Different methods of manufacturing FE-based oxygen carrier particles for reforming via chemical looping, and their effect on performance

Chemical looping combustion (CLC) is a means of combusting carbonaceous fuels, which inherently separates the greenhouse gas carbon dioxide from the remaining combustion products, and has the potential to be used for the production of high-purity hydrogen. Iron-based oxygen carriers for CLC have been subject to considerable work; however, there are issues regarding the lifespan of iron-based oxygen carriers over repeated cycles. In this work, haematite (Fe2O3) was reduced in an N2+CO+CO2 mixture within a fluidised bed at 850°C, and oxidised back to magnetite (Fe3O4) in a H2O+N2 mixture, with the subsequent yield of hydrogen during oxidation being of interest. Subsequent cycles started from Fe3O4 and two transition regimes were studied; Fe3O4↔Fe0.947O and Fe 3O4↔Fe. Particles were produced by mechanical mixing and co-precipitation. In the case of co-precipitated particles, Al was added such that the ratio of Fe:Al by weight was 9:1, and the final pH of the particles during precipitation was investigated for its subsequent effect on reactivity. This paper shows that co-precipitated particles containing additives such as Al may be able to achieve consistently high H2 yields when cycling between Fe3O4 and Fe, and that these yields are a function of the ratio of [CO2] to [CO] during reduction, where thermodynamic arguments suggest that the yield should be independent of this ratio. A striking feature with our materials was that particles made by mechanical mixing performed much better than those made by co-precipitation when cycling between Fe3O4 and Fe0.947O, but much worse than co-precipitated particles when cycling between Fe3O 4 and Fe.

Modelling within-host spatiotemporal dynamics of invasive bacterial disease

Mechanistic determinants of bacterial growth, death, and spread within mammalian hosts cannot be fully resolved studying a single bacterial population. They are also currently poorly understood. Here, we report on the application of sophisticated experimental approaches to map spatiotemporal population dynamics of bacteria during an infection. We analyzed heterogeneous traits of simultaneous infections with tagged Salmonella enterica populations (wild-type isogenic tagged strains [WITS]) in wild-type and gene-targeted mice. WITS are phenotypically identical but can be distinguished and enumerated by quantitative PCR, making it possible, using probabilistic models, to estimate bacterial death rate based on the disappearance of strains through time. This multidisciplinary approach allowed us to establish the timing, relative occurrence, and immune control of key infection parameters in a true host-pathogen combination. Our analyses support a model in which shortly after infection, concomitant death and rapid bacterial replication lead to the establishment of independent bacterial subpopulations in different organs, a process controlled by host antimicrobial mechanisms. Later, decreased microbial mortality leads to an exponential increase in the number of bacteria that spread locally, with subsequent mixing of bacteria between organs via bacteraemia and further stochastic selection. This approach provides us with an unprecedented outlook on the pathogenesis of S. enterica infections, illustrating the complex spatial and stochastic effects that drive an infectious disease. The application of the novel method that we present in appropriate and diverse host-pathogen combinations, together with modelling of the data that result, will facilitate a comprehensive view of the spatial and stochastic nature of within-host dynamics. © 2008 Grant et al.

Bacterial growth rate and host factors as determinants of intracellular bacterial distributions in systemic Salmonella enterica infections.

Bacteria of the species Salmonella enterica cause a range of life-threatening diseases in humans and animals worldwide. The within-host quantitative, spatial, and temporal dynamics of S. enterica interactions are key to understanding how immunity acts on these infections and how bacteria evade immune surveillance. In this study, we test hypotheses generated from mathematical models of in vivo dynamics of Salmonella infections with experimental observation of bacteria at the single-cell level in infected mouse organs to improve our understanding of the dynamic interactions between host and bacterial mechanisms that determine net growth rates of S. enterica within the host. We show that both bacterial and host factors determine the numerical distributions of bacteria within host cells and thus the level of dispersiveness of the infection.

Probing biomolecular interaction forces using an anharmonic acoustic technique for selective detection of bacterial spores.

Receptor-based detection of pathogens often suffers from non-specific interactions, and as most detection techniques cannot distinguish between affinities of interactions, false positive responses remain a plaguing reality. Here, we report an anharmonic acoustic based method of detection that addresses the inherent weakness of current ligand dependant assays. Spores of Bacillus subtilis (Bacillus anthracis simulant) were immobilized on a thickness-shear mode AT-cut quartz crystal functionalized with anti-spore antibody and the sensor was driven by a pure sinusoidal oscillation at increasing amplitude. Biomolecular interaction forces between the coupled spores and the accelerating surface caused a nonlinear modulation of the acoustic response of the crystal. In particular, the deviation in the third harmonic of the transduced electrical response versus oscillation amplitude of the sensor (signal) was found to be significant. Signals from the specifically-bound spores were clearly distinguishable in shape from those of the physisorbed streptavidin-coated polystyrene microbeads. The analytical model presented here enables estimation of the biomolecular interaction forces from the measured response. Thus, probing biomolecular interaction forces using the described technique can quantitatively detect pathogens and distinguish specific from non-specific interactions, with potential applicability to rapid point-of-care detection. This also serves as a potential tool for rapid force-spectroscopy, affinity-based biomolecular screening and mapping of molecular interaction networks.