Synthesis,Characterization and Catalytic Activities of Palladium(II) Nitroaryl Complexes

Two palladium(II) nitroaryl complexes trans-[bromo(p-nitrophenyl)bis(triphenylphosphine)palladium(II)] 1 and trans-[bromo(2,4-dinitrophenyl)bis(triphenylphosphine)palladium(II)] 2 have been synthesized. The complexes were characterized by FTIR and NMR (¹H, ¹³C and ³¹P) spectroscopy and elemental analysis. The molecular structure of complex 2, as confirmed by X-ray crystallography, reveals that the Pd atom and its neighboring groups (two PPh₃, Br and phenylene group) lie in a slightly distorted square plane. In the UV–Vis spectra of the complexes 1 and 2, the palladium to aryl charge transfer bands were observed. The emission peaks from the singlet excited states (S₁ → S₀) were observed in the photoluminescence spectra of the complexes. The thermal stability of the complexes has been studied by thermal gravimetric analysis (TGA). TGA data showed that both complexes are thermally stable up to 200 °C, and complex 1 is more stable than 2. The catalytic efficiency of the new palladium(II) complexes was studied as demonstrated using the Sonogashira coupling reactions with good yields. The experimental results suggest that the Sonogashira coupling reactions can be performed at moderate temperature (50 °C) using these new palladium(II) complexes as catalysts.     

Estimation of gross calorific value of coals using artificial neural networks

The gross calorific value (GCV) is an important property defining the energy content and thereby efficiency of fuels, such as coals. There exist a number of correlations for estimating the GCV of a coal sample based upon its proximate and/or ultimate analyses. These correlations are mainly linear in character although there are indications that the relationship between the GCV and a few constituents of the proximate and ultimate analyses could be nonlinear. Accordingly, in this paper a total of seven nonlinear models have been developed using the artificial neural networks (ANN) methodology for the estimation of GCV with a special focus on Indian coals. The comprehensive ANN model developed here uses all the major constituents of the proximate and ultimate analyses as inputs while the remaining six sub-models use different combinations of the constituents of the stated analyses. It has been found that the GCV prediction accuracy of all the models is excellent with the comprehensive model being the most accurate GCV predictor. Also, the performance of the ANN models has been found to be consistently better than that of their linear counterparts. Additionally, a sensitivity analysis of the comprehensive ANN model has been performed to identify the important model inputs, which significantly affect the GCV. The ANN-based modeling approach illustrated in this paper is sufficiently general and thus can be gainfully extended for estimating the GCV of a wide spectrum of solid, liquid and gaseous fuels.     

Effects of Rheological Behavior of Viscoelastic Surfactants on Formation Damage in Carbonate Rocks

Viscoelastic surfactants (VES) are used in various oilfield applications such as matrix stimulation and enhanced oil recovery. The loss of surfactants during the propagation of VES could result in a significant reduction in the permeability of the rock (formation damage). The objective of the current work was to identify the effect of rheological behavior of the VES on the formation damage using core‐flooding experiments, nuclear magnetic resonance (NMR), and scanning electron microscopy (SEM) analysis. A combination of core‐flooding, NMR, and SEM techniques was used to quantify and identify the location of formation damage in carbonate core samples. The viscosity and storage modulus strongly depend on the nature and concentration of salts. The viscosity increased by increasing the salt concentration up to a specific point (15 wt% CaCl₂) and then starts decreasing. The VES formulations that displayed the maximum and minimum viscosities were used to identify the impact of rheological behavior on formation damage. Core‐flooding experiments were performed to assess the formation damage due to high‐viscosity and low‐viscosity VES formulations. The reduction in the permeability of carbonate rocks reaches more than 90% of the initial permeability. It was found that low‐viscosity VES caused more damage compared with high‐viscosity VES when they were used at constant concentrations. NMR and core‐flooding results revealed that the damage took place both in pore body and pore throat. However, most of the surfactant was retained at the pore throat.     

Effects of ZnO and MoS<Subscript>2</Subscript> Solid Lubricants on Mechanical and Tribological Properties of M50-Steel-Based Composites at High Temperatures: Experimental and Simulation Study

Prospective beneficial effects of mixtures of temperature-adaptive solid lubricants (ZnO–MoS₂) on mechanical and tribological properties of M50 alloy steel were investigated at temperatures from 25 to 800 °C. ZnO and MoS₂ were mixed with M50 (designated as M) to create composites MZ (M50 steel plus ZnO), MM (M50 steel plus MoS₂), and MZM (M50 steel plus both additives). Sliding friction and wear experiments were performed at different temperatures using a pin-on-disk at a sliding speed of 0.2 m s^?1 and a load of 12 N. Silicon nitride and M50 steel were used as the pin materials. In order to understand the friction and wear behavior of composites, analyses of their surfaces were done using XRD, EPMA, FESEM, EDS line/mapping, and XPS tests. A dynamic simulation model based on the finite element method was built to simulate the different stresses on the contact pairs. Results elucidated that MZM attained the least friction (0.17), compared to M (0.40), MZ (0.26), or MM (0.29) at 800 °C. The increase in surface roughness of MZM due to sliding was reduced by 37.3% compared to that of MZ (11.9%) or MM (22.7%). The good lubricating behaviors were referred to the synergetic effects of ZnO, MoS₂, and formed lubricating components on worn surfaces.     

Genome size and base composition in Oryzaephilus surinamensis (Coleoptera: Sylvanidae) and differences between native (feral) and silo pest populations in Israel

In this study, flow cytometry was used for assessing and comparing the genome size (GS) and the whole genome base composition (AT/GC ratio) of the saw-toothed grain beetle Oryzaephilus surinamensis (L.). In addition, the presence and frequency of endosymbiotic Wolbachia bacteria was studied. The haploid GS was estimated to lie within the range of 151.5-154 Mbp in O. surinamensis, making it the smallest value of haploid GS known among beetles. Furthermore, it was found that in eight silo pest populations GS was significantly smaller than in eight feral (native) populations obtained from fallen oak acorns. The ability of O. surinamensis to colonize different habitats globally could be connected with an unusually AT-rich (for an invertebrate) genome (AT-base content ranging from 68 to 76%). Native (feral) populations of O. surinamensis appear to have genetically diverged from the storage-pest populations tested. Larvae of pest origin survived better than larvae of native (feral) origin under laboratory conditions, which resembled silo conditions more than natural habitats.     

Tunable Thermoelectric Performance in Porous Armchair Graphene Nanoribbons as a Function of Strain,Pore Morphology and Temperature

In this paper, the thermoelectric performance of porous armchair graphene nanoribbons under tensile and compressive strain is investigated as a function of pore morphology and temperature. For all the porous structures irrespective of their pore size, the performance improves at a compressive strain of 10%, while for tensile nature, the minimum cut-off strain required for improved thermoelectric figure of merit (ZT) shows an inverse relation with the pore size. In addition, optimal pore shape geometry can yield better performance, even at lower values of strain. Further analysis reveals that tensile strain is not able to improve the performance at low and intermediate temperatures of around 300 K, whereas tensile/compressive strain is effective in enhancing the performance of porous armchair graphene nanoribbons at higher temperatures. Furthermore, the structures are found to be more sensitive to compressive strain than the tensile one since the effect of compressive strain is found to improve ZT more significantly. Our analysis based on Non-Equilibrium Green’s function calculations suggests a possible route for tailoring the functionality of nanomaterials so as to achieve great potentials for thermoelectric applications at various temperatures.     

An integrated fine-grain runtime system for MPI

Fine-grain MPI (FG-MPI) extends the execution model of MPI to allow for interleaved execution of multiple concurrent MPI processes inside an OS-process. It provides a runtime that is integrated into the MPICH2 middleware and uses light-weight coroutines to implement an MPI-aware scheduler. In this paper we describe the FG-MPI runtime system and discuss the main design issues in its implementation. FG-MPI enables expression of function-level parallelism, which along with a runtime scheduler, can be used to simplify MPI programming and achieve performance without adding complexity to the program. As an example, we use FG-MPI to re-structure a typical use of non-blocking communication and show that the integrated scheduler relieves the programmer from scheduling computation and communication inside the application and brings the performance part outside of the program specification into the runtime.     

Microwave-Assisted Pretreatment of Sago Palm Bark

Three types of microwave-assisted diluted solvents were employed using 0.1 N H₂SO₄ (MSA), 0.1 N NaOH (MSH), and 0.01 N NaHCO₃ (MSB). These solvents were evaluated as possible pretreatment routes for sago palm bark (SPB) with their effects on the pretreated substrate. A variety of analyses, consisting of fiber analysis, energy dispersive X-ray spectroscopy (EDX), X-ray fluorescence spectrometer (XRF), X-ray powder diffraction (XRD), thermogravimetric analysis (TGA), scanning electron microscope (SEM), and high-performance liquid chromatography (HPLC), were performed to understand the pretreatment effects on the chemical and physical characteristics of SPB and pretreatment liquor. The thermal analysis has revealed that higher hemicellulose degradation was also found in MSA pretreatment. In the analyses of the pretreatment liquid for the extracted monomeric sugar, a higher amount of glucose was found (9 mg/g) using MSH pretreatment and the highest xylose level was found (4 mg/g) using MSA pretreatment. The analysis of the formation of inhibitors has shown that acetic acid was only found in the MSH pretreatment.     

The gray level aura matrices for textured image segmentation

Inspired by an intuitive analogy that exists between the gray level textures and the miscibility in the multiphase fluids, the aura concept was developed from set theory tools in order to modeling the texture image. The gray level aura matrix (GLAM) has been then proposed to generalize the gray level cooccurrence matrix (GLCM) which remains very popular in the texture analysis. The GLAM indicates how much each gray level is present in the neighborhood of each other gray level. The neighborhood is defined by a structuring element as one used in mathematical morphology. The GLAM is mainly used and studied in synthesis and classification of textures framework but very few works are devoted to the segmentation. The aim of this paper is to exploit the GLAM for the segmentation of textured images. Experiments results over synthetic and real images show the efficiency of the GLAM. The influence of the shape and the size of the structuring element on the segmentation results are also studied.