Improving the mechanical,thermal and electrical properties of polyurethane- graphene oxide nanocomposites synthesized by in-situ polymerization of ester-based polyol with hexamethylene diisocyanate

Many polyols or diols have been used for the synthesis of polyurethanes (PU), however, to the best of our knowledge, PU-graphene oxide (GO) nanocomposites synthesized with ester-based polyols have been rarely studied. In this work ester-based polyol synthesized by the reaction of adipic acid and 1,4 butane diol, was in-situ polymerized with hexamethylene diisocyanate (HDI) and GO to prepare PU-GO nanocomposites. The content of GO was changed from 1 to 2.5 wt% and its effect on the mechanical, thermal and electrical properties of the samples were examined. The presence of GO more than 1.5% in the nanocomposites resulted in brittle samples and reduced the tensile strength, however, the Young’s modulus of the samples containing 1 and 1.5% was increased to 11 and 12.08-fold (275 and 302 MPa) compared to the neat PU (25 MPa), respectively. The shore A hardness of the samples was increased from 86 for PU to 96 for PUGO-1.5. The abrasion resistance of the samples was decreased by increasing the GO content. Results of the thermogravimetric analysis showed that higher amounts of GO increase the thermal stability of the samples. The chemical and physical interactions between the surface of GO nanolayers and the PU chains were confirmed by FTIR spectroscopy. The dynamic mechanical analysis of the samples showed that GO nanolayers decreased the molecular motions of the PU chains in the nanocomposites which were noticed by shifting the glass transition to the higher temperatures.     

Voronoi based discrete least squares meshless method for heat conduction simulation in highly irregular geometries

A new technique is used in Discrete Least Square Meshfree(DLSM) method to remove the common existing deficiencies of meshfree methods in handling of the problems containing cracks or concave boundaries. An enhanced Discrete Least Squares Meshless method named as VDLSM(Voronoi based Discrete Least Squares Meshless) is developed in order to solve the steady-state heat conduction problem in irregular solid domains including concave boundaries or cracks. Existing meshless methods cannot estimate precisely the required unknowns in the vicinity of the above mentioned boundaries. Conducted researches are limited to domains with regular convex boundaries. To this end, the advantages of the Voronoi tessellation algorithm are implemented. The support domains of the sampling points are determined using a Voronoi tessellation algorithm. For the weight functions, a cubic spline polynomial is used based on a normalized distance variable which can provide a high degree of smoothness near those mentioned above discontinuities. Finally, Moving Least Squares(MLS) shape functions are constructed using a varitional method. This straight-forward scheme can properly estimate the unknowns(in this particular study, the temperatures at the nodal points) near and on the crack faces, crack tip or concave boundaries without need to extra backward corrective procedures, i.e. the iterative calculations for modifying the shape functions of the nodes located near or on these types of the complex boundaries. The accuracy and efficiency of the presented method are investigated by analyzing four particular examples. Obtained results from VDLSM are compared with the available analytical results or with the results of the well-known Finite Elements Method(FEM) when an analytical solution is not available. By comparisons, it is revealed that the proposed technique gives high accuracy for the solution of the steady-state heat conduction problems within cracked domains or domains with concave boundaries and at the same time possesses a high convergence rate which its accuracy is not sensitive to the arrangement of the nodal points. The novelty of this paper is the use of Voronoi concept in determining the weight functions used in the formulation of the MLS type shape functions.     

Physical and Morphological Properties of Combined Treated Wood Polymer Composites by Maleic Anhydride and Methyl Methacrylate

Wood polymer composites were prepared by consecutive impregnation with maleic anhydride (MAN) and methyl methacrylate (MMA). Samples impregnated with MAN alone, were heated at 120°C and 150°C for 4 and 8 h. Based on the Fourier transform infrared (FT-IR) analysis and soaking-drying test results, treatment with MAN at 150°C for 4 h resulted in formation of stable crosslinks. In the second stage, MMA was used for in situ polymerization within MAN-treated wood. Field emission scanning electron microscopy observation and FT-IR analysis indicated that MMA copolymerized with MAN, and the resultant polymer filled up the lumen and is also grafted on to the cell wall. Improvement of water repellency and dimensional stability were observed in the treated samples, particularly in combined treated samples. The MAN/MMA treatment improved interaction between polymer and wood.     

A linear model of elasto-plastic and adhesive contact deformation

Rigorous non-linear models of elasto-plastic contact deformation are time-consuming in numerical calculations for the distinct element method (DEM) and quite often unnecessary to represent the actual contact deformation of common particulate systems. In this work a simple linear elasto-plastic and adhesive contact model for spherical particles is proposed. Plastic deformation of contacts during loading and elastic unloading, accompanied by adhesion are considered, for which the pull-off force increases with plastic deformation. Considering the collision of a spherical cohesive body with a rigid flat target, the critical sticking velocity and coefficient of restitution in the proposed model are found to be very similar to those of Thornton and Ning’s model. Sensitivity analyses of the model parameters such as plastic, elastic, plastic-adhesive stiffnesses and pull-off force on work of compaction are carried out. It is found that by increasing the ratio of elastic to plastic stiffness, the plastic component of the total work increases and the elastic component decreases. By increasing the interface energy, the plastic work increases, but the elastic work does not change. The model can be used to efficiently represent the force-displacement of a wide range of particles, thus enabling fast numerical simulations of particle assemblies by the DEM.     

ERES: an extended regular expression signature for polymorphic worm detection

Journal of Computer Virology and Hacking Techniques - The quick spreading of modern sophisticated polymorphic worms poses a serious threat to the internet security. So far, several signature...     

Synthesis of Cellulose-graft-Polychloromethylstyrene-graft-Polyacrylonitrile Terpolymer/Organoclay Bionanocomposite by Metal Catalyzed Living Radical Polymerization and Solvent Blending Method

A bionanocomposite of grafted cellulose and organo-modified clay was synthesized through solution intercalation method. For this purpose, chloromethylstyrene was grafted onto cellulose using acryloylchloride and the subsequent free radical polymerization. The synthesized cellulose-graft-polychloromethylstyrene was used as an atom transfer radical polymerization macroinitiator of acrylonitrile in the presence of CuCl/2,2′-bipyridine catalyst system, to prepare the cellulose-graft-polychloromethylstyrene-graft-polyacrylonitrile terpolymer. For preparing the modified clay, Na-montmorillonite was mixed with hexadecyl trimethyl ammonium chloride salt. Finally, cellulose-graft-polychloromethylstyrene-graft-polyacrylonitrile/organoclay bionanocomposite was prepared in CCl₄ by solution intercalation method.     

Prediction of heavy oil viscosity using a radial basis function neural network

Heavy oil and extra heavy oil resources comprise about 75% of petroleum resources. The most important characteristic of heavy oils is their viscosity. Consequently, to extract and prepare these kinds of crude oil for use, great emphasis should be put on viscosity. The present study highlights the application of intelligent model named radial basis function (RBF) network optimized by genetic algorithm for estimation of diluted heavy oil viscosity in presence on kerosene. The input parameters of model were temperature and mass fraction of kerosene. The output of model was viscosity of heavy oil. Genetic algorithm was utilized to optimize the tuning parameters of RBF model. The outcomes of this study showed that the proposed model is accurate in estimation of target data.     

Adaptive fuzzy-SIFT rule-based registration for 3D cardiac motion estimation

Applied Intelligence - 3D Speckle tracking techniques are used to quantify cardiac deformation in 3D echocardiographic images. Elastic image registration methods are successful in solving 3D...