A review of carbon dioxide capture and utilization by membrane integrated microalgal cultivation processes

The capture of carbon dioxide (CO₂) from the air for microalgal cultivation has received increasing interest since it allows advantages that do not only reduce the amount of CO₂ already added to the air, but it is also more economical due to the accessibility of air, there are no regeneration requirements and it is a safe method that can help enhance microalgal growth. In order to capture CO₂ from the air, it is necessary to deal with CO₂ emissions from all sources in an atmosphere. Interestingly, the capture unit and microalgal culture can be located at any favorable site. Although a number of photobioreactors have been proposed with a CO₂ distribution system, the consequence of CO₂ losses is still being ignored. Thus, capturing CO₂ from the air via an integrated separation process in a photobioreactor is required for microalgal cultivation. Among the four available separation technologies, the membrane separation process would offer a safe, reliable and low cost method for CO₂ capture. Thus, this method of separation can be considered as a key factor in accelerating the development of a CO₂ enrichment process from the air for microalgal cultivation.     

In Vitro Degradation and Conversion of Melt‐Derived Microfibrous Borate (13‐93B3) Bioactive Glass Doped with Metal Ions

Microfibrous melt‐derived bioactive glasses based on a borate 13‐93B3 composition are showing a considerable capacity to heal chronic soft tissue wounds in humans and animals. Metal ion dopants in borate 13‐93B3 microfibers can be beneficial for healing soft tissue wounds and bone defects but their role and delivery have received little attention. In this study, the effect of selected metal ion dopants on the degradation and conversion of 13‐93B3 microfibers in simulated body fluid at 37°C was investigated. Two groups of microfibers (diameter = 0.2–3 μm) composed of 13‐93B3 glass (composition 6 Na₂O, 12 K₂O, 5 MgO, 20 CaO, 4 P₂O₅, 53 B₂O₃, wt%) doped with (1) CuO (0.4 wt%) + ZnO (1.0 wt%); and (2) CuO (0.4 wt%) + ZnO (1.0 wt%) + Fe₂O₃ (0.4 wt%) + SrO (2.0 wt%) were studied. The metal ion dopants had little effect on the degradation of the parent 13‐93B3 glass microfibers and their conversion to an amorphous calcium phosphate (ACP) product but they inhibited the crystallization of the ACP to HA. The release of Cu and Sr ions from the glass into the medium was considerably higher than Zn and Fe ions which were retained mainly in the ACP or HA product. These results are pertinent to the design of borate bioactive glasses for optimum healing of soft tissue wounds and bone.     

Hydrothermal deposition and characterization of heteroepitaxial BaTiO3 films on SrTiO3 and LaAlO3 single crystals

Heteroepitaxial BaTiO₃ thin films were deposited in an aqueous solution under hydrothermal conditions on single crystal substrates of (100) SrTiO₃ and (012) LaAlO₃. The reactants consisted of fine TiO₂ particles in a strongly alkaline solution of Ba(OH)₂ at a temperature of 150°C. The growth of the films was studied by atomic force microscopy, high resolution scanning electron microscopy, and X-ray diffraction. The formation of the films occurred by nucleation of {001} faceted islands followed by three-dimensional growth of the islands to cover the substrate. Repeated hydrothermal treatment improved the film thickness and the surface coverage of the substrate at the expense of increased surface roughness. X-ray diffraction coupled with pole figure analysis showed that the films had the same in-plane and out-of-plane orientation as the substrate.     

Interfacial shear stress in SiC fibre-reinforced cordierite

An analytical model based on a consistent shear-lag theory was developed to predict the interfacial shear stress in single fibre pull-out tests. The calculations show that the stress is highly dependent on the specimen thickness and the method of testing. Data for the debond stress and the interfacial shear stress were measured for single SiC fibres embedded in a magnesium aluminium silicate (cordierite) matrix. The effect of fibre embedded length, processing schedule, and matrix toughening were investigated. For a fixed sample support configuration during testing, good agreement was obtained between the model predictions and experimental data.     

Thermolysis of mono-, di- and tri-benzylamines,IV

Thermolysis of mono-, di- or tri-benzylamine for some days in the absence of promoters gave the same products: ammonia, toluene, dibenzyl, stilbene and benzaldehyde. Thermolysis of dibenzylamine in isoquinoline as a solvent gave 1-benzyl-isoquinoline together with the normal pyrolysis products. When naphthalene and 2-naphthol are used as solvents, benzylation of the solvent nuclei was observed to give 1- and 2-benzylnaphthalenes and 1-benzyl-2-naphthol respectively. In conclusion, thermolysis of tri-, di- or mono-benzylamines proceeds through a free radical mechanism with successive conversions of the tertiary, through secondary to primary alkylamines resulting in the same pyrolysis products.     

Factors Controlling the Sintering of Ceramic Particulate Composites: II, Coated Inclusion Particles

Composite powders were synthesized by coating coarse ZrO₂ inclusion particles with a cladding of fine-grained, crystalline ZnO powder using a chemical precipitation technique. Three different inclusion sizes (1, 3, and 14 μm) were used by selecting the size of the starting ZrO₂ powder, and the volume fraction of the inclusions was controlled by the amount of ZnO precipitated. The powders were compacted by uniaxial pressing in a die and then sintered at a constant heating rate of 4°C/min to 1500°C. The sintering kinetics were almost independent of the inclusion volume fraction, and of the inclusion size, for inclusion contents up to ∼40 vol%. Furthermore, composites containing up to ∼40 vol% inclusions were sintered to almost full density under the same conditions used for the unreinforced matrix. This is considerably better than the densities obtained for conventionally mixed powders, where a modest inclusion content (< ∼ 10 vol%) has been observed to cause a severe reduction in the sintered density of the composite matrix. The kinetic data and microstructural observations are a further indication that the main factors which oppose the free sintering of ceramic particulate composites are processing-related; these factors are (i) inclusion-inclusion interactions which constrain the matrix and (ii) the packing of the matrix phase in regions immediately surrounding the inclusions.     

Pore size distribution during compaction and early stage sintering of silicon nitride

The effect of a number of compaction parameters on the pore size distribution in silicon nitride powder compacts has been investigated by mercury porosimetry. The powder was compacted in a uniaxial die and the parameters of interest included uniaxial load, loading rate, polymer additives and stress relaxation. The use of a low-viscosity polymer solution as a lubricant, the allowance of stress relaxation following loading and heat treatment above the glass transition temperature of the polymer lead to a more uniform pore size distribution in the green samples. The more uniform green samples, in turn, showed a more uniform pore size distribution after initial stage sintering. The potential of the present techniques for improving the microstructural uniformity in ceramic bodies is discussed.     

Optimal Sparse Autoencoder Based Sleep Stage Classification Using Biomedical Signals

The recently developed machine learning (ML) models have the ability to obtain high detection rate using biomedical signals. Therefore, this article develops an Optimal Sparse Autoencoder based Sleep Stage Classification Model on Electroencephalography (EEG) Biomedical Signals, named OSAE-SSCEEG technique. The major intention of the OSAE-SSCEEG technique is to find the sleep stage disorders using the EEG biomedical signals. The OSAE-SSCEEG technique primarily undergoes preprocessing using min-max data normalization approach. Moreover, the classification of sleep stages takes place using the Sparse Autoencoder with Smoothed Regularization (SAE-SR) with softmax (SM) approach. Finally, the parameter optimization of the SAE-SR technique is carried out by the use of Coyote Optimization Algorithm (COA) and it leads to boosted classification efficiency. In order to ensure the enhanced performance of the OSAE-SSCEEG technique, a wide ranging simulation analysis is performed and the obtained results demonstrate the betterment of the OSAE-SSCEEG technique over the recent methods.     

Cat Swarm with Fuzzy Cognitive Maps for Automated Soil Classification

Accurate soil prediction is a vital parameter involved to decide appropriate crop, which is commonly carried out by the farmers. Designing an automated soil prediction tool helps to considerably improve the efficacy of the farmers. At the same time, fuzzy logic (FL) approaches can be used for the design of predictive models, particularly, Fuzzy Cognitive Maps (FCMs) have involved the concept of uncertainty representation and cognitive mapping. In other words, the FCM is an integration of the recurrent neural network (RNN) and FL involved in the knowledge engineering phase. In this aspect, this paper introduces effective fuzzy cognitive maps with cat swarm optimization for automated soil classification (FCMCSO-ASC) technique. The goal of the FCMCSO-ASC technique is to identify and categorize seven different types of soil. To accomplish this, the FCMCSO-ASC technique incorporates local diagonal extrema pattern (LDEP) as a feature extractor for producing a collection of feature vectors. In addition, the FCMCSO model is applied for soil classification and the weight values of the FCM model are optimally adjusted by the use of CSO algorithm. For examining the enhanced soil classification outcomes of the FCMCSO-ASC technique, a series of simulations were carried out on benchmark dataset and the experimental outcomes reported the enhanced performance of the FCMCSO-ASC technique over the recent techniques with maximum accuracy of 96.84%.