steady periodic distribution after the change has occurred. However, because of low thermal conductivity of adobe, the retrieval of the stored coolness in these walls is slow, and the mean daily temperature of the room air in the adobe building does not change appreciably beyond seven days after the change. Increase of the wall thickness beyond 50 cm does not improve the thermal performance of the building significantly.     

Hot-nanoparticle-mediated fusion of selected cells

Complete fusion of two selected cells allows for the creation of novel hybrid cells with inherited genetic properties from both original cells.Alternatively,via fusion of a selected cell with a selected vesicle,chemicals or genes can be directly delivered into the cell of interest,to control cellular reactions or gene expression.Here,we demonstrate how to perform an optically controlled fusion of two selected cells or of one cell and one vesicle.Fusion is mediated by laser irradiating plasmonic gold nanoparticles optically trapped between two cells (or a vesicle and a cell) of interest.This hot-particle-mediated fusion causes total mixing of the two cytoplasms and the two cell membranes resulting in formation of a new hybrid cell with an intact cell membrane and enzymatic activity following fusion.Similarly,fusion between a vesicle and a cell results in delivery of the vesicle cargo to the cytoplasm,and after fusion,the cell shows signs of viability.The method is an implementation of targeted drug delivery at the single-cell level and has a great potential for cellular control and design.     

Prediction of carbon dioxide separation from gas mixtures in petroleum industries using the Levenberg–Marquardt algorithm

In this study, two mathematical models for hydrate formation process to separate carbon dioxide by a combination of two different kinds of organic and surfactant promoters are presented. Promoters such as sodium dodecyl sulfate, sodium dodecyl benzene sulfonate, and dodecyl trimethyl ammonium chloride as surfactant promoters; also, tetrahydrofuran, cyclopentane, 1,3-dioxolane, and 2-methyl tetrahydrofuran as organic promoters have been used in recent years. The results showed that a combination of 3000 ppm of surfactant promoters and 4 wt% organic promoters had the highest separation rate of carbon dioxide and; consequently, the investigated models were based on this optimum condition. As a matter of fact, by using these simulations the hydrate formation behavior was predicted with high accuracy; moreover, conducting consuming experiments is not essential anymore. To sum up, in the present research both Vandermonde matrix model and Levenberg-Marquardt algorithm were applied to predict the hydrate formation behavior; in addition, their results were precisely considered and validated with experimental data.     

The Effect of Ti on Mechanical Properties of Extruded In-Situ Al-15 pct Mg2Si Composite

This work was carried out to investigate the effect of different Ti concentrations as a modifying agent on the microstructure and tensile properties of an in-situ Al-15 pctMg₂Si composite. Cast, modified, and homogenized small ingots were extruded at 753 K (480 °C) at the extrusion ratio of 18:1 and ram speed of 1 mm/s. Various techniques including metallography, tensile testing, and scanning electron microscopy were used to characterize the mechanical behavior, microstructural observations, and fracture mechanisms of this composite. The results showed that 0.5 pctTi addition and homogenizing treatment were highly effective in modifying Mg₂Si particles. The results also exhibited that the addition of Ti up to 0.5 pct increases both ultimate tensile strength (UTS) and tensile elongation values. The highest UTS and elongation values were found to be 245 MPa and 9.5 pct for homogenized and extruded Al-15 pctMg₂Si-0.5 pctTi composite, respectively. Fracture surface examinations revealed a transition from brittle fracture mode in the as-cast composite to ductile fracture in homogenized and extruded specimens. This can be attributed to the changes in size and morphology of Mg₂Si intermetallic and porosity content.     

Asphaltene precipitation and deposition in oil reservoirs – Technical aspects,experimental and hybrid neural network predictive tools

Precipitation of asphaltene is considered as an undesired process during oil production via natural depletion and gas injection as it blocks the pore space and reduces the oil flow rate. In addition, it lessens the efficiency of the gas injection into oil reservoirs. This paper presents static and dynamic experiments conducted to investigate the effects of temperature, pressure, pressure drop, dilution ratio, and mixture compositions on asphaltene precipitation and deposition. Important technical aspects of asphaltene precipitation such as equation of state, analysis tools, and predictive methods are also discussed. Different methodologies to analyze asphaltene precipitation are reviewed, as well. Artificial neural networks (ANNs) joined with imperialist competitive algorithm (ICA) and particle swarm optimization (PSO) are employed to approximate asphaltene precipitation and deposition with and without CO₂ injection. The connectionist model is built based on experimental data covering wide ranges of process and thermodynamic conditions. A good match was obtained between the real data and the model predictions. Temperature and pressure drop have the highest influence on asphaltene deposition during dynamic tests. ICA-ANN attains more reliable outputs compared with PSO-ANN, the conventional ANN, and scaling models. In addition, high pressure microscopy (HPM) technique leads to more accurate results compared with quantitative methods when studying asphaltene precipitation.     

Application of dielectric barrier discharge (DBD) plasma packed with glass and ceramic pellets for SO2 removal at ambient temperature: optimization and modeling using response surface methodology

Air pollution is a major health problem in developing countries and has adverse effects on human health and the environment. Non-thermal plasma is an effective air pollution treatment technology. In this research, the performance of a dielectric barrier discharge (DBD) plasma reactor packed with glass and ceramic pellets was evaluated in the removal of SO₂ as a major air pollutant from air in ambient temperature. The response surface methodology was used to evaluate the effect of three key parameters (concentration of gas, gas flow rate, and voltage) as well as their simultaneous effects and interactions on the SO₂ removal process. Reduced cubic models were derived to predict the SO₂ removal efficiency (RE) and energy yield (EY). Analysis of variance results showed that the packed-bed reactors (PBRs) studied were more energy efficient and had a high SO₂ RE which was at least four times more than that of the non-packed reactor. Moreover, the results showed that the performance of ceramic pellets was better than that of glass pellets in PBRs. This may be due to the porous surface of ceramic pellets which allows the formation of microdischarges in the fine cavities of a porous surface when placed in a plasma discharge zone. The maximum SO₂ RE and EY were obtained at 94% and 0.81 g kWh⁻¹, respectively under the optimal conditions of a concentration of gas of 750 ppm, a gas flow rate of 2 l min⁻¹, and a voltage of 18 kV, which were achieved by the DBD plasma packed with ceramic pellets. Finally, the results of the model's predictions and the experiments showed good agreement.     

From Feather Waste to Valuable Nanoparticles

Feather is a waste product generated in large quantities from industrial poultry processing. Recycling of this renewable source of biopolymers has been the objective of many researches due to its high protein content, biodegradability, and biocompatibility. This study investigates the feasibility of producing nanoparticles from feather waste by enzymatic hydrolysis, followed by ultrasonic treatment. The effects of enzyme concentration, hydrolysis time and substrate concentration on particles size were evaluated to optimize the best condition in order to attain the smallest particles by a Box-Behnken Design. The optimum hydrolysis conditions were found to be: enzyme concentration: 3.6%, substrate concentration: 5 g/l and hydrolysis time: 243 h. Scanning electron micrographs indicated fiber fibrillation and degradation as it was progressively converted into particles form. The results of particle size analysis indicated the positive effect of sonication on reducing particles size. Fourier transform infrared spectra showed no remarkable changes in the chemical composition of treated samples. Moreover, crystallinity and thermal stability of feather nanoparticles enhanced upon enzymatic hydrolysis and ultrasonic treatment.     

The effects of post annealing on the mechanical properties, microstructure and texture evolutions of pure copper deformed by twist extrusion process

X-ray diffraction peak broadening analysis showed that performing a proper heat treatment between the twist extrusion passes of commercially pure copper decreased the coherent domain size and increased the microstrain. Moreover, SEM micrographs illustrated that annealed material contained new formed grains that could not grow due to lack of sufficient time. Under such circumstances, the ultimate strength was elevated about 45 MPa. The deformed material showed texture of simple shear deformation, changing by applying the post annealing.