Anisotropy Effects in the Shape-Memory Performance of Polymer Foams

Isotropic and anisotropic shape-memory polymer foams are prepared by supercritical carbon dioxide foaming from a multiblock copolymer (PDLCL) consisting of poly(ω-pentadecalactone) and poly(ε-caprolactone) segments. Analysis by micro-computed tomography reveals for the anisotropic PDLCL foam cells a high shape anisotropy ratio of R = 1.72 ± 0.62 with a corresponding Young's compression moduli ratio between longitudinal and transversal direction of 4.3. The experimental compression data in the linear elastic range can be well described by the anisotropic open foam model of Gibson and Ashby. A micro-morphological analysis for single pores using scanning electron microscopy images permits the correlation between the macroscopic stress-compression behavior and microscale structural changes.     

Small-Molecule Inhibition of the uPAR ⋅ uPA Interaction by Conformational Selection

The urokinase receptor (uPAR) is a cell surface receptor that binds to the serine protease urokinase-type plasminogen activator (uPA) with high affinity. This interaction is beneficial for extravascular fibrin clearance, but it has also been associated with a broad range of pathological conditions including cancer, atherosclerosis, and kidney disease. Here, starting with a small molecule that we previously discovered by virtual screening and cheminformatics analysis, we design and synthesize several derivatives that were tested for binding and inhibition of the uPAR ⋅ uPA interaction. To confirm the binding site and establish a binding mode of the compounds, we carried out biophysical studies using uPAR mutants, among them uPAR^H47C−N259C, a mutant previously developed to mimic the structure of uPA-bound uPAR. Remarkably, a substantial increase in potency is observed for inhibition of uPAR^H47C−N259C binding to uPA compared to wild-type uPAR, consistent with our use of the structure of uPAR in its uPA-bound state to design small-molecule uPAR ⋅ uPA antagonists. Combined with the biophysical studies, molecular docking followed by extensive explicit-solvent molecular dynamics simulations and MM-GBSA free energy calculations yielded the most favorable binding pose of the compound. Collectively, these results suggest that potent inhibition of uPAR binding to uPA with small molecules will likely only be achieved by developing small molecules that exhibit high-affinity to solution apo structures of uPAR, rather than uPA-bound structures of the receptor.     

Novel Gemini Cationic Surfactants: Thermodynamic,Antimicrobial Susceptibility,and Corrosion Inhibition Behavior against Acidithiobacillus ferrooxidans

The Egyptian oil and gas industry is suffering from severe metal corrosion problems, particularly microbial-induced corrosion. There is limited knowledge on the corrosion inhibition of carbon steels in the presence of an acidophilic, iron-oxidizing bacterial species Acidithiobacillus ferrooxidans. Therefore, in this study, novel Gemini cationic surfactants, in three forms depending on variation in alkyl chains of 8, 12, and 16 carbon atoms named FHPAO, FHPAD, and FHPAH, respectively, were synthesized and characterized by Fourier transform infrared and nuclear magnetic resonance spectroscopy. The surface parameters and the thermodynamic of the synthesized surfactants were evaluated at three different temperatures, 20, 40, and 60 °C. The synthesized Gemini cationic surfactants were tested as broad-spectrum antimicrobial, antibacterial and anticandida agents. They evaluated as biocides and corrosion inhibitors against Acidithiobacillus ferrooxidans. FHPAD showed higher adsorption ability at the solution interface and higher affinity to construct micelles than FHPAO and FHPAH. Both adsorption and micellization processes were hydrophobic and temperature dependent. FHPAO, FHPAD and FHPAH exhibited wide-spectrum antimicrobial activities, and the highest activity and the lowest minimum bactericidal/fungicidal inhibitory concentrations were attributed to FHPAD. Furthermore, synthesized FHPAD demonstrated the highest metal corrosion inhibition efficiency of 95.5% at 5 mM in comparison to 87.5% and 81.7% for FHPAO and FHPAH, respectively. In conclusion, this study provides novel synthesized cationic surfactants with many applications in the oil and gas industry, such as broad-spectrum antimicrobial, biocides, and corrosion inhibitors for acidophilic, iron-oxidizing bacterial species Acidithiobacillus ferrooxidans.     

Corrosion Inhibition of Novel Prepared Cationic Surfactants for API N80 Carbon Steel Pipelines in Oil Industries

The objective of this study is to investigate the corrosion inhibition of API N80 steel pipelines in 1M HCl solution by a synthesized compound (N-(3-(dimethyl octyl ammonio) propyl) palmitamide bromide, subjected to four different modes of measurements. Weight loss (WL) was investigated at five different temperatures: 25–60°C, while potentiodynamic polarization, electrochemical impedance spectroscopy (EIS) and electrochemical frequency modulation (EFM) were tested at 25°C. The result showed that the synthesized inhibitor was good and its protection efficiency (%η) significantly increased by increasing both the dose and the temperature. The polarization curve revealed that the studied inhibitor acts as mixed-type of inhibitor. Adsorption of the investigated inhibitor led to a reduction in the double layer capacitance and an increase in the charge transfer resistance. The adsorption of this inhibitor was found to obey the Langmuir adsorption model. The thermodynamic parameters were calculated and discussed. A clear correlation was found between corrosion protection efficiency and theoretical parameters obtained using density functional theory.     

Exact and approximate analytic solutions of the nonlinear convective fin problem with temperature-dependent thermal conductivity

This article shows that the well-known nonlinear boundary value problem of the differential equation for temperature distribution of convective straight fins with temperature-dependent thermal conductivity is exactly solvable in an implicit form. Furthermore, an exact solution in an explicit form is derived. Also, an accurate analytic solution (series solution) is obtained by a new variation of the Adomian decomposition method.     

DETONATION CLASSIFICATION FROM ACOUSTIC SIGNATURE WITH THE RESTRICTED BOLTZMANN MACHINE

We compare the recently proposed Discriminative Restricted Boltzmann Machine (DRBM) to the classical Support Vector Machine (SVM) on a challenging classification task consisting in identifying weapon classes from audio signals. The three weapon classes considered in this work (mortar, rocket, and rocket‐propelled grenade), are difficult to reliably classify with standard techniques because they tend to have similar acoustic signatures. In addition, specificities of the data available in this study make it challenging to rigorously compare classifiers, and we address methodological issues arising from this situation. Experiments show good classification accuracy that could make these techniques suitable for fielding on autonomous devices. DRBMs appear to yield better accuracy than SVMs, and are less sensitive to the choice of signal preprocessing and model hyperparameters. This last property is especially appealing in such a task where the lack of data makes model validation difficult.     

A model for measuring complexity of automated and hybrid assembly systems

The demand for delivering product variety has been increasing. Increased product variety caused by product customization, personalization, evolution and changes in their manufacturing systems. Variety allows manufacturers to satisfy a wide range of customer requirements, but it can also be a major contributing factor to increased complexity of assembly. Complexity is generally believed to be one of the main causes of the present challenges in manufacturing systems such as lengthy and costly design processes, higher life cycle costs and the existence of numerous failure modes. Complex assembly systems are costly to implement, run, control and maintain. Assessing complexity of assembly helps guides designers in creating assembly-oriented product designs and following steps to reduce and manage sources of assembly complexity. On the other hand, reducing complexity of assembly helps lower assembly cost and time, improves productivity and quality and increases profitability and competitiveness. The complexity of assembly should be assessed by considering both products and their assembly systems. In this paper, a structural classification coding scheme has been used to measure assembly systems complexity. It considers the inherent structural complexity of typical assembly equipment. The derived assembly systems complexity accounts for the number, diversity and information content within each class of the assembly system modules. A domestic appliance drive assembly system is used to demonstrate the use of the classification code to calculate the assembly system complexity. The developed complexity metrics can be used by designers as decision support tools to compare and rationalize various automated assembly systems alternatives and select the design that meets the requirements while reducing potential assembly complexity and associated cost.     

Stochastic optimization of nonlinear energy sinks

Nonlinear energy sinks (NES) are a promising technique to achieve vibration mitigation. Through nonlinear stiffness properties, NES are able to passively and irreversibly absorb energy. Unlike the traditional Tuned Mass Damper (TMD), NES absorb energy from a wide range of frequencies. Many studies have focused on NES behavior and dynamics, but few have addressed the optimal design of NES. Design considerations of NES are of prime importance as it has been shown that NES dynamics exhibit an acute sensitivity to uncertainties. In fact, the sensitivity is so marked that NES efficiency is near-discontinuous and can switch from a high to a low value for a small perturbation in design parameters or loading conditions. This article presents an approach for the probabilistic design of NES which accounts for random design and aleatory variables as well as response discontinuities. In order to maximize the mean efficiency, the algorithm is based on the identification of regions of the design and aleatory space corresponding to markedly different NES efficiencies. This is done through a sequence of approximated sub-problems constructed from clustering, Kriging approximations, a support vector machine, and Monte-Carlo simulations. The refinement of the surrogates is performed locally using a generalized max-min sampling scheme which accounts for the distributions of random variables. The sampling scheme also makes use of the predicted variance of the Kriging surrogates for the selection of aleatory variables values. The proposed algorithm is applied to three example problems of varying dimensionality, all including an aleatory excitation applied to the main system. The stochastic optima are compared to NES optimized deterministically.     

Impact of hydroquinone on thermal and electrical properties of plasticized [poly(vinyl alcohol)]0.7(LiBr)0.3(H2SO4) solid acid membrane

A novel multi‐component system containing poly(vinyl alcohol), lithium bromide, sulfuric acid, ethylene carbonate and hydroquinone was prepared using a solution‐casting technique. The presence of hydroquinone as a reducing agent in the inorganic–organic membrane structure thus produced was thought to lead to enhanced thermal stability of the membrane. The activation energy for the thermal decomposition of the product samples increased with increasing hydroquinone doping. The ionic conductivities of the films were determined from AC impedance measurements in the temperature range 300–373 K. The maximum conductivity was found to be 1.75 × 10^?3 S cm^?1 for a film doped with 4 wt% hydroquinone. The results give some insight into the potential utility of the membrane as a proton‐conducting solid polymer electrolyte. Copyright © 2011 Society of Chemical Industry