Calcined oyster shell nanoparticles (COS NPs): a new,efficient and reusable catalyst for one-pot rapid preparation of 1,8-dioxo-octahydroxanthenes under solvent-free conditions

Research on Chemical Intermediates - Calcined oyster shell nanoparticles (COS NPs) as a novel heterogeneous nanocatalyst were prepared and fully characterized by X-ray fluorescence analysis,...     

Amino-functionalized SBA-15 catalyzed one-step synthesis of 2-amino-5-cyano-4-hydroxy-6-aryl pyrimidines

A simple and efficient approach towards one-step synthesis of 2-amino-5-cyano-4-hydroxy-6-aryl pyrimidines has been developed. It is based on three-component condensation of aliphatic, aromatic or heterocyclic aldehydes, ethyl cyanoacetate and guanidinium carbonate in the presence of amino-functionalized SBA-15 catalyst in ethanol. In this chemical process, the tautomeric interconversion of pyrimidine derivatives has been observed. This efficient technique has the advantage to give 2-amino-pyrimidine derivatives using a heterogeneous catalyst in high yields, to be completed in short reaction times and to offer a simple product isolation procedure.     

Inventory control and pricing for perishable products under age and price dependent stochastic demand

Multistage stochastic programming (SP) with both endogenous and exogenous uncertainties is a novel problem in which some uncertain parameters are decision-dependent and others are independent of decisions. The main difficulty of this problem is that nonanticipativity constraints (NACs) make up a significantly large constraint set, growing very fast with the number of scenarios and leading to an intractable model. Usually, a lot of these constraints are redundant and hence, identification and elimination of redundant NACs can cause a significant reduction in the problem size. Recently, a polynomial time algorithm has been proposed in the literature which is able to identify all redundant NACs in an SP problem with only endogenous uncertainty. In this paper, however, we extend the algorithm proposed in the literature and present a new method which is able to make the upper most possible reduction in the number of NACs in any SP with both exogenous and endogenous uncertain parameters. Proving the validity of this method is another innovation of this study. Computational results confirm that the proposed approach can significantly reduce the problem size within a reasonable computation time.     

Determination of the Heat Transfer Coefficient of Metal Oxide Based Water Nanofluids in a Laminar Flow Regime Using an Adaptive Neuro-Fuzzy Inference System

In order to enhance the thermal properties of turbine oil (TO), three different nanoparticles (CuO, Al₂O₃, and TiO₂) are loaded into the TO. To measure the thermal performance of nanoparticle-based TO nanofluids at laminar flow and under constant heat flux boundary conditions, an experimental setup was applied. The obtained data clearly demonstrate the positive effect of all nanoparticles on the heat transfer rate of TO. As the most important factor, the heat transfer coefficient of the abovementioned two-phase systems is increased upon increasing both the volume concentration and the flow rate. An adaptive neuro-fuzzy inference system (ANFIS) is applied for modeling the effect of critical parameters on the heat transfer coefficient of nanoparticle-TO based nanofluids numerically. The results are compared with experimental ones for training and test data. The results suggest that the developed model is valid enough and promising for predicting the extant of the heat transfer coefficient. R² and MSE values for all data were 0.990208751 and 108.1150734, respectively. Based on the results, it is obvious that our proposed modeling by ANFIS is efficient and valid, which can be expanded for more general states.     

Offline estimation of 2D crystal lattice parameters by processing the electron diffraction image

Electron diffraction provides useful information about the internal composition of materials and has been in the use of material scientists for more than fifty years. In order to extract useful information from offline diffraction images, they are manually analyzed by using some photometric technique. Manual analysis is however a cumbersome, laborious and difficult task. To reduce the labors of material scientists one can employ image processing techniques to perform automated analysis, due to the well established popularity and clear evidence of widely used image processing techniques. In this work an image processing technique is being proposed for the extraction of 2D unit cell information from diffraction images on one hand and finding the 2D point group contained by the lattices on the other. The technique employs a morphological shrinking operation to find the center of each spot in the underlying preprocessed diffraction image. This is followed by the extraction of eight points with reference to the spot produced by the transmitted electron beam. The resultant nine points, i.e. the extracted eight plus the reference spot generated by the transmitted electron beam, are then subjected to symmetry operations, rotation symmetry and mirror symmetry, in polar coordinate system, to classify the point group of the lattice produced by the electron diffraction. One of the difficult task, even in manual analysis, is to ascertain the exact spot where the transmitted electron beam hit the sample at the time of realization of the image. This has been accurately and intuitively done by employing the notion that the transmitted spot must have greater number of pixels, with the highest gray value, among the diffracted spots. The proposed strategy has been applied to a sample set of various images and the results shows that the technique is efficient in determining the unit cell in 2D and classify the point group with good accuracy.     

Synthesis,Characterization and Properties of a Novel Environmentally Friendly Mono Azo Disperse Dye and Its Application on Polyethylene Terephthalate (PET)

The aim of this research is to achieve the synthesis of a novel mono azo disperse dye containing both a β‐naphthyl acetate group and carboxylic acid ester group and application on PET fabric. In this study the dyeing properties have also been investigated. The synthesized dye was characterized using UV‐Vis, FTIR, ¹H NMR and ¹³C NMR spectroscopic techniques. To investigate alkali‐clearability, both alkali‐hydrolysis behavior and the effect of its fastness properties with regard to PET fabric were examined. This dye showed a reasonable level of hydrolysis under relatively mild alkaline conditions. The application of the dye to PET fabric showed good leveling and building up properties. Estimating fastness properties of the dyed fabric showed excellent wash, rubbing fastness, good light and sublimation fastness. The results furthermore displayed that the synthesized dye offers the option of alkali‐clearing process over that of a conventional reduction‐clearing process. Therefore, the value of Chemical Oxygen Demand (COD), Biological Oxygen Demand (BOD) and water pollution as well as the expenditure of production were decreased.     

Phenylpropanoids from Tanacetum baltistanicum with Nematocidal and Insecticidal Activities

Chemistry of Natural Compounds - One new and seven known secondary metabolites 1–8 were isolated, and the nematocidal and insecticidal activities of major compounds from Tanacetum...