Fabrication of capped gold nanoparticles by using various amino acids

The production of gold nanoparticles (GNPs) by amino acid is one of the most attractive and interesting subjects in nanobiotechnology. In this study, amino acids have been utilised as a reducing agent and also an agent for capping GNPs. The GNPs were prepared using a reduction solution containing gold cations with optimum concentration of gold salt (5?mM), and also functionalised by glutamic acid, phenylalanine and tryptophan with optimum concentration of amino acids (25?mM). The optimum condition of gold solution and amino acids were achieved by ultraviolet–visible spectroscopy. The size of nanoparticles was obtained 5–20, 10–20 and 20–30?nm, respectively, by transmission electron microscopy and dynamic light scattering techniques. The results obtained from experimental and quantum calculations confirm that amino acids have strong bond while they have anion binding. Moreover, the free carboxylic groups of capped GNPs are one of the suitable and capable beads for binding biological agents. As a result, the medical applications of amino acids and proteins can be used as a practical method due to the strong interaction of peripheral amine groups with nanoparticles.     

Hybrid Fractal-Wavelet Method for Multi-Channel EEG Signal Compression

In this paper, a hybrid method is proposed for multi-channel electroencephalograms (EEG) signal compression. This new method takes advantage of two different compression techniques: fractal and wavelet-based coding. First, an effective decorrelation is performed through the principal component analysis of different channels to efficiently compress the multi-channel EEG data. Then, the decorrelated EEG signal is decomposed using wavelet packet transform (WPT). Finally, fractal encoding is applied to the low frequency coefficients of WPT, and a modified wavelet-based coding is used for coding the remaining high frequency coefficients. This new method provides improved compression results as compared to the wavelet and fractal compression methods.     

Achieving Outstanding Mechanical Performance in Reinforced Elastomeric Composite Fibers Using Large Sheets of Graphene Oxide

A simple fiber spinning method used to fabricate elastomeric composite fibers with outstanding mechanical performance is demonstrated. By taking advantage of the large size of as‐prepared graphene oxide sheets (in the order of tens of micrometers) and their liquid crystalline behavior, elastomeric composite fibers with outstanding low strain properties have been fabricated without compromising their high strain properties. For example, the modulus and yield stress of the parent elastomer improved by 80‐ and 40‐fold, respectively, while maintaining the high extensibility of ～400% strain inherent to the parent elastomer. This outstanding mechanical performance was shown to be dependent upon the GO sheet size. Insights into how both the GO sheet size dimension and dispersion parameters influence the mechanical behavior at various applied strains are discussed.     

Minimizing torque ripple in a brushless DC motor with fuzzy logic: applied to control rod driving mechanism of MNSR

A permanent magnet BLDC(brushless direct current) motor is used to move the control rod of a miniature neutron source reactor(MNSR). The BLDC motor drive is modeled using MATLAB/SIMULINK. Two main parts of the modeling are the inverter switching and the current control. Current control with chopping used to minimize the torque ripple of the MNSR control rod drive. Fuzzy logic current control together with soft chopping control shows the best response of all the three strategies. The prototype drive mechanism has an ATmega32 controller and power MOSFET switches. The simulation results are compared with experimental drive mechanism.     

Simulation and Estimation of Vapor-Liquid Equilibrium for Asymmetric Binary Systems (CO2-Alcohols) Using Artificial Neural Network

Since it is not always possible to carry out experiments at all desired temperatures and pressures, generally thermodynamic models based on equations of state are used for estimation of vapor-liquid equilibrium. In this work, a method using artificial neural network (ANN) was designed and applied to simulate and estimate the VLE for the binary asymmetric systems containing CO₂ and Alcohols. The vapor-liquid equilibrium data of six systems include (CO₂-methanol), (CO₂-ethanol), (CO₂-1-butanol), (CO₂-2-butanol), (CO₂-1-pentanol) and (CO₂-2-pentanol) were used to developed the ANN for simulation of VLE. The results when using a developed ANN model or other methods such as SRK equations of state with LCVM, PSRK, WS, were compared with experimental data at various temperatures and pressures. Finally, it was observed that there is more qualitative and quantitative conformity between ANN model results and experimental data. Furthermore, the developed ANN model showed more accurate estimation over wide range of experimental conditions.     

A variable neighborhood binary particle swarm algorithm for cell layout problem

In this paper, a new mathematical model is proposed for inter- and intra-cell layout problem in cellular manufacturing system. A binary particle swarm optimization algorithm with a new heuristic approach for satisfying the constraints of model is implemented to solve the proposed model. Also, a variable neighborhood search is applied for finding better local optimal solutions. Some sensitivity analyses are carried out to find the best values of PSO parameters. To prove the efficiency of the proposed algorithm, various numerical examples in small, medium, and large sizes in both perfect geometric shapes and random placements are generated and solved.     

A note on spark bubble drop-on-demand droplet generation: simulation and experiment

The fluid dynamics of the spark bubble-generated droplet is studied both experimentally and numerically. The emphasis is especially on the droplet behavior after pinch-off. Commercial inkjet printers often produce satellite droplets along with parent droplets which are not desirable from the viewpoint of printing efficiency. Furthermore, standard drop-on-demand droplet generators are normally restricted to the generation of droplets with the same size as the nozzle diameter. In the spark bubble droplet generation method, a spark-generated bubble induces droplet formation through a hole in a solid surface separating the liquid and air interfaces. Immediately after ignition occurs, a bubble forms and creates pressure waves as it expands and contracts in a nonsymmetrical fashion. These pressure waves, depending on the geometries of the bubble location, plate, and hole may cause a single droplet smaller than the plate aperture to form and break up. In this article, a combined numerical and experimental study has been conducted to investigate the droplet behavior created in this manner. A high-speed camera is utilized to capture the droplet formation process. The numerical simulations have been carried out using the boundary integral spatial solution coupled with the time integration, i.e., a mixed Eulerian–Lagrangian approach. There is reasonable agreement between the simulations and experiment.     

Numerical investigation of the mechanism behind the deflagration to detonation transition in homogeneous and inhomogeneous mixtures of H2-air in an obstructed channel

The accidental release of hydrogen into enclosures can result in a flammable mixture with concentration gradients and possible deflagration-to-detonation transition (DDT). This numerical study aims to investigate the effect of obstacle spacing and mixture concentration on the DDT in a homogeneous and inhomogeneous hydrogen-air mixture. The paper focuses on the mechanisms behind the DDT in two mixtures with an average hydrogen concentration of 15% and 30%. Unlike the near-stoichiometric mixture, in the lean mixture, DDT only occurs in the inhomogeneous mixture. Depending on obstacle spacing, three different regimes of DDT were observed in the near-stoichiometric inhomogeneous mixture: i) Detonation was ignited when a strong Mach stem formed and propagated between the obstacles; ii) two explosion centers appeared when incident shock and Mach stem reflected from upper and lower obstacles, respectively; iii) Mach stem did not form but DDT occurred behind the flame front at the top of the obstacle.