Termination of real-time programs: Definitely, definitely not, or maybe

Real-time control programs are often used in contexts where (conceptually) they run forever. Repetitions within such programs (or their specifications) may either (i) be guaranteed to terminate, (ii) be guaranteed to never terminate (loop forever), or (iii) may possibly terminate. In dealing with real-time programs and their specifications, we need to be able to represent these possibilities, and define suitable refinement orderings. A refinement ordering based on Dijkstra's weakest precondition only copes with the first alternative. Weakest liberal preconditions allow one to constrain behaviour provided the program terminates, which copes with the third alternative to some extent. However, neither of these handles the case when a program does not terminate. To handle this case a refinement ordering based on relational semantics can be used. In this paper we explore these issues and the definition of loops for real-time programs as well as corresponding refinement laws.

Scaleup of wet granulation processes: science not art

Significant advances have been made in the last decade to quantify the process of wet granulation. The attributes of product granules from the granulation process are controlled by a combination of three groups of processes occurring in the granulator: (1) wetting and nucleation, (2) growth and consolidation and (3) breakage and attrition. For the first two of these processes, the key controlling dimensionless groups are defined and regime maps are presented and validated with data from tumbling and mixer granulators. Granulation is an example of particle design. For quantitative analysis, both careful characterisation of the feed formulation and knowledge of operating parameters are required. A key thesis of this paper is that the design, scaleup and operation of granulation processes can now be considered as quantitative engineering rather than a black art. Résumé

Thermal Cycling Stability of Silica Membranes for Gas Separation

Hydrogen is being seen as an alternative energy carrier to conventional hydrocarbons to reduce greenhouse gas emissions. High efficiency separation technologies to remove hydrogen from the greenhouse gas, carbon dioxide, are therefore in growing demand. Traditional thermodynamic separation systems utilise distillation, absorption and adsorption, but are limited in efficiency at compact scales. Molecular sieve silica (MSS) membranes can perform this separation as they have high permselectivity of hydrogen to carbon dioxide, but their stability under thermal cycling is not well reported. In this work we exposed a standard MSS membrane and a carbonised template MSS (CTMSS) membrane to thermal cycling from 100 to 450°C. The standard MSS and carbonised template CTMSS membranes both showed permselectivity of helium to nitrogen dropping from around 10 to 6 in the first set of cycles, remaining stable until the last test. The permselectivity drop was due to small micropore collapse, which occurred via structure movement during cycling. Simulating single stage membrane separation with a 50:50 molar feed of H2:CO2, H2 exiting the permeate stream would start at 79% and stabilise at 67%. Higher selectivity membranes showed less of a purity drop, indicating the margin at which to design a stable membrane separation unit for CO2 capture.

Functionalisation of nanoparticles as electrolytes in fuel cells

Inorganic metal oxide materials are generally poor proton conductors as conductivities are lower than 10-5-10-6 S.cm-1. However, by functionalising Silica, Zirconia or Titania, proton conduction increases by up to 5 orders of magnitude. Hence, functionalised nanomaterials are becoming very competitive against conventional electrolyte materials such as Nafion. In this work, sol-gel processes are employed to produce silica phosphate, zirconia phosphate and titania phosphate functionalised nanoparticles. Furthermore, conductivities at hydrate conditions are investigated, and nanoparticle formation and functionalisation effects on proton conductivity are discussed. Results show conductivities up to 10-1 S.cm-1 (95% RH). Proton conduction increases with the functionalisation content, however heat treatment of nanoparticles locks the functionality in the crystal phase, thus inhibiting proton conduction. Controlling the mesopore phase allows for high proton conduction at hydrated conditions, clearly indicating facilitated ion transport through the pore channels.