Modeling of one-dimensional smoldering of polyurethane in microgravity conditions

Results are presented from a model of forward smoldering combustion of polyurethane foam in microgravity. The transient one-dimensional numerical-model is based on that developed at the University of Texas at Austin. The conservation equations of energy, species, and mass in the porous solid and in the gas phases are numerically solved. The solid and the gas phases are not assumed to be in thermal or in chemical equilibrium. The chemical reactions modeled consist of foam oxidation and pyrolysis reactions, as well as char oxidation. The model has been modified to account for new polyurethane kinetics parameters and radial heat losses to the surrounding environment. The kinetics parameters are extracted from thermogravimetric analyses published in the literature and using Genetic Algorithms as the optimization technique. The model results are compared with previous tests of forward smoldering combustion in microgravity conducted aboard the NASA Space Shuttle. The model calculates well the propagation velocities and the overall smoldering characteristics. Direct comparison of the solution with the experimental temperature profiles shows that the model predicts well these profiles at high temperature, but not as well at lower temperatures. The effect of inlet gas velocity is examined, and the minimum airflow for ignition is identified. It is remarkable that this one-dimensional model with simplified kinetics is capable of predicting cases of smolder ignition but with no self-propagation away from the igniter region. The model is used for better understanding of the controlling mechanisms of smolder combustion for the purpose of fire safety, both in microgravity and normal gravity, and to extend the unique microgravity data to wider conditions avoiding the high cost of space-based experiments.     

Chiral symmetry breaking and meson decays in a relativistic quark model

Applying two different Lorentz-covariant quark models, one of them being essentially nonrelativistic, chiral symmetry breaking parameters of strong interaction will be calculated. Also attention will be paid to meson decays. The model retaining relativistic spinor structure for quark-antiquark wave functions turns out to be more appropriate than the nonrelativistic one.     

Molecular geometries and moments from the maximum overlap criterion

The maximized overlap population, defined as Σ_μ≠νP_μνS_μν, and a related quantity, Σ_μ,νP_μνS²_μν are computed for a series of configurations. The extremum of both approximate molecular geometries, the latter with an accuracy suitable for predictive value. The maximum overlap orbitals predict dipole and quadrupole moments that give reasonable agreement with experimental values.     

Determination of submicromolar amounts of uranium(VI) by compleximetric titration with pyridine-2,6-dicarboxylic acid

Uranium(VI) is selectively determined by a compleximetric titration with pyridine-2,6-dicarboxylic acid, using arsenazo-I indicator and hexamethylenetetramine buffer at pH 4.9. Cyclohexanediaminetetraacetic acid and diethylenetriaminepentaacetic acid provide masking of interfering metal ions. A probe colorimeter apparatus is recommended for end-point detection. The relative standard deviation is 0.6% for 0.17–0.76 μmol of uranium.     

Green's-function reaction dynamics: a particle-based approach for simulating biochemical networks in time and space

We have developed a new numerical technique, called Green's-function reaction dynamics (GFRD), that makes it possible to simulate biochemical networks at the particle level and in both time and space. In this scheme, a maximum time step is chosen such that only single particles or pairs of particles have to be considered. For these particles, the Smoluchowski equation can be solved analytically using Green's functions. The main idea of GFRD is to exploit the exact solution of the Smoluchoswki equation to set up an event-driven algorithm, which combines in one step the propagation of the particles in space with the reactions between them. The event-driven nature allows GFRD to make large jumps in time and space when the particles are far apart from each other. Here, we apply the technique to a simple model of gene expression. The simulations reveal that spatial fluctuations can be a major source of noise in biochemical networks. The calculations also show that GFRD is highly efficient. Under biologically relevant conditions, GFRD is up to five orders of magnitude faster than conventional particle-based techniques for simulating biochemical networks in time and space. GFRD is not limited to biochemical networks. It can also be applied to a large number of other reaction-diffusion problems.     

Valence quark dominance in inelastic neutrino interactions

Scaling observed in neutrino nucleon interactions at relatively low energies and not too small , is attributed to elastic $\text{v(}\text{v}\text{)}$ scattering off three point-like, handed Zweig-Gell-Man valence quarks with low effective mass. The model predicts total inelastic cross sections all in agreement with available experiments.     

Potential-Derived point-charge model study of electrostatic interaction energies in some hydrogen-bonded systems

Mulliken's atomic charges (MC ) and potential derived (PD ) point charges obtained from STO -3G wave functions are used to study the electrostatic interaction energies for a series of representative hydrogenbonded complexes. The results of the above-mentioned models are compared with the more accurate results of segmental multipole moment (SMM ) expansion, and it is shown that the PD model is superior to the Mc model. The results of PD model are shown to be well correlated with the results of SMM expansion technique. Results of our calculations using 6-31G and 6-31G** PD charges are also reported here. Electrostatic interaction energies obtained using 6-31G** PD charges are compared with the 6-31G** SCF interaction energies available for the nine hydrogen-bonded dimers of ammonia, water, and hydrogen fluoride and a good con-elation between the two is shown. The interrelationship between the results of different basis sets are also examined for the PD point-charge model. The electrostatic interaction energies obtained using STO -3G PD model are shown to be well correlated to the results of 6-31G and 6-31G** PD models.     

Designing peptide based nanomaterials

This tutorial review looks at the design rules that allow peptides to be exploited as building blocks for the assembly of nanomaterials. These design rules are either derived by copying nature (alpha-helix, beta-sheet) or may exploit entirely new designs based on peptide derivatives (peptide amphiphiles, pi-stacking systems). We will examine the features that can be introduced to allow self-assembly to be controlled and directed by application of an externally applied stimulus, such as pH, light or enzyme action. Lastly the applications of designed self-assembly peptide systems in biotechnology (3D cell culture, biosensing) and technology (nanoelectronics, templating) will be examined.