Development of a heterogeneous catalyst for lignocellulosic biomass conversion:Glucose dehydration by metal chlorides in a silica-supported ionic liquid layer

An attempt is made to immobilize the homogeneous metal chloride/EMIMCl catalyst for glucose dehydration to 5-hydroxymethylfurfural. To this end, ionic liquid fragments were grafted to the surface of SBA-15 to generate a heterogenized mimick of the homogeneous reaction medium. Despite a decrease in the surface area, the ordered mesoporous structure of SBA-15 was largely retained. Metal chlorides dispersed in such ionic liquid film are able to convert glucose to HMF with much higher yields as is possible in the aqueous phase. The reactivity order CrCl > AlCl > CuCl > FeCl is similar to the order in the ionic liquid solvent, yet the selectivity are lower. The HMF yield of the most promising CrCl-Im-SBA-15 can be improved by using a HO:DMSO mixture as the reaction medium and a 2-butanol/MIBK extraction layer. Different attempts to decrease metal chloride leaching by using different solvents are described. © 2013 American Institute of Chemical Engineers Environ Prog.

The ParaPhrase Project:Parallel patterns for adaptive heterogeneous multicore systems

This paper describes the ParaPhrase project, a new 3-year targeted research project funded under EU Framework 7 Objective 3.4 (Computer Systems), starting in October 2011. ParaPhrase aims to follow a new approach to introducing parallelism using advanced refactoring techniques coupled with high-level parallel design patterns. The refactoring approach will use these design patterns to restructure programs defined as networks of software components into other forms that are more suited to parallel execution. The programmer will be aided by high-level cost information that will be integrated into the refactoring tools. The implementation of these patterns will then use a well-understood algorithmic skeleton approach to achieve good parallelism. A key ParaPhrase design goal is that parallel components are intended to match heterogeneous architectures, defined in terms of CPU/GPU combinations, for example. In order to achieve this, the ParaPhrase approach will map components at link time to the available hardware, and will then re-map them during program execution, taking account of multiple applications, changes in hardware resource availability, the desire to reduce communication costs etc. In this way, we aim to develop a new approach to programming that will be able to produce software that can adapt to dynamic changes in the system environment. Moreover, by using a strong component basis for parallelism, we can achieve potentially significant gains in terms of reducing sharing at a high level of abstraction, and so in reducing or even eliminating the costs that are usually associated with cache management, locking, and synchronisation. © 2013 Springer-Verlag Berlin Heidelberg.

Understanding the Optimal Adsorption Energies for Catalyst Screening in Heterogeneous Catalysis

The fundamental understanding of the activity in heterogeneous catalysis has long been the major subject in chemistry. This paper shows the development of a two-step model to understand this activity. Using the theory of chemical potential kinetics with Bronsted-Evans-Polanyi relations, the general adsorption energy window is determined from volcano curves, using which the best catalysts can be searched. Significant insights into the reasons for catalytic activity are obtained.

Application of heterogeneous catalysts prepared by mechanochemical synthesis

Mechanochemical synthesis has the potential to provide more sustainable preparative routes to catalysts than the current multistep solvent-based routes. In this review, the mechanochemical synthesis of catalysts is discussed, with emphasis placed on catalysts for environmental, energy and chemical synthesis applications. This includes the formation of mixed-metal oxides as well as the process of dispersing metals onto solid supports. In most cases the process involves no solvent. Encouragingly, there are several examples where the process is advantageous compared with the more normal solvent-based methods. This can be because of process cost or simplicity, or, notably, where it provides more active/selective catalysts than those made by conventional wet chemical methods. The need for greater, and more systematic, exploration of this currently unconventional approach to catalyst synthesis is highlighted.

Coupling ground and airborne geophysical data with upscaling techniques for regional groundwater modeling of heterogeneous aquifers: Case study of a sedimentary aquifer intruded by volcanic dykes in Northern Ireland

In highly heterogeneous aquifer systems, conceptualization of regional groundwater flow models frequently results in the generalization or negligence of aquifer heterogeneities, both of which may result in erroneous model outputs. The calculation of equivalence related to hydrogeological parameters and applied to upscaling provides a means of accounting for measurement scale information but at regional scale. In this study, the Permo-Triassic Lagan Valley strategic aquifer in Northern Ireland is observed to be heterogeneous, if not discontinuous, due to subvertical trending low-permeability Tertiary dolerite dykes. Interpretation of ground and aerial magnetic surveys produces a deterministic solution to dyke locations. By measuring relative permeabilities of both the dykes and the sedimentary host rock, equivalent directional permeabilities, that determine anisotropy calculated as a function of dyke density, are obtained. This provides parameters for larger scale equivalent blocks, which can be directly imported to numerical groundwater flow models. Different conceptual models with different degrees of upscaling are numerically tested and results compared to regional flow observations. Simulation results show that the upscaled permeabilities from geophysical data allow one to properly account for the observed spatial variations of groundwater flow, without requiring artificial distribution of aquifer properties. It is also found that an intermediate degree of upscaling, between accounting for mapped field-scale dykes and accounting for one regional anisotropy value (maximum upscaling) provides results the closest to the observations at the regional scale.

SHEPARD: Scheduling on heterogeneous platforms using application resource demands

Heterogeneous computing technologies, such as multi-core CPUs, GPUs and FPGAs can provide significant performance improvements. However, developing applications for these technologies often results in coupling applications to specific devices, typically through the use of proprietary tools. This paper presents SHEPARD, a compile time and run-time framework that decouples application development from the target platform and enables run-time allocation of tasks to heterogeneous computing devices. Through the use of special annotated functions, called managed tasks, SHEPARD approximates a task's performance on available devices, and coupled with the approximation of current device demand, decides which device can satisfy the task with the lowest overall execution time. Experiments using a task parallel application, based on an in-memory database, demonstrate the opportunity for automatic run-time task allocation to achieve speed-up over a static allocation to a single specific device. © 2014 IEEE.

Power Modeling and Capping for Heterogeneous ARM/FPGA SoCs

Low-power processors and accelerators that were originally designed for the embedded systems market are emerging as building blocks for servers. Power capping has been actively explored as a technique to reduce the energy footprint of high-performance processors. The opportunities and limitations of power capping on the new low-power processor and accelerator ecosystem are less understood. This paper presents an efficient power capping and management infrastructure for heterogeneous SoCs based on hybrid ARM/FPGA designs. The infrastructure coordinates dynamic voltage and frequency scaling with task allocation on a customised Linux system for the Xilinx Zynq SoC. We present a compiler-assisted power model to guide voltage and frequency scaling, in conjunction with workload allocation between the ARM cores and the FPGA, under given power caps. The model achieves less than 5% estimation bias to mean power consumption. In an FFT case study, the proposed power capping schemes achieve on average 97.5% of the performance of the optimal execution and match the optimal execution in 87.5% of the cases, while always meeting power constraints.

Stochastic Analysis of Saltwater Intrusion in Heterogeneous Aquifers using Local Average Subdivision

This study investigates the effects of ground heterogeneity, considering permeability as a random variable, on an intruding SW wedge using Monte Carlo simulations. Random permeability fields were generated, using the method of Local Average Subdivision (LAS), based on a lognormal probability density function. The LAS method allows the creation of spatially correlated random fields, generated using coefficients of variation (COV) and horizontal and vertical scales of fluctuation (SOF). The numerical modelling code SUTRA was employed to solve the coupled flow and transport problem. The well-defined 2D dispersive Henry problem was used as the test case for the method. The intruding SW wedge is defined by two key parameters, the toe penetration length (TL) and the width of mixing zone (WMZ). These parameters were compared to the results of a homogeneous case simulated using effective permeability values. The simulation results revealed: (1) an increase in COV resulted in a seaward movement of TL; (2) the WMZ extended with increasing COV; (3) a general increase in horizontal and vertical SOF produced a seaward movement of TL, with the WMZ increasing slightly; (4) as the anisotropic ratio increased the TL intruded further inland and the WMZ reduced in size. The results show that for large values of COV, effective permeability parameters are inadequate at reproducing the effects of heterogeneity on SW intrusion.

Experimental Investigation of Transient Saltwater Intrusion in Heterogeneous Porous Media

A 2D sandbox style experiment was developed to compare the results of numerical modelling to physical testing for saltwater intrusion in homogeneous and heterogeneous aquifers. The sandbox consisted of a thin central viewing chamber filled with glass beads of varying diameters (780μm, 1090μm and 1325μm) under fully saturated conditions. Dyed saltwater (SW) was introduced at the side boundary and a head difference imposed across the porous media. Images of the SW wedge were recorded at intervals in order to assess the suitability of the numerical models predictions of transient SW intrusion. Numerical modelling of the experimental cases were simulated using SUTRA. Two main parameters were chosen to express the condition of the intruding SW wedge at each recorded time step; the toe penetration length (TL) and the width of the mixing zone (WMZ). The WMZ was larger under transient conditions in the heterogeneous case, while the TL was longer for the homogeneous case. The increased variability in the flow field fo the heterogeneous case resulted in increased dispersion, and thus, increased WMZ.

An Intelligent Threat Prevention Framework with Heterogeneous Information

Three issues usually are associated with threat prevention intelligent surveillance systems. First, the fusion and interpretation of large scale incomplete heterogeneous information; second, the demand of effectively predicting suspects’ intention and ranking the potential threats posed by each suspect; third, strategies of allocating limited security resources (e.g., the dispatch of security team) to prevent a suspect’s further actions towards critical assets. However, in the literature, these three issues are seldomly considered together in a sensor network based intelligent surveillance framework. To address
this problem, in this paper, we propose a multi-level decision support framework for in-time reaction in intelligent surveillance. More specifically, based on a multi-criteria event modeling framework, we design a method to predict the most plausible intention of a suspect. Following this, a decision support model is proposed to rank each suspect based on their threat severity and to determine resource allocation strategies. Finally, formal properties are discussed to justify our framework.