Publications

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This review discusses the coordination number (CN) and the coordination geometry of the first coordination sphere of Pb(II) atoms in crystal structures of 98 lead(II) complexes with O-donor ligands and the stereochemically active lone pair of electrons (LP, E) in the terms of the valence shell electron-pair repulsion (VSEPR) model. The CN of Pb(II) atoms of the first coordination sphere has values falling into the range (3 + E) to (6 + E). The following coordination polyhedra-{psi}-tetrahedron (I), {psi}-trigonal bipyramid (II), {psi}-octahedron (III), {psi}-pentagonal bipyramid with an axial (IV) or equatorial (V) vacant position are formed. For the investigated structures of the Pb(II) complexes, the formula of each compound, the overall CN of the Pb(II) atom considered as the sum of the CN in the first coordination sphere and the number of secondary bonds, the polyhedron shape, the Pb-O bond lengths, and O-Pb-O bond angles in the first coordination sphere, secondary bond lengths, references and REFCODEs are presented in the comprehensive Tables. The quantum chemical investigations performed using density functional theory (DFT) method have confirmed the stereochemical activity of the LP of Pb(II) atoms in the studied structures of lead(II) complexes with O-donor ligands.

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Nanoparticles are now more than ever being used to tailor materials function and performance in differentiating technologies because of their profound effect on thermo-physical, mechanical and optical properties. The most feasible way to disperse particles in a bulk material or control their packing at a substrate is through fluidization in a carrier, followed by solidification through solvent evaporation/drying/curing/sintering. Unfortunately processing particles as concentrated, fluidized suspensions into useful products remains an art largely because the effect of particle shape and volume fraction on fluidic properties and suspension stability remains unexplored in a regime where particle-particle interaction mechanics is prevalent. To achieve a stronger scientific understanding of the factors that control nanoparticle dispersion and rheology we have developed a multiscale modeling approach to bridge scales between atomistic and molecular-level forces active in dense nanoparticle suspensions. At the largest length scale, two 'coarse-grained' numerical techniques have been developed and implemented to provide for high-fidelity numerical simulations of the rheological response and dispersion characteristics typical in a processing flow. The first is a coupled Navier-Stokes/discrete element method in which the background solvent is treated by finite element methods. The second is a particle based method known as stochastic rotational dynamics. These two methods provide a new capability representing a 'bridge' between the molecular scale and the engineering scale, allowing the study of fluid-nanoparticle systems over a wide range of length and timescales as well as particle concentrations. To validate these new methodologies, multi-million atoms simulations explicitly including the solvent have been carried out. These simulations have been vital in establishing the necessary 'subgrid' models for accurate prediction at a larger scale and refining the two coarse-grained methodologies.

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Nanocrystalline and nanostructured materials offer unique microstructure-dependent properties that are superior to coarse-grained materials. These materials have been shown to have very high hardness, strength, and wear resistance. However, most current methods of producing nanostructured materials in weapons-relevant materials create powdered metal that must be consolidated into bulk form to be useful. Conventional consolidation methods are not appropriate due to the need to maintain the nanocrystalline structure. This research investigated new ways of creating nanocrystalline material, new methods of consolidating nanocrystalline material, and an analysis of these different methods of creation and consolidation to evaluate their applicability to mesoscale weapons applications where part features are often under 100 {micro}m wide and the material's microstructure must be very small to give homogeneous properties across the feature.

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We present a Bayesian approach for estimating transmission chains and rates in the Abakaliki smallpox epidemic of 1967. The epidemic affected 30 individuals in a community of 74; only the dates of appearance of symptoms were recorded. Our model assumes stochastic transmission of the infections over a social network. Distinct binomial random graphs model intra- and inter-compound social connections, while disease transmission over each link is treated as a Poisson process. Link probabilities and rate parameters are objects of inference. Dates of infection and recovery comprise the remaining unknowns. Distributions for smallpox incubation and recovery periods are obtained from historical data. Using Markov chain Monte Carlo, we explore the joint posterior distribution of the scalar parameters and provide an expected connectivity pattern for the social graph and infection pathway.

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