carbon materials2 through their unique combination of excellent processability and high carbon yield. The enediyne functionality of the monomers undergo a thermal Bergman cycloaromatization reaction that yields reactive naphthalene diradicals which polymerize to form polynapthalene.(Figure 1) The tetrafunctionality of the monomers allows for both a higher processing window due to extensive branching and ultimately the formation of network polymers. The high carbon yield results in less shrinkage of the polymer upon pyrolysis to the glassy carbon state. This allows for the faithful templating of carbon structures from a polymeric precursor.

Hydrogen fuel cell electrodes require several properties for optimum performance. An ideal electrode would have as high a surface area as possible with an uniform dispersion of nano-scale catalyst particles attached to the surface. The electrode must be electrically conductive and have good mass transport for products and reactants. Carbon supported platinum is the best known catalyst for the oxidation of hydrogen at the anode and the reduction of oxygen at the cathode of a proton exchange membrane fuel cell (PEMFC) 3. The material also must have good compatibility with the material used for the proton exchange membrane in the membrane electrode assembly (MEA), usually a sulfonated fluoropolymer such as Nafion. We have undertaken a study to prepare a high surface area carbon material through a BODA templating method which can then be functionalized with both well dispersed platinum nanoparticles …

Abstract

The turbine of an automotive turbocharger is essentially one acoustic element in the exhaust system which lies between the primary noise source, the gas pulsations through the exhaust valves, and the primary noise radiation element, the exhaust tailpipe orifice. As such, like every other acoustic element of the exhaust system, it has a passive effect on the propagation of the primary exhaust noise. Thus if a comprehensive model of the acoustic propagation through the entire exhaust system of a turbocharged engine is sought, an acoustic model of the turbine is a prerequisite.

This paper presents a preliminary attempt to create such a model. The model is a purely fluid mechanic one, without recourse to any empiricism such as a turbine map. The nonlinear equations of the fluid flow are developed and solved for steady flow, to determine the mean convective flow effects upon the noise. The full time-domain equations are then linearised and solved for a single frequency of sound.

Results are given from both the steady flow and the acoustic analyses. The latter are presented in terms of both transmission loss and four-pole parameters. The model is found to give a rational representation of the passive effect of a turbine rotor.

Abstract

This paper presents a one-dimensional acoustic model for prediction of the frequencies of

self-excited oscillation and acoustic mode shapes in combustion systems. The impedance of

the combustion system is represented in terms of a frequency response function (FRF).

Impedances of the settling and combustion chambers are predicted by using the acoustic

model, taking into account the temperature distribution in the combustion chamber. Reasonably

good agreement between measured and predicted acoustic resonance frequencies and

mode shapes was achieved. Some data on stability regimes are discussed.

# 2003 Elsevier Science Ltd. All rights reserved.

Keywords: Combustion; Instability; Eigen-frequencies; Prediction; Measurement

Abstract

Experimental investigations have been carried out to measure axial effective thermal conductivities of

packed beds for a number of particles and catalyst pellets. Measurements were made for three gases (air,

nitrogen and carbon dioxide) in beds packed with ball bearings, copper chromite, chromia alumina, alumina

hollow cylinders and alumina spheres. A glass vacuum vessel was employed for most measurements,

but a thin wall stainless steel vessel was used in a few experiments.

Empirical correlations to predict the axial effective thermal conductivity of packed bed reactors have

been derived from the experimental results.

2002 Elsevier Science Ltd. All rights reserved.

Keywords: Axial thermal conductivities; Packed beds

The preparation and characterization of a cobalt substituted ETS-10 titanosilicate are described. X-ray diffraction shows that cobalt incorporation causes an increase in unit cell dimensions. UV–VIS, EPR, Raman and Co K-edge XANES spectra all show that Co2+ occupies tetrahedral sites, substituting for silicon. The 29Si NMR spectra do not permit identification of which silicon sites in ETS-10 are substituted, but the Co K-edge EXAFS shows clearly that Co2+ substitutes at Si(3Si,1Ti) sites.

A review is given of recent work in the authors' laboratory on the characterization of different forms of nanostructured titania. It is shown that nanocrystalline anatase powders and nanocrystalline anatase thin films differ significantly in their optical properties, due primarily to differences in sintering behaviour on drying. It is argued that the electronic properties of these systems are determined by surface phenomena rather than quantum size effects. The novel titanosilicate zeolite ETS-10 which contains one dimensional “quantum wires” of titania provides an alternative system for studying quantum size effects which has considerable potential for photocatalysis.

This paper presents empirical methods for enhancing the accuracy of inductive learning systems. It

addresses the problems of: learning propositional production rules in multi-class classification tasks in

noisy domains, maintaining continuous learning when confronted with new situations after the learning

phase is completed, and classifying an object when no rule is satisfied for it.

It is shown that interleaving the learning and performance-evaluation processes, allows accurate

classifications to be made on real-world data sets. The paper presents the system ARIS which

implements this approach, and it is shown that the resulting classifications are often more accurate than

those made by the non-refined knowledge bases.

The core design decision that lies behind ARIS is that it employs an ordering of the rules according to

their weight. A rule’s weight is learned by using Bayes’ theorem to calculate weights for the rule’s

conditions and to combine them. This model focuses the analysis of the knowledge base and assists the

refinement process significantly.

The system is non-interactive, it relies on heuristics to focus the refinement on those experiments that

appear to be most consistent with the refinement data set. The design framework of ARIS consists of a

tabular model for expressing rule weights, and the relationship between refinement cases and the rules

satisfied for each case to focus the refinement process. The system has been used to refine knowledge

bases created by ARIS itself, as well as to refine knowledge bases created by the RIPPER and C4.5

systems [6,25] in ten selected domains. Two main advantages have been observed. First, the ability to

gradually improve the knowledge base as the refinement proceeds. Second, is the ability to learn strong

rules utilising condition’s weight using minimum covering algorithm. Thus, by taking account of this

information we improve the applicability and quality of refinement