Heterogeneous permanganate oxidations: Synthesis of medium ring keto-lactones via substituent directed oxidative cyclisation

Homoallyl alcohols 4a-b and 5a-b undergo smooth oxidative cyclisation to give the corresponding ring enlarged keto-lactones under heterogeneous permanganate oxidation conditions.

High-Throughput Study of the Cu(CH3COO)(2)center dot H2O-5-Nitroisophthalic Acid Heterocyclic Ligand System: Synthesis, Structure, Magnetic, and Heterogeneous Catalytic Studies of Three Copper Nitroisophthalates

A high-throughput screening was employed to identify new compounds in Cu(CH3COO)(2)center dot H2O-NIPA-heterocyclic ligand systems. Of the compounds identified, three compounds, Cu-3{(NO2)-C6H3-(COO)(2)}(3)(C3N6H6)] (1), Cu-2(mu(3)-OH)(H2O){(NO2)-C6H3-(COO)(2)}(CN4H)]center dot-(H2O) (II), and Cu-2(mu(3)-OH)(H2O){(NO2)-C6H3-(COO)(2}-)(CN5H2)]center dot 2(H2O) (III), have been isolated as good quality single crystals by employing conventional hydrothermal methods. Three other compounds, Cu-2{(NO2)-C6H3-(COO)(2)}-(CN4H)(H2O) (IIa), Cu-2{(NO2)-C6H3-(COO)(2)}(CN5H2) (IIIa), and Cu-2{(NO2)-C6H3-(COO)(2)}{(CN5H2)(2)}2H(2)O (IIIb), were identified by a combination of elemental analysis, thermogravimetric analysis (TGA), and IR spectroscopic studies, although their structures are yet to be determined. The single crystalline compounds were also characterized by elemental analysis, TGA, IR, UV vis, magnetic, and catalytic studies. The structures of the compounds have paddle wheel (I) and infinite Cu 0(H) Cu chains (II and HI) connected with NLPA and heterocyclic ligands forming two-(II) and three-dimensional (I and III) structures. The bound and lattice water molecules in 11 and 111 could be reversibly removed/inserted without affecting the structure. In the case of II, the removal of water gives rise to a structural transition, but the dehydrated phase reverts back to the original phase on prolonged exposure to atmospheric conditions. Magnetic studies indicate an overall antiferromagnetism in all of the compounds. Lewis acid catalytic studies indicate that compounds II and HI are active for cyanosilylation of imines.

meso-substituted octabromoporphyrins: Synthesis, spectroscopy, electrochemistry and electronic structure

The free-base, copper(II) and zinc(II) derivatives of 5,10,15,20-tetraarylporphyrin (aryl = phenyl, 4-methylphenyl or 4-chlorophenyl) and the corresponding brominated 2,3,7,8,12,13,17,18-octabromo-5,10,15,20-tetraarylporphyrin derivatives have been synthesized and their spectral and redox properties compared by UV/VIS, H-1 NMR, ESR and cyclic voltammetric methods. Substitution with the electron-withdrawing bromine groups at the pyrrole carbons has a profound influence on the UV/VIS and H-1 NMR spectral features and also on the redox potentials of these systems. On the other hand, electron-withdrawing chloro or electron-donating methyl groups at the para positions of the four phenyl rings have only a marginal effect on the spectra and redox potentials of both the brominated and the non-brominated derivatives. The ESR data for the copper(II) derivatives of ail these systems reveal that substitution at either the beta-pyrrole carbons and/or the para positions of the meso-phenyl groups does not significantly affect the spin-Hamiltonian parameters that describe the metal centre in each case. Collectively, these observations suggest that the highest-occupied (HOMO) and lowest-unoccupied molecular orbitals (LUMO) of the octabromoporphyrins involve the porphyrin pi-ring system as is the case with the non-brominated derivatives.-Investigations have been carried out to probe the electronic structures of these systems by three different approaches involving spectral and redox potential data as well as AMI calculations. The results obtained suggest that the electron-withdrawing beta-bromine substituents stabilize the LUMOs and, to a lesser degree, the HOMOs and that the extent of these changes can be fine-tuned, in a subtle way, by substituting at the meso-aryl rings of a given porphyrin.

Heterogeneous nucleation of nanometre-sized Bi particles embedded in a Zn matrix

It is argued that the nanometric dispersion of Bi in a Zn matrix is an ideal model system for heterogeneous nucleation experiments. The classical theory of heterogeneous nucleation with a hemispherical cap model is applied to analyse the nucleation data. It is shown that, unlike the results of earlier experiments, the derived site density for catalytic nucleation and contact angle are realistic and strongly suggest the validity of the classical theory. The surface energy between the 0001 plane of Zn and the <10(1)over bar 2> plane of Bi, which constitute the epitaxial nucleation interface, is estimated to be 39 mJ m(-2).

Oxidation of aqueous sulphur dioxide catalysed by poly-4-vinylpyridine-Cu(II) complex .2. Combined homogeneous and heterogeneous phase oxidation

Aqueous phase oxidation of sulphur dioxide at low concentrations catalysed by a PVP-Cu complex in the solid phase and dissolved Cu(II) in the liquid phase is studied in a rotating catalyst basket reactor (RCBR). The equilibrium adsorption of Cu(II) and S(VI) on PVP particles is found to be of the Langmuir-type. The diffusional effects of S(IV) species in PVP-Cu resin are found to be insignificant whereas that of product S(VI) are found to be significant. The intraparticle diffusivity of S(VI) is obtained from independent tracer experiments. In the oxidation reaction HSO3- is the reactive species. Both the S(IV) species in the solution, namely SO2(aq) and HSO3- get adsorbed onto the active PVP-Cu sites of the catalyst, but only HSO3- undergoes oxidation. A kinetic mechanism is proposed based on this feature which shows that SO2(aq) has a deactivating effect on the catalyst. A rate model is developed for the three-phase reaction system incorporating these factors along with the effect of concentration of H2SO4 on the solubility of SO2 in the dilute aqueous solutions of Cu(II). Transient oxidation experiments are conducted at different conditions of concentration of SO2 and O-2 in the gas phase and catalyst concentration, and the rate parameters are estimated from the data. The observed and calculated profiles are in very good agreement. This confirms the deactivating effect of nonreactive SO2(aq) on the heterogeneous catalysis.

Redistribution Mechanisms for Assignment of Heterogeneous Objects

There are p heterogeneous objects to be assigned to n competing agents (n > p) each with unit demand. It is required to design a Groves mechanism for this assignment problem satisfying weak budget balance, individual rationality, and minimizing the budget imbalance. This calls for designing an appropriate rebate function. When the objects are identical, this problem has been solved which we refer as WCO mechanism. We measure the performance of such mechanisms by the redistribution index. We first prove an impossibility theorem which rules out linear rebate functions with non-zero redistribution index in heterogeneous object assignment. Motivated by this theorem,we explore two approaches to get around this impossibility. In the first approach, we show that linear rebate functions with non-zero redistribution index are possible when the valuations for the objects have a certain type of relationship and we design a mechanism with linear rebate function that is worst case optimal. In the second approach, we show that rebate functions with non-zero efficiency are possible if linearity is relaxed. We extend the rebate functions of the WCO mechanism to heterogeneous objects assignment and conjecture them to be worst case optimal.

Automatic Compilation of MATLAB Programs for Synergistic Execution on Heterogeneous Processors

MATLAB is an array language, initially popular for rapid prototyping, but is now being increasingly used to develop production code for numerical and scientific applications. Typical MATLAB programs have abundant data parallelism. These programs also have control flow dominated scalar regions that have an impact on the program's execution time. Today's computer systems have tremendous computing power in the form of traditional CPU cores and throughput oriented accelerators such as graphics processing units(GPUs). Thus, an approach that maps the control flow dominated regions to the CPU and the data parallel regions to the GPU can significantly improve program performance. In this paper, we present the design and implementation of MEGHA, a compiler that automatically compiles MATLAB programs to enable synergistic execution on heterogeneous processors. Our solution is fully automated and does not require programmer input for identifying data parallel regions. We propose a set of compiler optimizations tailored for MATLAB. Our compiler identifies data parallel regions of the program and composes them into kernels. The problem of combining statements into kernels is formulated as a constrained graph clustering problem. Heuristics are presented to map identified kernels to either the CPU or GPU so that kernel execution on the CPU and the GPU happens synergistically and the amount of data transfer needed is minimized. In order to ensure required data movement for dependencies across basic blocks, we propose a data flow analysis and edge splitting strategy. Thus our compiler automatically handles composition of kernels, mapping of kernels to CPU and GPU, scheduling and insertion of required data transfer. The proposed compiler was implemented and experimental evaluation using a set of MATLAB benchmarks shows that our approach achieves a geometric mean speedup of 19.8X for data parallel benchmarks over native execution of MATLAB.

Multi-agent search using?sensors with heterogeneous capabilities

In this thesis we address the problem of multi-agent search. We formulate two deploy and search strategies based on optimal deployment of agents in search space so as to maximize the search effectiveness in a single step. We show that a variation of centroidal Voronoi configuration is the optimal deployment. When the agents have sensors with different capabilities, the problem will be heterogeneous in nature. We introduce a new concept namely, generalized Voronoi partition in order to formulate and solve the heterogeneous multi-agent search problem. We address a few theoretical issues such as optimality of deployment, convergence and spatial distributedness of the control law and the search strategies. Simulation experiments are carried out to compare performances of the proposed strategies with a few simple search strategies.

New Insights into Selective Heterogeneous Nucleation of Metal Nanoparticles on Oxides by Microwave-Assisted Reduction: Rapid Synthesis of High-Activity Supported Catalysts

Microwave-based methods are widely employed to synthesize metal nanoparticles on various substrates. However, the detailed mechanism of formation of such hybrids has not been addressed. In this paper, we describe the thermodynamic and kinetic aspects of reduction of metal salts by ethylene glycol under microwave heating conditions. On the basis of this analysis, we identify the temperatures above which the reduction of the metal salt is thermodynamically favorable and temperatures above which the rates of homogeneous nucleation of the metal and the heterogeneous nucleation of the metal on supports are favored. We delineate different conditions which favor the heterogeneous nucleation of the metal on the supports over homogeneous nucleation in the solvent medium based on the dielectric loss parameters of the solvent and the support and the metal/solvent and metal/support interfacial energies. Contrary to current understanding, we show that metal particles can be selectively formed on the substrate even under situations where the temperature of the substrate Is lower than that of the surrounding medium. The catalytic activity of the Pt/CeO(2) and Pt/TiO(2) hybrids synthesized by this method for H(2) combustion reaction shows that complete conversion is achieved at temperatures as low as 100 degrees C with Pt-CeO(2) catalyst and at 50 degrees C with Pt-TiO(2) catalyst. Our method thus opens up possibilities for rational synthesis of high-activity supported catalysts using a fast microwave-based reduction method.

Combining heterogeneous classifiers for relational databases

Practical usage of machine learning is gaining strategic importance in enterprises looking for business intelligence. However, most enterprise data is distributed in multiple relational databases with expert-designed schema. Using traditional single-table machine learning techniques over such data not only incur a computational penalty for converting to a flat form (mega-join), even the human-specified semantic information present in the relations is lost. In this paper, we present a practical, two-phase hierarchical meta-classification algorithm for relational databases with a semantic divide and conquer approach. We propose a recursive, prediction aggregation technique over heterogeneous classifiers applied on individual database tables. The proposed algorithm was evaluated on three diverse datasets. namely TPCH, PKDD and UCI benchmarks and showed considerable reduction in classification time without any loss of prediction accuracy. (C) 2012 Elsevier Ltd. All rights reserved.

Automatic compilation of MATLAB programs for synergistic execution on heterogeneous processors

MATLAB is an array language, initially popular for rapid prototyping, but is now being increasingly used to develop production code for numerical and scientific applications. Typical MATLAB programs have abundant data parallelism. These programs also have control flow dominated scalar regions that have an impact on the program's execution time. Today's computer systems have tremendous computing power in the form of traditional CPU cores and throughput oriented accelerators such as graphics processing units(GPUs). Thus, an approach that maps the control flow dominated regions to the CPU and the data parallel regions to the GPU can significantly improve program performance. In this paper, we present the design and implementation of MEGHA, a compiler that automatically compiles MATLAB programs to enable synergistic execution on heterogeneous processors. Our solution is fully automated and does not require programmer input for identifying data parallel regions. We propose a set of compiler optimizations tailored for MATLAB. Our compiler identifies data parallel regions of the program and composes them into kernels. The problem of combining statements into kernels is formulated as a constrained graph clustering problem. Heuristics are presented to map identified kernels to either the CPU or GPU so that kernel execution on the CPU and the GPU happens synergistically and the amount of data transfer needed is minimized. In order to ensure required data movement for dependencies across basic blocks, we propose a data flow analysis and edge splitting strategy. Thus our compiler automatically handles composition of kernels, mapping of kernels to CPU and GPU, scheduling and insertion of required data transfer. The proposed compiler was implemented and experimental evaluation using a set of MATLAB benchmarks shows that our approach achieves a geometric mean speedup of 19.8X for data parallel benchmarks over native execution of MATLAB.

Runtime dependence computation and execution of loops on heterogeneous systems

GPUs have been used for parallel execution of DOALL loops. However, loops with indirect array references can potentially cause cross iteration dependences which are hard to detect using existing compilation techniques. Applications with such loops cannot easily use the GPU and hence do not benefit from the tremendous compute capabilities of GPUs. In this paper, we present an algorithm to compute at runtime the cross iteration dependences in such loops. The algorithm uses both the CPU and the GPU to compute the dependences. Specifically, it effectively uses the compute capabilities of the GPU to quickly collect the memory accesses performed by the iterations by executing the slice functions generated for the indirect array accesses. Using the dependence information, the loop iterations are levelized such that each level contains independent iterations which can be executed in parallel. Another interesting aspect of the proposed solution is that it pipelines the dependence computation of the future level with the actual computation of the current level to effectively utilize the resources available in the GPU. We use NVIDIA Tesla C2070 to evaluate our implementation using benchmarks from Polybench suite and some synthetic benchmarks. Our experiments show that the proposed technique can achieve an average speedup of 6.4x on loops with a reasonable number of cross iteration dependences.

Heterogeneous locational optimisation using a generalised Voronoi partition

In this paper a generalisation of the Voronoi partition is used for locational optimisation of facilities having different service capabilities and limited range or reach. The facilities can be stationary, such as base stations in a cellular network, hospitals, schools, etc., or mobile units, such as multiple unmanned aerial vehicles, automated guided vehicles, etc., carrying sensors, or mobile units carrying relief personnel and materials. An objective function for optimal deployment of the facilities is formulated, and its critical points are determined. The locally optimal deployment is shown to be a generalised centroidal Voronoi configuration in which the facilities are located at the centroids of the corresponding generalised Voronoi cells. The problem is formulated for more general mobile facilities, and formal results on the stability, convergence and spatial distribution of the proposed control laws responsible for the motion of the agents carrying facilities, under some constraints on the agents' speed and limit on the sensor range, are provided. The theoretical results are supported with illustrative simulation results.

An electron rich porous extended framework as a heterogeneous catalyst for Diels-Alder reactions

An electron rich porous metal-organic framework (MOF) has been synthesized, which acts as an effective heterogeneous catalyst for Diels-Alder reactions through encapsulation of the reactants in confined nano-channels of the framework.