Critical effect of aging condition on mesostructural ordering in mesoporous titania thin film

Here we demonstrate facile synthesis method for formation of highly ordered mesoporous cubic Im-3 m titania thin film. The mesostructural ordering is strongly dependent on the aging condition after the spin-coating. The aging condition under low temperature and low humidity is found as an optimum condition for achieving highly ordered mesostructure in titania thin films. The effects of other important synthetic parameters, such as pH of the precursor solutions and aging periods, on the mesostructural ordering are carefully examined. After the calcination, continuous mesoporous films with partially crystallized frameworks are formed without any cracks. The mesostructure of the calcined films is formed by thermal shrinkage of the original Im-3 m mesostructure. The mesostructural change in the films calcined at various temperatures are studied by using the grazing-incidence small-angle X-ray scattering (GI-SAXS). The GI-SAXS patterns show the strong shrinkage along the perpendicular direction to the substrate by increasing the calcination temperature.     

Artificial neural network approach for prediction of stress–strain curve of near b titanium alloy

In the present study, artificial neural network(ANN) approach was used to predict the stress–strain curve of near beta titanium alloy as a function of volume fractions of a and b. This approach is to develop the best possible combination or neural network(NN) to predict the stress–strain curve. In order to achieve this, three different NN architectures(feed-forward back-propagation network,cascade-forward back-propagation network, and layer recurrent network), three different transfer functions(purelin, Log-Sigmoid, and Tan-Sigmoid), number of hidden layers(1 and 2), number of neurons in the hidden layer(s),and different training algorithms were employed. ANN training modules, the load in terms of strain, and volume fraction of a are the inputs and the stress as an output.ANN system was trained using the prepared training set(a,16 % a, 40 % a, and b stress–strain curves). After training process, test data were used to check system accuracy. It is observed that feed-forward back-propagation network is the fastest, and Log-Sigmoid transfer function is giving the best results. Finally, layer recurrent NN with a single hidden layer consists of 11 neurons, and Log-Sigmoid transfer function using trainlm as training algorithm is giving good result, and average relative error is1.27 ± 1.45 %. In two hidden layers, layer recurrent NN consists of 7 neurons in each hidden layer with trainrp as the training algorithm having the transfer function of LogSigmoid which gives better results. As a result, the NN is founded successful for the prediction of stress–strain curve of near b titanium alloy.     

Halogen-free acylation of toluene over FeSBA-1 molecular sieves

Three-dimensional cage type iron substituted mesoporous silica with different iron contents (FeSBA-1) was synthesized in a highly acidic media using cetyltriethylammonium bromide and tetraethylorthosilicate as a template and a silica source, respectively. Acylation of toluene with acetic anhydride (AA) was carried out over FeSBA-1 mesoporous catalysts with different n_Si/n_Fe ratios in the temperature range 80–180 °C for a time-on-stream of 1–6 h under liquid phase conditions. The important factors affecting the conversion and the selectivity of the reaction, such as the reaction temperature, feed ratio, catalyst weight and time-on-stream were studied and the results are discussed in detail. The reaction conditions were optimized and the n_AA/n_Toluene ratio of 2 and catalyst weight of 0.1 g (3.3 wt% of total reaction mixture) were maintained for all catalytic runs. It was found that the catalytic activity is strongly influenced by the amount of tetrahedral iron in the catalysts. Among the catalysts used in the present study, FeSBA-1(36) showed a high toluene conversion and selectivity to p-methylacetophenone (p-MAP) under the optimized reaction conditions. It was also found that the selectivity for p-MAP was always higher than m-MAP and o-MAP for all the catalysts and the activity of the catalysts changes in the following order: FeSBA-1(36) > FeSBA-1(90) > FeSBA-1(120).     

Nonresonant Microwave Absorption in Bi2212 Single Crystal: Second Peak and Microwave Power Dependence

Nonresonant microwave absorption (NMA) measurements were carried out at liquid-nitrogen temperature on a high quality Bi2212 single crystal, as a function of microwave power in three mutual orientations of crystal ab plane, dc field (H_dc), and microwave magnetic field (H_w). NMA line shapes in Bi2212 crystal are complicated with a narrow peak (P₁ peak) located near zero field, followed by a much broader second peak (P₂ peak) in the particular orientations. More excitingly, we show that the P₂ peak qualitatively evolves as a function of microwave power in the orientation of H_dc ab plane, plane, and H_dc H_w. In this configuration, as the microwave power is progressively increased, the broad P₂ peak first gets smeared off and then a multiple peak structure appears, which develops into another narrower second peak (P_s-peak) at high enough microwave powers. In the orientation of plane, H_w ab plane, and H_dc H_w, we report for the first time the appearance and disappearance of a new second peak (P₂-like peak) as a function of microwave power.     

Controlling the textural parameters of mesoporous carbon materials

The mesoporous carbon materials prepared by inorganic templating technique using mesoporous silica, SBA-15 as a template and sucrose as a carbon source, have been systematically investigated as a function of sucrose to mesoporous silica composition, with a special focus on controlling the mesoporous structure, surface morphology and the textural parameters such as specific surface area, specific pore volume and pore size distribution. All the materials have been unambiguously characterized by XRD, N₂ adsorption–desorption isotherms, high-resolution transmission electron microscopy, high-resolution field emission scanning electron microscopy, and Raman spectroscopy. It has been found that the porous structure, morphology and the textural parameters of the mesoporous carbons materials, CMK-3-x where x represent the sucrose to silica weight ratio, can be easily controlled by the simple adjustment of concentration of sucrose molecules. It has also been found that the specific surface area of the mesoporous carbon materials systematically increases with decreasing the sucrose to silica weight ratio. Moreover, the specific pore volume of the materials increases from 0.57 to 1.31 cm³/g with decreasing the sucrose to silica weight ratio from 5 to 1.25 and then decreases to 1.23 cm³/g for CMK-3-0.8. HRTEM and HR-FESEM also show a highly ordered pore structure and better surface morphology for CMK-3-1.25 as compared to other materials prepared in this study. Thus, it can be concluded that the sucrose to silica weight ratio of 1.25 is the best condition to prepare well ordered mesoporous carbon materials with good textural parameters, pore structure and narrow pore size distribution.     

Influence of Bi2O3/WO3 substitution on the optical,mechanical, chemical durability and gamma ray shielding properties of lithium-borate glasses

Six different lithium bismuth boro-tungstate glasses with chemical composition 20Li₂O-(20-x)Bi₂O₃-xWO₃-60B₂O₃ (x = 0, 1, 2, 3, 4 and 5 mol%) were produced by the quenching method. Then, the glasses were investigated by means of their optical, mechanical, chemical durability and gamma ray shielding properties. Measured values of density and ultrasonic velocities were used to determine the elastic properties of the glasses. The optical band gap determined using the absorbance spectrum fitting (ASF) model was found to decrease under Bi₂O₃/WO₃ substitution. The presence of BO₃, BO₄, BiO₆, and WO₄ structural groups in the glasses was confirmed by Fourier transform infrared spectroscopy (FTIR). The dissolution rate in the glass 20Li₂O–15Bi₂O₃–5WO₃–60B₂O₃ (LBWB5) was found to be 10 times lower than 20Li₂O-20Bi₂O₃– 60B₂O₃. Mass attenuation coefficients (MAC) values of the produced glasses were determined using the MCNPX Monte Carlo code and Phy-X/PSD program. The photon attenuation parameters such as half value layer (HVL), mean free path (MFP), effective atomic number (Z_eff), exposure buildup factor (EBF) and energy absorption buildup factor (EABF) were also studied. The obtained results showed that Bi₂O₃/WO₃ substitution has a direct impact on the photon attenuation abilities of produced glasses. More specifically, HVL values increased from 0.252 × 10^?2 cm for LBWB0 glass to 0.275 × 10^?2 cm for LBWB5 glass. However, different trends were observed for the photon buildup factors for the produced glasses. It can be concluded that the produced glasses have promising structural, optical, and photon attenuation properties to be used for gamma shielding applications.     

Artificial neural network approach for prediction of stress–strain curve of near β titanium alloy

In the present study, artificial neural network（ANN） approach was used to predict the stress-strain curve of near beta titanium alloy as a function of volume fractions of a and b. This approach is to develop the best possible combination or neural network（NN） to predict the stress-strain curve. In order to achieve this, three different NN architectures（feed-forward back-propagation network,cascade-forward back-propagation network, and layer recurrent network）, three different transfer functions（purelin, Log-Sigmoid, and Tan-Sigmoid）, number of hidden layers（1 and 2）, number of neurons in the hidden layer（s）,and different training algorithms were employed. ANN training modules, the load in terms of strain, and volume fraction of a are the inputs and the stress as an output.ANN system was trained using the prepared training set（a,16 % a, 40 % a, and b stress-strain curves）. After training process, test data were used to check system accuracy. It is observed that feed-forward back-propagation network is the fastest, and Log-Sigmoid transfer function is giving the best results. Finally, layer recurrent NN with a single hidden layer consists of 11 neurons, and Log-Sigmoid transfer function using trainlm as training algorithm is giving good result, and average relative error is1.27 ± 1.45 %. In two hidden layers, layer recurrent NN consists of 7 neurons in each hidden layer with trainrp as the training algorithm having the transfer function of LogSigmoid which gives better results. As a result, the NN is founded successful for the prediction of stress-strain curve of near b titanium alloy.     

Stochastic analysis of a two unit cold standby system with preparation time for repair

This paper deals with the cost-benefit analysis of a two unit cold standby system in which the cold standby unit replaces the failed operative unit after a random amount of time. Inspection is required to decide whether it needs type I or type II repair. Failure, repair, replacement and inspection time distributions are arbitrarily distributed. A repair man is not always available with the system, but is called for repair whenever the operative unit fails.     

Pharmacokinetics of a single dose of phenylpropanolamine following oral administration at two different times of the day

Pharmacokinetics of a single oral dose of phenylpropanolamine (CAS 154-41-6) was investigated by administering 50 mg of the drug at 10.00 and 22.00 h to 8 healthy male volunteers in a crossover design with a wash-out period of 10 days. Serum samples were analysed for phenylpropanolamine using high performance liquid chromatography. Pharmacokinetic parameters were calculated using model independent method. A significant (p < 0.05) elevation in Cmax (227.45 versus 181.98 micrograms/l) was observed following the drug administration at 22.00 h as compared to 10.00 h. These variations may be due to circadian changes in gastric pH contributing to the time dependent changes in the absorption of the drug.     

Diamond-Based Supercapacitors with Ultrahigh Cyclic Stability Through Dual-Phase MnO2-Graphitic Transformation Induced by High-Dose Mn-Ion Implantation

While occasionally being able to charge and discharge more quickly than batteries, carbon-based electrochemical supercapacitors (SCs) are nevertheless limited by their simplicity of processing, adjustable porosity, and lack of electrocatalytic active sites for a range of redox reactions. Even SCs based on the most stable form of carbon (sp³ carbon/diamond) have a poor energy density and inadequate capacitance retention during long charge/discharge cycles, limiting their practical applications. To construct a SC with improved cycling stability/energy density Mn-ion implanted (high-dose; 10¹⁵–10¹⁷ ions cm⁻²) boron doped diamond (Mn-BDD) films have been prepared. Mn ion implantation and post-annealing process results in an in situ graphitization (sp² phase) and growth of MnO₂ phase with roundish granular grains on the BDD film, which is favorable for ion transport. The dual advantage of both sp² (graphitic phase) and sp³ (diamond phase) carbons with an additional pseudocapacitor (MnO₂) component provides a unique and critical function in achieving high-energy SC performance. The capacitance of Mn-BDD electrode in a redox active aqueous electrolyte (0.05 M Fe(CN)₆^3-/4− + 1 M Na₂SO₄) is as high as 51 mF cm⁻² at 10 mV s⁻¹ with exceptional cyclic stability (≈100% capacitance even after 10 000 charge/discharge cycles) placing it among the best-performing SCs. Furthermore, the ultrahigh capacitance retention (≈80% retention after 88 000 charge/discharge cycles) in a gel electrolyte containing a two-electrode configuration shows a promising prospect for high-rate electrochemical capacitive energy storage applications.