Electro-spray of high viscous liquids for producing mono-sized spherical alginate beads

Alginate beads, often used for controlled release of enzymes and drugs, are usually produced by spraying sodium alginate liquid into a gelling agent using mechanical vibration nozzle or air jet. In this work an alternative method of electro-spray was employed to form droplets with desired size from a highly viscous sodium alginate solution using constant DC voltage. The droplets were then cured in a calcium chloride solution. The main objective was to produce mono-sized beads from such a highly viscous and non-Newtonian liquid (1000-5000 mPa s). The effects of nozzle diameter, flow rate and concentration of liquid on the size of the beads were investigated. Among the parameters studied, voltage had a pronounced effect on the size of beads as compared to flow rate zzle diameter and concentration of alginate liquid. The size of beads was reduced to a minimum value with increasing the voltage in the range of 0-10 kV. At the early stages of voltage increase (I.e. Up to about 4 kV), the rate of size reduction was relatively low, while the dripping mode dominated. However, in the middle part of the range of applied voltage, where the rate of size reduction was high (I.e. About 4-7 kV), an unstable transition occurred between dripping and jetting. At the end part of the range (I.e. 7-10 kV) jet mode of spray was observed. Increasing the height of fall of the droplets was found to improve the sphericity of the beads, because of the increased time of flight for the droplets. This was especially identifiable at higher concentrations of the alginate liquid (I.e. 3 w/v%)     

Acetic acid effects on enhancement of growth rate and reduction of amorphous carbon deposition on CNT arrays along a growth window in a floating catalyst reactor

The mm-long carbon nanotube (CNT) arrays were grown in a floating catalyst reactor, using xylene-ferrocene and a small amount of acetic acid as the feed. The CNT arrays deposited on a quartz substrate at several positions along the reactor were extensively characterized using Raman spectroscopy, scanning electron microscopy, X-ray diffraction, high-resolution transmission electron microscopy, and optical microscopy. Various characterization methods consistently reveal that the acetic acid additive to the feed alleviates deposition of amorphous carbon layer, which gradually thickens CNTs along the reactor. The acetic acid also resulted in a higher growth rate along the so-called growth window, where CNT arrays are deposited on the quartz substrate. High-performance liquid chromatography of extracted byproducts (PAHs) confirmed the presence of some polycyclic aromatic hydrocarbons. The solid weight of PAHs decreased upon addition of ferrocene as the catalyst precursor, as well as of acetic acid to xylene feed. The results suggest that primary light products of xylene pyrolysis can be competitive reactants for both catalytic and subsequent pyrolytic reactions. They may also be more efficient feeds for CNT growth than xylene itself.     

Cyanoacetanilides Intermediates in Heterocyclic Synthesis. Part 5: Preparation of Hitherto Unknown 5‐Aminopyrazole and Pyrazolo[1,5‐a]pyrimidine Derivatives Containing Sulfamoyl Moiety

Novel 5‐aminopyrazole and pyrazolo[1,5‐a]pyrimidine derivatives have been synthesized from the readily accessible cyanoacetanilide derivative ( 2 ).     

Numerical solution of the nonlinear Schrodinger equation by feedforward neural networks

We present a method to solve boundary value problems using artificial neural networks (ANN). A trial solution of the differential equation is written as a feed-forward neural network containing adjustable parameters (the weights and biases). From the differential equation and its boundary conditions we prepare the energy function which is used in the back-propagation method with momentum term to update the network parameters. We improved energy function of ANN which is derived from Schrodinger equation and the boundary conditions. With this improvement of energy function we can use unsupervised training method in the ANN for solving the equation. Unsupervised training aims to minimize a non-negative energy function. We used the ANN method to solve Schrodinger equation for few quantum systems. Eigenfunctions and energy eigenvalues are calculated. Our numerical results are in agreement with their corresponding analytical solution and show the efficiency of ANN method for solving eigenvalue problems.     

Spin-valley Hall conductivity of doped ferromagnetic silicene under strain

The spin-valley Hall conductivity(SHC-VHC) of two-dimensional material ferromagnetic graphene's silicon analog,silicene, is investigated in the presence of strain within the Kubo formalism in the context of the Kane–Mele Hamiltonian.The Dirac cone approximation has been used to investigate the dynamics of carriers under the strain along the armchair(AC) direction. In particular, we study the effect of external static electric field on these conductivities under the strain.In the presence of the strain, the carriers have a larger effective mass and the transport decreases. Our findings show that SHC changes with respect to the direction of the applied electric field symmetrically while VHC increases independently.Furthermore, the reflection symmetry of the structure has been broken with the electric field and a phase transition occurs to topological insulator for strained ferromagnetic silicene. A critical strain is found in the presence of the electric field around 45%. SHC(VHC) decreases(increases) for strains smaller than this value symmetrically while it increases(decreases) for strains larger than one.     

Designing a multi-scroll chaotic system by operating Logistic map with fractal process

Recently, chaotic systems have been widely investigated in several engineering applications. This paper presents a new chaotic system based on Julia’s fractal process, chaotic attractors and Logistic map in a complex set. Complex dynamic characteristics were analyzed, such as equilibrium points, bifurcation, Lyapunov exponents and chaotic behavior of the proposed chaotic system. As we know, one positive Lyapunov exponent proved the chaotic state. Numerical simulation shows a plethora of complex dynamic behaviors, which coexist with an antagonist form mixed of bifurcation and attractor. Then, we introduce an algorithm for image encryption based on chaotic system. The algorithm consists of two main stages: confusion and diffusion. Experimental results have proved that the proposed maps used are more complicated and they have a key space sufficiently large. The proposed image encryption algorithm is compared to other recent image encryption schemes by using different security analysis factors including differential attacks analysis, statistical tests, key space analysis, information entropy test and running time. The results demonstrated that the proposed image encryption scheme has better results in the level of security and speed.     

A Conditional Moment Closure Study of Chemical Reaction Source Terms in SCCI Combustion

The objective of this study is to evaluate conditional moment closure (CMC) approaches to model chemical reaction rates in compositionally stratified, autoigniting mixtures, in thermochemical conditions relevant to stratified charge compression ignition (SCCI) engines. First-order closure, second-order closure and double conditioning are evaluated and contrasted as options in comparison to a series of direct numerical simulations (DNSs). The two-dimensional (2D) DNS cases simulate ignitions in SCCI-like thermochemical conditions with compositionally stratified n-heptane/air mixtures in a constant volume. The cases feature two different levels of stratification with three mean temperatures in the negative-temperature coefficient (NTC) regime of ignition delay times. The first-order closure approach for reaction rates is first assessed using hybrid DNS-CMC a posteriori tests when implemented in an open source computational fluid dynamics (CFD) package known as OpenFOAM\(^{{\circledR }}\). The hybrid DNS-CMC a posteriori tests are not a full CMC but a DNS-CMC hybrid in that they compute the scalar and velocity fields at the DNS resolution, thus isolating the first-order reaction rate closure model as the main source of modelling error (as opposed to turbulence model, scalar probability density function model, and scalar dissipation rate model). The hybrid DNS-CMC a posteriori test reveals an excellent agreement between the model and DNS for the cases with low levels of stratification, whereas deviations from the DNS are observed in cases which exhibit high level of stratifications. The a priori analysis reveals that the reason for disagreement is failure of the first-order closure hypothesis in the model due to the high level of conditional fluctuations. Second-order and double conditioning approaches are then evaluated in a priori tests to determine the most promising path forwards in addressing higher levels of stratification. The a priori tests use the DNS data to compute the model terms, thus directly evaluating the model assumptions. It is shown that in the cases with a high level of stratification, even the second-order estimation of the reaction rate source term cannot provide a reasonably accurate closure. Double conditioning using mixture-fraction and sensible enthalpy, however, provides an accurate first-order closure to the reaction rate source term.     

Sensitivity analysis of the equal angle divider mechanism kinematics with the synthesis of the joint gap tolerances

Tolerance analysis of mechanical components and assemblies is a key element in the industry for improving product quality and reducing overall cost. This paper is an attempt to propose a methodology to formulate and compute the kinematic assembly variations with respect to the critical dimensions (joint clearances) by calculating the homogeneous matrix of loops with considering the transforming and rotation matrix, the tolerance sensitivities, the geometrical responses to assembly variations, and the tolerance sensitivity of mechanism for clearance in the joints in different motion phases. The analysis is performed by the systematic methodology which is extended for kinematic sensitivity and positional error analysis with published results.