Tools to Simulate Distributive Mixing in Twin‐Screw Extruders

The application of the mapping method in finite element modeling is extended to quantitatively compare mixing in different twin‐screw extruder layouts. The mapping method provides volumetric quantities, which are crucial for the analysis and optimization of mixing based on the tracking of particles in the velocity field. A new approach to the mapping method is developed to analyze mixing in complex, dynamic open geometries. Several screw configurations and different types of conveying screws are compared, changing the pitch and gap widths. The volume‐weighted intensity of segregation is used as a mixing measure.

     

Insights in hydrodynamics of bubbling fluidized beds at elevated pressure by DEM–CFD approach

A numerical simulation was conducted to study the effect of pressure on bubble dynamics in a gas–solid fluidized bed. The gas flow was modeled using the continuum theory and the solid phase, by the discrete element method (DEM). To validate the simulation results, calculated local pressure fluctuations were compared with corresponding experimental data of 1-mm polyethylene particles. It was shown that the model successfully predicts the hydrodynamic features of the fluidized bed as observed in the experiments. Influence of pressure on bubble rise characteristics such as bubble rise path, bubble stability, average bubbles diameter and bubble velocity through the bed was investigated. The simulation results are in conformity with current hydrodynamic theories and concepts for fluidized beds at high pressures. The results show further that elevated pressure reduces bubble growth, velocity and stability and enhances bubble gyration through the bed, leading to change in bed flow structure.     

Antimicrobial Ionic Liquid-Based Materials for Biomedical Applications

Excessive and unwarranted administration of antibiotics has invigorated the evolution of multidrug-resistant microbes. There is, therefore, an urgent need for advanced active compounds. Ionic liquids with short-lived ion-pair structures are highly tunable and have diverse applications. Apart from their unique physicochemical features, the newly discovered biological activities of ionic liquids have fascinated biochemists, microbiologists, and medical scientists. In particular, their antimicrobial properties have opened new vistas in overcoming the current challenges associated with combating antibiotic-resistant pathogens. Discussions regarding ionic liquid derivatives in monomeric and polymeric forms with antimicrobial activities are presented here. The antimicrobial mechanism of ionic liquids and parameters that affect their antimicrobial activities, such as chain length, cation/anion type, cation density, and polymerization, are considered. The potential applications of ionic liquids in the biomedical arena, including regenerative medicine, biosensing, and drug/biomolecule delivery, are presented to stimulate the scientific community to further improve the antimicrobial efficacy of ionic liquids.     

Metal-silicon reaction rates—the effects of capping

Evidence is presented showing that the presence of the commonly used anti-reflection coating material Ta₂O₅ on the free surface of contact metallization can either suppress or enhance, depending on the system, the interaction that takes place at elevated temperatures between the metallization and the underlying Si. The cap layer is shown to suppress both the generation and annihilation of vacancies at the free surface of the metal which are necessary to support metal-Si interactions. Evidence is also presented indicating that the mechanical condition of the free metal surface has a significant effect on the metal-silicon reaction rate.     

Low-Resolution Architectures for Power-Efficient Scaling of mmWave Phased Array Receivers

Journal of Signal Processing Systems - Utilizing mmWave massive MIMO frontends for base station to mobile communication promises unprecedented throughput gains in cellular networks. Power...     

A simple one-pot procedure for the direct conversion of alcohols into alkyl nitriles using TsIm

A convenient and efficient one-pot preparation of nitriles from alcohols using N-(p-toluenesulfonyl)imidazole (TsIm) is described. In this method, treatment of alcohols with a mixture of NaCN, TsIm and triethylamine in the presence of catalytic amounts of tetra-n-butylammonium iodide (TBAI) in refluxing DMF furnishes the corresponding alkyl nitriles in good yields. This methodology is highly efficient for various structurally diverse alcohols with selectivity for ROH: 1° > 2° > 3°.     

UWB body area network channel modeling: An analytical approach

The aim of this work is to develop an analytically-based approach for ultra wide band (UWB) body area network (BAN) channel modeling. In detail, the body will be modeled as multi-layered stratified cylinders of infinite length, and the Maxwell's equation will be solved for plane wave and line source excitations. Human-type tissues will be assumed in the multi-layered stratified cylindrical model. Validation of the procedure through measurement results has been provided.     

Automatic selection and fusion of color spaces for image thresholding

Automatic selection of color models has a great significance for machine vision purposes like image segmentation, object recognition, etc. Typically, selection of a proper color model is a problem that can just solve by testing the models on the target one by one. To achieve a proper color model, in this article, we propose a new method which is shaped on the basis of clustering and relation among models. The proposed method is verified experimentally for two different images (in thresholding purpose). The experimental results show that this method has a suitable power for automatic purposes.     

Semantic image classification by genetic algorithm using optimised fuzzy system based on Zernike moments

Image classification is a challenging problem of computer vision. This study reports a fuzzy system to semantic image classification. As it is a complex task, various information of digital image, including three color space components and two Zernike moments with different order, are gathered and utilized as an input of fuzzy inference system to materialize a robust rotation/lighting condition and size invariant image classifier. For better performance, all the membership functions are optimized by genetic algorithm after empirical design stage. 90.62 and 96.25 % classification rates for RGB and HSI color spaces confirm the reliability of optimized system in different image conditions given in this contribution.