Applied Mechanics and Materials Vols. 284-287

Abstract: Stress transfer in the carbon nanotube reinforced nanocomposites is investigated in this work. The model consists of two concentric cylinders, namely, a single-walled carbon nanotube cylinder (SWCNT) and a matrix cylinder, as the representative volume element (RVE). The stress analysis is performed using the shear lag model for the axisymmetric RVE. Analytical solutions for the axial normal stresses in the SWCNT and matrix, and the interfacial shear stress across the SWCNT/matrix interface are obtained. Numerical results show that using a large volume fraction improves the efficiency of the stress transfer from the matrix to the carbon nanotubes.

Abstract: This paper investigates the stochastic dynamic behaviors of nonlinear vibration of the fluid-loaded double-walled carbon nanotubes (DWCNTs) by considering the effects of the geometric nonlinearity and the nonlinearity of van der Waals (vdW) force. The nonlinear governing equations of the fluid-conveying DWCNTs are formulated based on the Hamilton’s principle. The Young’s modulus of elasticity of the DWCNTs is assumed as stochastic with respect to the position to actually describe the random material properties of the DWCNTs. By utilizing the perturbation technique, the nonlinear governing equations of the fluid-conveying can be decomposed into two sets of nonlinear differential equations involving the mean value of the displacement and the first variation of the displacement separately. Then we adopt the harmonic balance method in conjunction with Galerkin’s method to solve the nonlinear differential equations successively. Some statistical dynamic response of the DWCNTs such as the mean values and standard deviations of the amplitude of the displacement are computed. It is concluded that the mean value and standard deviation of the amplitude of the displacement increase nonlinearly with the increase of the frequencies.

Abstract: Ag/ZnO nanorod structure was synthesized by using the hydrothermal method to grow ZnO nanorods and melted silver nonoparticles into ZnO nanorods by thermal annealing process in vacuum at 700 oC. The photocatalytic activity for methylene blue decolorization is enhanced by silver nanoparticles melted into a ZnO nanorod structure owing to the formation of Schottky barrier near the Ag/ZnO interface prolongs the recombination of electron-hole pairs effectively. The size effect of silver nanoparticles in the Ag/ZnO nanorod structure for photocatalytic activity was discussed which was changed from 12 to 34 nm. The smaller silver nanoparticle size sample shows better decolorization efficiency of methylene blue solution owing to the higher surface area of Ag/ZnO nanoroad. Ag/ZnO nanorod films have been characterized by X-ray diffraction (XRD), UV-vis spectroscopy, field-emission scanning electron microscopy (FE-SEM) and transmission electron microscopy (TEM). The dye decolorization significantly increased from 69 to 99 % after UV light irradiation for 8 hr by the optimum Ag/ZnO nanorod film.

Abstract: System-in-package (SiP) has become a mainstream technology in IC package industry as it provides the solutions to the growing needs of high speed functions, mobility/portability, energy efficiency, and miniaturization of electronic products. One special form of SiP is the multi-chip module (MCM) in which multiple integrated circuits (ICs), semiconductor dies or other discrete components are packaged onto a unifying substrate. Thus, the reliability of package integrity becomes one of the major reliability concerns. In the present paper, a robust design analysis on the thermo-mechanical reliability of an MCM package with flip-chip technology is demonstrated. Our results show that for the specific package, the CTE of the substrate is the most influential factor to the fatigue reliability of the package. The optimal combination of the parameters is recommended. The robust design analysis optimizes the fatigue life from 165 cycles to 1080 cycles which is a 554.5% gain on the fatigue life.

Abstract: Ethylmaltol was prepared from ethylfurfuryl alcohol by electrolysis, acidification, glycosidation, oxidation and acidolysis. The ultraviolet spectrophotometric method was used for quantitative determination of ethylmaltol. The chemical structures of the intermediates were characterized by mean of FTIR. The experimental results showed that the yield of ethylmaltol was greatly dependent on electrolyte, quantity of electricity, oxidation time, acidolysis time and acidolysis temperature. The appropriate conditions were electrolyte of NaBr, quantity of electricity of 1.6Ah, oxidation time of 3 hours, acidolysis timeof 3 hours, acidolysis temperature of 100°C and the highest yield of ethylmaltol was 66.76%.

Abstract: The optimum extraction condition of water-soluble asparagus powder through water boiling method is to extract it twice, in the first extraction, 8% is set as the solid-liquid ratio, 15 minutes is set as the soak time and 40 minutes is set as the boiling time; in the second extraction, 10% is set as the solid-liquid ratio, 40 minutes is set as the boiling time. Under this condition, the dry yield rate is 33.98%, and the total active substance yield rate is 10.34% (including flavones yield rate of 1.0%, saponin yield rate of 5.99%, and polysaccharide yield rate of 3.35%). Water-soluble asparagus powder has good removal effects on hydroxyl radicals, superoxide anion free radicals, and DPPH free radicals. The water-soluble asparagus powders made from the raw material in different pick-time have different removal effects on DPPH free radicals, and the asparagus powder made from asparagus picked in August, September, and October is better.The best is to read these instructions and follow the outline of this text.

Abstract: Stents have been used for the treatment of cardiovascular diseases and are often placed inside coronary arteries. The manufacture of metal stents is a challenging issue because of the features, like geometry and the material of stents. An improved manufacturing process of stents is presented. The proposed processes consist of the following steps: boring and polishing, laser cutting, vacuum annealing and surface finishing (ultrasonic cleaning, acid pickling, and electrolytic polishing). The precision boring operation is used to obtain the required wall thickness from off-the-shelf seamless tube. The laser cutting is performed to change the shape of the stent, and the finishing operations is selected to modify the surface features, like smoothness and texture of stents. 316LVM stainless steel sample with an outside-diameter of 3 mm, a wall thickness of 0.1 mm, and a length of 25 mm, had been manufactured and demonstrated the proposed manufacture technology. The surface roughness of a stent manufactured is the value of Ra 14.3 nm which basically meets the design requirement for further performance evaluation. It is hoped that the above finding can be used for future study of stents.

Abstract: A stable and versatile biosensor surface is a desirable feature for any sensor, and the DNA-directed immobilization (DDI) of protein-DNA conjugates on the mixed ssDNA/ Oligo(ethylene glycol) (OEG) self-assembled monolayers (SAMs) offer an alternative choice for preparing various types of protein chips. The patterned DNA chip is suitable for long-term storage and easily converted into a protein chip in one simple step. In our previous study, the experimental results indicated that a 50:1 ratio of OEG: COOH-terminated OEG and DNA sequences with 20 mer are the best conditions or making a protein chip via a DNA-directed immobilization (DDI) method. In this study, we investigate the effect of buffer pH values on the measurement of human serum albumin (HSA) by using the protein chip prepared by DDI method. The results showed that the largest SPR response is found in the detection of HSA with the use of 10 mM MES buffer (150 mM sodium chloride, adjusted to pH 4.0). We suggest that this was a consequence from the contribution of attractive electrostatic force between HSA and the negatively charged sensor surface. The lowest detection limitation of HSA with the use of MES buffer is 0.02 mg/ml. In addition, there is a linear relationship between the SPR signals and HSA concentrations (from 0.02 mg/ml to 0.5 mg/ml). Chip regeneration experiments were also performed in our study with the results showing that the average response for HSA detection on regenerated surface was nearly 92.3% of the response produced by using fresh surface.

Abstract: Batch reactive distillation is an integrated unit of batch reactor and distillation. It provides benefits of having higher conversion and yield by continuous removal of side product. The aim of this paper is to develop an artificial neural network (ANN) based model for production of isopropyl myristate in an industrial scaled semibatch reactive distillation. Two cases of the MIMO model were developed. Case 1 does not consider historical data as inputs while case 2 does. The trained ANN for both cases was validated with independent validation data and the best architecture was optimized. Case 1 resulted to 8 inputs, 14 hidden nodes and 2 outputs [8-14-2] ANN while Case 2 resulted to [12-13-2] ANN. The results show that both ANN models have ability to predict the unknown validation and testing data very well. However, the [8-14-2] ANN model produce higher accuracy than [12-13-2] ANN model with MSE of 0.00094 and 0.0013, respectively.

Abstract: MTBE is a chemical that can be used as anti-knock additive to replace lead additive (tetra ethyl lead) which can be efficiently produced using reactive distillation process. It has been established in the literature that MTBE reactive distillation poses a highly nonlinear behavior due to the combination of reaction and separation processes. A reliable model for predicting the behavior is required especially for the control purposes. In this work, a Neural Wiener model which is one of the available types of oriented block model was utilised to develop the MTBE reactive distillation model. The required data for the Neural Wiener model were generated using a validated Aspen dynamics model for the MTBE reactive distillation process. It is found that the Neural Wiener model is capable to predict the MTBE purity and isobutene conversion with accuracy of 98.55% and 96.95%, respectively. Those values are quantitatively better in comparison to the state space model which gives lower values for prediction accuracy of 87.86% and 82.90%, respectively.