Characterizations and activities of the nano-sized Ni/Al2O3 and Ni/La-Al2O3 catalysts for NH3 decomposition

A series of nano-sized Ni/Al2O3 and Ni/La-Al2O3 catalysts that possess high activities for NH3 decomposition have been successfully synthesized by a coprecipitation method. The catalytic performance was investigated under the atmospheric conditions and a significant enhancement in the activity after the introduction of La was observed. Aiming to study the influence of La promoter on the physicochemical properties, we characterized the catalysts by N-2 adsorption/desorption, XRD, H-2-TPR, chemisorption and TEM techniques. Physisorption results suggested a high specific surface area and XRD spectra showed that nickel particles are in a highly dispersed state. A combination of XRD, TEM and chemisorption showed that Ni-0 particles with the average size lower, than 5.0 nm are always obtained even though the Ni loading ranged widely from 4 to 63 %. Compared with the Ni/Al2O3 catalysts, the Ni/La-Al2O3 ones with an appropriate amount of promoter enjoy a more open mesoporous structure and higher dispersion of Ni. Reduction kinetic studies of prepared catalysts were investigated by temperature-programmed reduction (TPR) method and the fact that La additive partially destroyed the metastable Ni-Al mixed oxide phase was detailed. (c) 2005 Elsevier B.V. All rights reserved.

Microcalorimetric studies of the iridium catalyst for hydrazine decomposition reaction

Microcalorimetric studies of H-2, NH3 and O-2 adsorption, as well as the NH3 decomposition activities evaluation were used to characterize the iridium catalysts for hydrazine decomposition with different supports (Al2O3, SiO,) and iridium contents (1.8, 10.8 and 22.1%). The higher H-2 chemisorption amounts on Ir/Al2O3 catalysts than those on the corresponding Ir/SiO2 counterparts revealed that the strong interaction of iridium and Al2O3 led to higher dispersion of iridium on Ir/Al2O3 catalysts than on Ir/SiO2 catalysts. The larger increase in strong H-2 adsorption sites on highly loaded Ir/Al2O3 than the corresponding Ir/SiO2 ones could be attributed to the interaction not only between iridium atoms but also between iridium and Al2O3. The microcalorimetric results for NH3 adsorption showed that no apparent chemisorption of NH3 existed on Ir/SiO2 catalysts while NH3 chemisorption amounts increased on Ir/Al2O3 catalysts with iridium loadings, which arose from the interaction of the catalysts support of Al2O3 With chloride anion. Both highly dispersed iridium active sites and chloride anion on Ir/Al2O3 catalysts could be beneficial to the intermediate NH3 decomposition in N2H4 decomposition. The similar O-2 plots of differential heat versus normalized coverage on Ir/Al2O3 and Ir/SiO2 catalysts could not be due to the metal-support interaction, but to the formation of strong Ir-O bond. (C) 2005 Elsevier B.V. All rights reserved.

Neonatal EEG classification using atomic decomposition

The electroencephalogram (EEG) is an important noninvasive tool used in the neonatal intensive care unit (NICU) for the neurologic evaluation of the sick newborn infant. It provides an excellent assessment of at-risk newborns and formulates a prognosis for long-term neurologic outcome.The automated analysis of neonatal EEG data in the NICU can provide valuable information to the clinician facilitating medical intervention. The aim of this thesis is to develop a system for automatic classification of neonatal EEG which can be mainly divided into two parts: (1) classification of neonatal EEG seizure from nonseizure, and (2) classifying neonatal background EEG into several grades based on the severity of the injury using atomic decomposition. Atomic decomposition techniques use redundant time-frequency dictionaries for sparse signal representations or approximations. The first novel contribution of this thesis is the development of a novel time-frequency dictionary coherent with the neonatal EEG seizure states. This dictionary was able to track the time-varying nature of the EEG signal. It was shown that by using atomic decomposition and the proposed novel dictionary, the neonatal EEG transition from nonseizure to seizure states could be detected efficiently. The second novel contribution of this thesis is the development of a neonatal seizure detection algorithm using several time-frequency features from the proposed novel dictionary. It was shown that the time-frequency features obtained from the atoms in the novel dictionary improved the seizure detection accuracy when compared to that obtained from the raw EEG signal. With the assistance of a supervised multiclass SVM classifier and several timefrequency features, several methods to automatically grade EEG were explored. In summary, the novel techniques proposed in this thesis contribute to the application of advanced signal processing techniques for automatic assessment of neonatal EEG recordings.

The Effect of Wood Burial and Submersion on Decomposition: Implications for Reducing Carbon Emissions

Gemstone Team Carbon Sinks

A domain decomposition algorithm for viscous/inviscid coupling

In fluid mechanics, it is well accepted that the Euler equation is one of the reduced forms of the Navier-Stokes equation by truncating the viscous effect. There are other truncation techniques currently being used in order to truncate the Navier-Stokes equation to a reduced form. This paper describes one such technique, suitable for adaptive domain decomposition methods for the solution of viscous flow problems. The physical domain of a viscous flow problem is partitioned into viscous and inviscid subdomains without overlapping regions, and the technique is embedded into a finite volume method. Some numerical results are provided for a flat plate and the NACA0012 aerofoil. Issues related to distributed computing are discussed.

A defect equation approach for the coupling of subdomains in domain decomposition methods

A defect equation for the coupling of nonlinear subproblems defined in nonoverlapped subdomains arise in domain decomposition methods is presented. Numerical solutions of defect equations by means of quasi-Newton methods are considered.

Domain decomposition using a 2-level correction scheme

The PHYSICA software was developed to enable multiphysics modelling allowing for interaction between Computational Fluid Dynamics (CFD) and Computational Solid Mechanics (CSM) and Computational Aeroacoustics (CAA). PHYSICA uses the finite volume method with 3-D unstructured meshes to enable the modelling of complex geometries. Many engineering applications involve significant computational time which needs to be reduced by means of a faster solution method or parallel and high performance algorithms. It is well known that multigrid methods serve as a fast iterative scheme for linear and nonlinear diffusion problems. This papers attempts to address two major issues of this iterative solver, including parallelisation of multigrid methods and their applications to time dependent multiscale problems.

Feller transition functions, Resolvent Decomposition Theorems, and their application in unstable denumerable Markov processes

This paper surveys the recent progresses made in the field of unstable denumerable Markov processes. Emphases are laid upon methodology and applications. The important tools of Feller transition functions and Resolvent Decomposition Theorems are highlighted. Their applications particularly in unstable denumerable Markov processes with a single instantaneous state and Markov branching processes are illustrated.