Iron(III) Porphyrin Covalently Supported onto Magnetic Amino-Functionalized Nanospheres as Catalyst for Hydrocarbon and Herbicide Oxidations

This work describes the covalent immobilization of an ironporphyrin, 5,10,15,20-tetrakis(pentafluorophenyl)porphyrin iron(III) chloride (FeTFPP), onto maghemite/silica magnetic nanospheres covered with aminofunctionalized silica. The resulting material (gamma-Fe2O3/SiO2-NHFeP) was characterized by diffuse reflectance infrared spectroscopy (DRIFTS) and UV-Vis absorption spectroscopy. The catalytic activity of this magnetic ironporphyrin was investigated in the oxidation of hydrocarbons (styrene, (Z)-cyclooctene and R-(+)-limonene) and an herbicide (simazine) by hydrogen peroxide or 3-chloroperoxybenzoic acid. Hydrocarbon and simazine oxidation reaction products were analyzed by gas chromatography (GC) and high performance liquid chromatography (HPLC), respectively. This catalytic system proved to be efficient and selective for hydrocarbon oxidation, leading to high product yields from styrene (89%), cyclooctene (71%) and R-(+) -limonene (86%). Simazine oxidation was attained with 100% selectivity for a dechlorinated product (OEAT), while several oxidation products were obtained for the same catalyst in homogeneous media. The catalyst can be easily recovered through application of an external magnetic field and washed after reaction. Catalyst reuse experiments for R-(+)-limonene oxidation have shown that the catalytic activity is kept at 90% after 10 consecutive reactions.

Strontium zirconate heterogeneous catalyst for biodiesel production: Synthesis, characterization and catalytic activity evaluation

Strontium zirconate oxide was synthesized by co-precipitation and the citrate route and was evaluated as a heterogeneous catalyst for biodiesel production. The catalyst samples were characterized by XRD, FTIR, and TG, and catalytic activity was measured based on the ester content of the biodiesel produced that was quantified by GC. The co-precipitate samples were obtained in alkaline pH and had a mixture of the perovskite and pure strontium and zirconium oxide phases. Ester conversion using these samples was approximately 1.6%, indicating no catalytic activity. The citrate route was more efficient in producing perovskite when carried out at pH 7-8; excess SrCO3 was found on the catalyst surface due to CO2 adsorption, thus demonstrating no catalytic activity. The same synthesis carried out at pH 2 resulted in free OH- groups, with a small amount of the carbonate species that produced ester yield values of 98%. Therefore, matrices based on strontium zirconate produced via the citrate route in acidic media are potential heterogeneous catalysts for transesterification. (C) 2012 Elsevier B.V. All rights reserved.

Iron(III) porphyrin covalently supported onto magnetic amino-functionalized nanospheres as catalyst for hydrocarbon and herbicide oxidations

This work describes the covalent immobilization of an ironporphyrin, 5,10,15,20- tetrakis(pentafluorophenyl)porphyrin iron(III) chloride (FeTFPP), onto maghemite/silica magnetic nanospheres covered with aminofunctionalized silica. The resulting material (γ-Fe2O3/SiO2-NHFeP) was characterized by diffuse reflectance infrared spectroscopy (DRIFTS) and UV-Vis absorption spectroscopy. The catalytic activity of this magnetic ironporphyrin was investigated in the oxidation of hydrocarbons (styrene, (Z)-cyclooctene and R-(+)-limonene) and an herbicide (simazine) by hydrogen peroxide or 3-chloroperoxybenzoic acid. Hydrocarbon and simazine oxidation reaction products were analyzed by gas chromatography (GC) and high performance liquid chromatography (HPLC), respectively. This catalytic system proved to be efficient and selective for hydrocarbon oxidation, leading to high product yields from styrene (89%), cyclooctene (71%) and R-(+)-limonene (86%). Simazine oxidation was attained with 100% selectivity for a dechlorinated product (OEAT), while several oxidation products were obtained for the same catalyst in homogeneous media. The catalyst can be easily recovered through application of an external magnetic field and washed after reaction. Catalyst reuse experiments for R-(+)-limonene oxidation have shown that the catalytic activity is kept at 90% after 10 consecutive reactions.

Efficient Kernel Computation for Volterra Filter Structure Evaluation

Despite their generality, conventional Volterra filters are inadequate for some applications, due to the huge number of parameters that may be needed for accurate modelling. When a state-space model of the target system is known, this can be assessed by computing its kernels, which also provides valuable information for choosing an adequate alternate Volterra filter structure, if necessary, and is useful for validating parameter estimation procedures. In this letter, we derive expressions for the kernels by using the Carleman bilinearization method, for which an efficient algorithm is given. Simulation results are presented, which confirm the usefulness of the proposed approach.

Efficient Forest Data Structure for Evolutionary Algorithms Applied to Network Design

The design of a network is a solution to several engineering and science problems. Several network design problems are known to be NP-hard, and population-based metaheuristics like evolutionary algorithms (EAs) have been largely investigated for such problems. Such optimization methods simultaneously generate a large number of potential solutions to investigate the search space in breadth and, consequently, to avoid local optima. Obtaining a potential solution usually involves the construction and maintenance of several spanning trees, or more generally, spanning forests. To efficiently explore the search space, special data structures have been developed to provide operations that manipulate a set of spanning trees (population). For a tree with n nodes, the most efficient data structures available in the literature require time O(n) to generate a new spanning tree that modifies an existing one and to store the new solution. We propose a new data structure, called node-depth-degree representation (NDDR), and we demonstrate that using this encoding, generating a new spanning forest requires average time O(root n). Experiments with an EA based on NDDR applied to large-scale instances of the degree-constrained minimum spanning tree problem have shown that the implementation adds small constants and lower order terms to the theoretical bound.