Estimation of the minimum machining performance in the abrasive waterjet machining using integrated ANN-SA

In this study, Artificial Neural Network (ANN) and Simulated Annealing (SA) techniques were integrated labeled as integrated ANN-SA to estimate optimal process parameters in abrasive waterjet (AWJ) machining operation. The considered process parameters include traverse speed, waterjet pressure, standoff distance, abrasive grit size and abrasive flow rate. The quality of the cutting of machined-material is assessed by looking to the roughness average value (R_a). The optimal values of the process parameters are targeted for giving a minimum value of R_a. It was evidence that integrated ANN-SA is capable of giving much lower value of R_a at the recommended optimal process parameters compared to the result of experimental and ANN single-based modeling. The number of iterations for the optimal solutions is also decreased compared to the result of SA single-based optimization.     

Performance analysis of three advanced controllers for polymerization batch reactor: An experimental investigation

The performances of three advanced non-linear controllers are analyzed for the optimal set point tracking of styrene free radical polymerization (FRP) in batch reactors. The three controllers are the artificial neural network-based MPC (NN-MPC), the artificial fuzzy logic controller (FLC) as well as the generic model controller (GMC). A recently developed hybrid model (Hosen et al., 2011a. Asia-Pac. J. Chem. Eng. 6(2), 274) is utilized in the control study to design and tune the proposed controllers. The optimal minimum temperature profiles are determined using the Hamiltonian maximum principle. Different types of disturbances are introduced and applied to examine the stability of controller performance. The experimental studies revealed that the performance of the NN-MPC is superior to that of FLC and GMC.     

Dielectric Constant,Metallization Criterion and Optical Properties of CuO Doped TeO2–B2O3 Glasses

Journal of Inorganic and Organometallic Polymers and Materials - Copper oxide doped TeO2–B2O3 glass system with empirical formula;...     

Hybrid neural network for prediction of CO<Subscript>2</Subscript> solubility in monoethanolamine and diethanolamine solutions

The solubility of CO₂ in single monoethanolamine (MEA) and diethanolamine (DEA) solutions was predicted by a model developed based on the Kent-Eisenberg model in combination with a neural network. The combination forms a hybrid neural network (HNN) model. Activation functions used in this work were purelin, logsig and tansig. After training, testing and validation utilizing different numbers of hidden nodes, it was found that a neural network with a 3-15-1 configuration provided the best model to predict the deviation value of the loading input. The accuracy of data predicted by the HNN model was determined over a wide range of temperatures (0 to 120 °C), equilibrium CO₂ partial pressures (0.01 to 6,895 kPa) and solution concentrations (0.5 to 5.0M). The HNN model could be used to accurately predict CO₂ solubility in alkanolamine solutions since the predicted CO₂ loading values from the model were in good agreement with experimental data.     

Development of a novel nanocomposite consisting of 3-(4-methoxyphenyl)propionic acid and magnesium layered hydroxide for controlled-release formulation

ABSTRACT

Magnesium layered hydroxide (MLH) intercalated with anionic 3-(4-methoxyphenyl)propionic acid (MPP) was synthesised by a direct reaction method using magnesium oxide and MPP as precursors. A further coating of chitosan was applied on the external surface of MLH–MPP nanocomposite to form a new material, named MLH–MPP/chitosan nanocomposite. The XRD pattern showed an intense and sharp peak at basal spacing 18.9 Å, proving that MPP anions were successfully intercalated into the interlayer gallery of MLH in a monolayer arrangement. The XRD pattern of the MLH–MPP/chitosan nanocomposite shows similar peaks with the MLH–MPP nanocomposite. The result was also supported by FTIR spectra and elemental analysis. TGA/DTG spectra showed that the thermal stabilities of the guest anion in the both nanocomposites were markedly enhanced. A controlled-release study of the MPP ion from the MLH–MPP/chitosan nanocomposite showed a slower release compared to MLH–MPP nanocomposite with an initial rapid release and slow release thereafter. Meanwhile, the release behaviours of MPP ions from both nanocomposites were governed by pseudo-second order kinetics. This result highlights the potential of the nanocomposite as an encapsulated material for the controlled-release formulation of MPP anions.     

Optimizing the processing conditions of sodium potassium niobate thin films prepared by sol-gel spin coating technique

In the present study, potassium sodium niobate (KNN) thin films were synthesized by means of sol-gel spin coating method. Along with the synthesis, the effects of annealing temperature and various number of coating layers on both the structural and electrical properties were looked into. The results of the study revealed that the annealing temperature had a great impact on the properties of KNN. In addition, the XRD diffractograms and texture coefficient of the synthesized films confirmed that a highly oriented orthorhombic perovskite structure was obtained at 650 °C, whereas at a relatively higher temperature (700 °C), a spurious phase of K₄Nb₆O₁₇ was evolved. In addition, the growth of KNN at 650 °C exhibited a reasonable resistivity value for piezoelectric applications. Looking into the results, it was discovered that the KNN thin films also found to be dependent on a number of coating layers. Field emission scanning electron microscopy (FESEM) showed that KNN with five coating layers was highly crystalline, cracks-free, and had significantly more homogenous surface morphology and the size of grains being uniform, the resistivity of KNN thin films improved with the increasing number of coating layers i.e., up to five.     

Dynamic modeling of gas phase propylene homopolymerization in fluidized bed reactors

A new model with comprehensive kinetics for propylene homopolymerization in fluidized bed reactors was developed to investigate the effect of mixing, operating conditions, kinetic and hydrodynamic parameters on the reactor performance as well as polymer properties. Presence of the particles in the bubbles and the excess gas in the emulsion phase was considered to improve the two-phase model, thus, considering the polymerization reaction to take place in both the bubble and emulsion phases. It was shown that in the practical range of superficial gas velocity and catalyst feed rate, the ratio of produced polymer in the bubble phase to the total production rate is roughly between 10% and 13%, which is a substantial amount and cannot be ignored. Simulation studies were carried out to compare the results of the improved two-phase, conventional well-mixed and constant bubble size models. The improved two-phase and well mixed models predicted a narrower and safer window at the same running conditions compared with the constant bubble size model. The improved two-phase model showed close dynamic behavior to the conventional models at the beginning of polymerization, but starts to diverge with the evolution of time.     

Microbial-Catalyzed Biotransformation of Multifunctional Triterpenoids Derived from Phytonutrients

Microbial-catalyzed biotransformations have considerable potential for the generation of an enormous variety of structurally diversified organic compounds, especially natural products with complex structures like triterpenoids. They offer efficient and economical ways to produce semi-synthetic analogues and novel lead molecules. Microorganisms such as bacteria and fungi could catalyze chemo-, regio- and stereospecific hydroxylations of diverse triterpenoid substrates that are extremely difficult to produce by chemical routes. During recent years, considerable research has been performed on the microbial transformation of bioactive triterpenoids, in order to obtain biologically active molecules with diverse structures features. This article reviews the microbial modifications of tetranortriterpenoids, tetracyclic triterpenoids and pentacyclic triterpenoids.     

The formation of WO3 nanorods using the surfactant-assisted hydrothermal reaction

Monoclinic tungsten oxide (WO₃) nanorods were grown using the hydrothermal method on a seeded W foil. The seed layer was formed by thermal oxidation of W foil at 400°C for 30 min. Cetyltrimethylammonium bromide (CTAB) or hexamethylamine (HMT) was used in the reactive hydrothermal bath, along with sodium tungstate dihydrate (Na₂WO₄.2H₂O) and hydrochloric acid (HCl). The concentration of CTAB was varied from 0.01 M to 0.07 M and the concentration of HMT was varied from 0.01 M and 0.05 M. The result showed that CTAB-assisted hydrothermal reaction produced WO₃ nanorods with 4–7 nm diameter, and provided that CTAB concentration was less than 0.07 M. WO₃ nanorods could not be obtained when CTAB concentration was 0.07 M. Columnar structured WO₃ was produced with the presence of HMT in the hydrothermal bath. This was due to decomposition of HMT to form hydroxyl ions (OH^?) that inhibited the growth of nanorods. Cyclic voltammetry (CV) analysis showed better electrochromic property of WO₃ nanorods compared to columnar structured WO₃.