Toughening of epoxy resin systems using core–shell rubber particles: a literature review

Journal of Materials Science - Excellent thermal and mechanical properties and high chemical resistance with low shrinkage of epoxy resins open a wide window of various industrial applications,...     

Effect of Saturated/Unsaturated Fatty Acid Ratio on Physicochemical Properties of Palm Olein–Olive Oil Blend

Although blending polyunsaturated oil with more saturated or monounsaturated oils has been studied extensively, there is no similar information regarding the partial replacement of palm olein with olive oil (OO). Therefore the main objective of this study was to investigate the effects of OO partial replacement (0, 25, 50, 75, 90 and 100% w/w) on the chemical stability of palm olein oil (POO). The physicochemical properties of oil samples namely iodine value, peroxide value (PV), anisidine value, TOTOX value (total oxidation value, TV), free fatty acid (FFA), cloud point, color and viscosity were considered as response variables. Significant differences among the oil blend properties were determined at the significance level of P < 0.05. Apart from FFA, all the response variables were significantly influenced by type and concentration of oils. The oil blend containing 10% POO and 90% OO showed the highest TV (6.10); whereas the blend containing 90% POO and 10% OO exhibited the least TV (2.41). This study indicated that the chemical stability of oil blend significantly (P < 0.05) increased with increasing the proportion of polyunsaturated/monounsaturated fatty acid.     

Pricing and ordering decisions in a supply chain with imperfect quality items and inspection under buyback of defective items

In this article, the economic production and inventory model in a three-layer supply chain including one distributor, one manufacturer and one retailer for a single-product and general demand functions under three scenarios is developed. We assume that during the production process, both healthy and defective items are generated. As the first scenario, we develop the first model, in which the defective items are not reworked and all considered as scrape, while in the second model, we assume that the defective items are reworked and are sold as perfect item. In the second scenario, we assume that defective item can be sold with lower price than the selling price. Moreover, raw materials with imperfect quality are sent back from a distributor to outside supplier under a lower price. Determining the order quantity of the distributor and the selling prices of the distributor and the manufacturer as well as the retailer was the goal of this article such that the total profit of each member is maximised. In order to solve the models, the Stackelberg approach is employed between the members, and the concavity of the profit functions is proved using several theorems. Then, closed form solutions are derived for the decision variables and a solution algorithm is proposed to determine the optimal solutions. Finally, a numerical example is presented to illustrate the applicability of the model.     

The effect of graphene oxide on UV curing kinetics and properties of SU8 nanocomposites

In the present study SU8 nanocomposites were prepared by incorporating graphene oxide (GO ), and its effect on the UV curing kinetics, morphology, electrical, hardness and thermal properties of the nanocomposites were investigated at different loading levels of GO (0.1 ? 3 wt%). Studying the reaction kinetics of the UV curing process by means of real‐time infrared spectroscopy showed that the polymerization rate and the final conversion of epoxy groups was related to the loading level of GO in the nanocomposites. An autocatalytic kinetics model of the curing reaction confirmed the effect of GO nanoparticles on the curing rate constant (k ), the order of the initiation reaction (m ) and the ultimate conversion of the UV ‐cured nanocomposites. Appropriate experimental observations indicated that dispersion of GO within the resin plays a critical role on the cure kinetics and final conversion. The results of the kinetics modeling and morphological observations showed that the curing rate constant of the nanocomposites is highly dependent on the GO content and its dispersion state, indicating that GO prevents epoxy resin crosslinking by photoinitator deactivation. Moreover, oxygen functionalities, such as hydroxyl and carboxyl groups, on the surface of GO facilitate interfacial interactions between epoxy groups from the matrix and GO . Electrical conductivity measurements demonstrated that the UV ‐induced photo‐cured GO filled resins are conductive SU8 nanocomposites. It was observed that the thermal stability of the nanocomposites is enhanced due to the dispersion of GO in the matrix. Moreover, the microhardness analysis showed that addition of GO to neat SU8 increases the mechanical hardness of the nanocomposite. © 2016 Society of Chemical Industry     

Synthesis and characterization of PVAm/SBA-15 as a novel organic–inorganic hybrid basic catalyst

Composite polyvinyl amine/SBA-15 (PVAm/SBA-15) in various amounts of SBA-15 were prepared and characterized. The physical and chemical properties of PVAm/SBA-15 were investigated using FT-IR, XRD, BET, SEM and TGA techniques. The catalytic performance of each material was determined for the Knoevenagel condensation reaction between carbonyl compounds and ethyl cyanoacetate in the presence of ethanol as solvent. The effects of reaction temperature, solvent and the amounts of catalyst as well as recyclability of the catalyst were investigated. The catalyst used for this synthetically useful transformation showed a considerable degree of reusability besides being very active.     

Buckling of magneto-electro-hygro-thermal piezoelectric nanoplates system embedded in a visco-Pasternak medium based on nonlocal theory

Microsystem Technologies - In this present work the critical loading of magneto-electro-viscoelastic-hygro-thermal (MEVHT) piezoelectric nanoplates embedded in a viscoelastic foundation are...     

Generalized 3D high cycle fatigue criteria for multiscale bridging‐based progressive damage analysis of multilayer composite parts under random loads and material deterioration

Two frameworks are employed to develop two distinct categories of multiaxial high cycle fatigue life assessment models for composite components experiencing general and random loading conditions. In this regard, the decay in the material properties with cycles is also taken into account. It is obvious that in multilayer components, the fatigue failure is a progressive process that may be accompanied by gradual or sudden changes in the material properties and, consequently, the resulting stresses. In addition to using the traditional progressive damage analyses, a new concept is proposed for tracing of the localized fatigue failures more accurately. It is postulated that generally, the stress components have distinct frequencies, phase shifts, and mean values that all vary with time in a random manner. The proposed fatigue criteria, especially, the equivalent‐stress–based ones, are capable of predicting various fatigue failure modes, such as the fibre breakage, matrix cracking, and interfacial debonding. A special and comprehensive fatigue failure tracking and cycle counting algorithms that are capable of handling the mentioned general peculiarities are proposed. The proposed HCF criteria and the relevant fatigue life assessment algorithm are then implemented on a composite multilayer mono‐leaf spring of a realistic vehicle under a random field‐measured loading condition, as a typical component, and the results are compared and the experimental results conducted by the authors, for accuracy investigations. The considered stochastic road inputs have been chosen on the basis of the consumption times and field measurements.     

Power-efficient distributed scheduling of virtual machines using workload-aware consolidation techniques

There is growing demand on datacenters to serve more clients with reasonable response times, demanding more hardware resources, and higher energy consumption. Energy-aware datacenters have thus been amongst the forerunners to deploy virtualization technology to multiplex their physical machines (PMs) to as many virtual machines (VMs) as possible in order to utilize their hardware resources more effectively and save power. The achievement of this objective strongly depends on how smart VMs are consolidated. In this paper, we show that blind consolidation of VMs not only does not reduce the power consumption of datacenters but it can lead to energy wastage. We present four models, namely the target system model, the application model, the energy model, and the migration model, to identify the performance interferences between processor and disk utilizations and the costs of migrating VMs. We also present a consolidation fitness metric to evaluate the merit of consolidating a number of known VMs on a PM based on the processing and storage workloads of VMs. We then propose an energy-aware scheduling algorithm using a set of objective functions in terms of this consolidation fitness metric and presented power and migration models. The proposed scheduling algorithm assigns a set of VMs to a set of PMs in a way to minimize the total power consumption of PMs in the whole datacenter. Empirical results show nearly 24.9% power savings and nearly 1.2% performance degradation when the proposed scheduling algorithm is used compared to when other scheduling algorithms are used.