NiFe2O4@SiO2–PPA Nanoparticle: A Green Nanocatalyst for the Synthesis of β-Acetamido Ketones

ABSTRACT

In this work, silica coated magnetic nanoparticles of modified polyphosphoric acid (NiFe₂O₄@SiO₂–PPA deigned as NFS–PPA) represent as a reusable and green catalyst for one-pot four-component synthesis of β-acetamido ketones at room temperature under solvent-free conditions. This catalyst was synthesized and characterized by X-ray diffractions, transmission electron microscopy, scanning electron microscopy and vibrating sample magnetometry. The magnetic catalyst can be easily removed by a simple magnet and reused up to five times without any loss of its high catalytic activity. In addition to facility, this protocol enhances product purity and promises economic and also environmental profits.     

DLS: A dynamic local stitching mechanism to rectify transmitting path fragments in wireless sensor networks

In this paper, a pair of novel rectification algorithms (greedy negative pressure push algorithm and dynamic local stitching algorithm) is proposed to cooperatively repair broken transmitting paths in Wireless Sensor Networks. Our approach is to overcome the poor data validity in WSNs, specifically for harsh application environments – such as unattended sensor nodes or frail wireless transmitting channels – where fault tolerant becomes a vital aspect. Using adjacency information, Greedy negative pressure push algorithm can efficiently grow the transmitting path to achieve the minimum energy consumption for relays model. Here, we measured packet travel time and the expectation of relay distance to set this model's key parameters to achieve the lowest possible end-to-end transmitting delay. Dynamic local stitching algorithm has a major difference with other existing routing algorithms in rectifying broken paths; despite others that reroute whole paths, our algorithms only stitch broken fragments of the original path spending minimum amount of energy as well as recovery time. Based on mathematical computing and simulation, our novel rectification algorithm could effectively (1) reduce the total number of routing overheads, (2) improve net throughput, and (3) increase system fault tolerant much better than four already designed routing algorithms. Results were also very promising to motivate other algorithms in this field.     

A robust predictive model for base shear of steel frame structures using a hybrid genetic programming and simulated annealing method

This study presents a new empirical model to estimate the base shear of plane steel structures subjected to earthquake load using a hybrid method integrating genetic programming (GP) and simulated annealing (SA), called GP/SA. The base shear of steel frames was formulated in terms of the number of bays, number of storey, soil type, and situation of braced or unbraced. A classical GP model was developed to benchmark the GP/SA model. The comprehensive database used for the development of the correlations was obtained from finite element analysis. A parametric analysis was carried out to evaluate the sensitivity of the base shear to the variation of the influencing parameters. The GP/SA and classical GP correlations provide a better prediction performance than the widely used UBC code and a neural network-based model found in the literature. The developed correlations may be used as quick checks on solutions developed by deterministic analyses.     

On the Correlation of Rheology and Morphology of Bimodal Polypropylene Reactor Blends Synthesized by Homogeneous Binary Metallocene/Metallocene Catalysts

In this study, morphological and rheological characteristics of bimodal polypropylene reactor blends synthesized by binary catalysts based on I: rac-Me₂Si(2-Me-4-PhInd)₂ZrCl₂ and II: (2-PhInd)₂ZrCl₂ at different molar ratios were investigated. Gel permeation chromatography, scanning electron microscopy, and rheometry analysis were performed to evaluate the effect of molar ratio of catalyst II, responsible for the formation of elastomeric stereoblock polypropylene with low molecular weight, to catalyst I, responsible for production of high molecular weight isotactic (i) polypropylene, on the molecular weight, molecular weight distribution, morphological characteristics and rheological behavior of the synthesized products. The gel permeation chromatography results indicated that once a hybrid of the two catalysts is used, a broad and bimodal molecular weight distribution would be obtained, and the molar ratio of the catalysts governs the values of molecular weight and molecular weight distribution. ¹³C NMR results suggest that the different polypropylene tacticity resulting from the two catalysts (stereoblock vs. isotactic) is hardly influenced using a binary system. The effect of molecular weight enhancement and molecular weight distribution broadening was confirmed through the linear rheological data (G′ at lower frequencies, crossover modulus and crossover frequency) due to the impeded molecular motions of chains with high molecular weights which play an important role in the elasticity of chains. The zero shear rate viscosity and relaxation time, determined by fitting the Carreau–Yasuda model, are in great conformity with the experimental data at low-frequency region. Likewise, the miscibility and increased level of heterogeneity of microstructure, which is a result of changing the molar ratios of catalysts II/I, are confirmed through the Cole–Cole and Han plots and were further corroborated through the obtained scanning electron microscopy results.     

Performance of a photo‐impinging streams reactor for the phenol degradation process

BACKGROUND: Photocatalysis is one of the advanced oxidation processes that has gained in importance over recent years owing to its ability to decompose a wide range of organic and inorganic pollutants at ambient temperature and pressure. However, there are two essential issues regarding photocatalytic processes, i.e. limitations on photon transfer and on mass transfer. In the present study, a novel photo‐impinging streams reactor, which can minimize such limitations, has been utilized in the photocatalytic degradation of phenol. The design and operating parameters such as type of nozzle, flow rate, catalyst loading, pH, initial phenol concentration and light intensity were found to have the expected impact on the efficiency of the process. The effects of two different co‐oxidants, H₂O₂ and Na₂S₂O₈ on the photocatalysis were also examined. RESULTS: Results indicated that 100 mg L^?1 of phenol in a 750 cm³ solution was completely degraded within 2.5 h reaction time in the presence of TiO₂ without a co‐oxidant present; and within 1 h in the presence of a co‐oxidant. CONCLUSION: A comparison between the current data and those available in the literature revealed higher efficiency and increased performance of the present reactor relative to conventional apparatus. Copyright © 2010 Society of Chemical Industry     

Applications of FT-NIRS combined with PLS multivariate methods for the detection & quantification of saccharin adulteration in commercial fruit juices

Detection of adulteration in carbohydrate-rich foods like fruit juices is particularly difficult because of the variety of the commercial sweeteners available that match the concentration profiles of the major carbohydrates in the foods. In present study, a new sensitive and robust assay using Fourier Transform Near-Infrared Spectroscopy (FT-NIRS) combined with partial least square (PLS) multivariate methods has been developed for detection and quantification of saccharin adulteration in different commercial fruit juice samples. For this investigation, six different commercially available fruit juice samples were intentionally adulterated with saccharin at the following percentage levels: 0%, 0.10%, 0.30%, 0.50%, 0.70%, 0.90%, 1.10%, 1.30%, 1.50%, 1.70% and 2.00% (weight/volume). Altogether, 198 samples were used including 18 pure juice samples (unadulterated) and 180 juice samples adulterated with saccharin. PLS multivariate methods including partial least-squares discriminant analysis (PLS-DA) and partial least-squares regressions (PLSR) were applied to the obtained spectral data to build models. The PLS-DA model was employed to differentiate between pure fruit juice samples and those adulterated with saccharin. The R² value obtained for the PLS-DA model was 97.90% with an RMSE error of 0.67%. Similarly, a PLS regression model was also developed to quantify the amount of saccharin adulterant in juice samples. The R² value obtained for the PLSR model was 97.04% with RMSECV error of 0.88%. The employed model was then cross-validated by using a test set which included 30% of the total adulterated juice samples. The excellent performance of the model was proved by the low root mean squared error of prediction value of 0.92% and the high correlation factor of 0.97. This newly developed method is robust, nondestructive, highly sensitive and economical.