Nonequilibrium Zeldovich-von Neumann-Doring theory and reactive flow modeling of detonation

This paper discusses the Nonequilibrium Zeldovich-von Neumann-Doring (NEZND) theory of self-sustaining detonation waves and the Ignition and Growth reactive flow model of shock initiation and detonation wave propagation in solid explosives. The NEZND theory identified the nonequilibrium excitation processes that precede and follow the exothermic decomposition of a large high explosive molecule into several small reaction product molecules. The thermal energy deposited by the leading shock wave must be distributed to the vibrational modes of the explosive molecule before chemical reactions can occur. The induction time for the onset of the initial endothermic reactions can be calculated using high pressure-high temperature transition state theory. Since the chemical energy is released well behind the leading shock front of a detonation wave, a physical mechanism is required for this chemical energy to reinforce the leading shock front and maintain its overall constant velocity. This mechanism is the amplification of pressure wavelets in the reaction zone by the process of de-excitation of the initially highly vibrationally excited reaction product molecules. This process leads to the development of the three-dimensional structure of detonation waves observed for all explosives. For practical predictions of shock initiation and detonation in hydrodynamic codes, phenomenological reactive flow models have been developed. The Ignition and Growth reactive flow model of shock initiation and detonation in solid explosives has been very successful in describing the overall flow measured by embedded gauges and laser interferometry. This reactive flow model uses pressure and compression dependent reaction rates, because time-resolved experimental temperature data is not yet available. Since all chemical reaction rates are ultimately controlled by temperature, the next generation of reactive flow models will use temperature dependent reaction rates. Progress on a statistical hot spot ignition and growth reactive flow model with multistep Arrhenius chemical reaction pathways is discussed. The text was submitted by the authors in English.     

Structures and syntheses of four Np sulfate chain structures: Divergence from U crystal chemistry

Four Np⁵⁺ sulfates, X₄[(NpO₂)(SO₄)₂]Cl (X=K, Rb) (KS1, RbS1), Na₃[(NpO₂)(SO₄)₂](H₂O)_2.5 (NaS1), and CaZn₂[(NpO₂)₂(SO₄)₄](H₂O)₁₀ (CaZnS1) were synthesized by evaporation of solutions derived from hydrothermal treatment. Their structures were solved by direct methods and refined on the basis of F² for all unique data collected with MoKα radiation and a CCD-based detector to agreement indices (KS1, RbS1, NaS1, CaZnS1) R₁=0.0237, 0.0593, 0.0363, 0.0265 calculated for 2617, 2944, 2635, 2572 unique observed reflections, respectively. KS1 crystallizes in space group P2/n, a=10.0873(4), b=4.5354(2), c=14.3518(6), β=103.383(1)°, , Z=2. RbS1 is also monoclinic, P2/n, with a=10.5375(8), b=4.6151(3), c=16.0680(12), β=103.184(1)°, , Z=2. NaS1 is monoclinic, P2₁/m, with a=7.6615(5), b=7.0184(4), c=11.0070(7), β=90.787(1)°, , Z=4. CaZnS1 is monoclinic, P2₁/m, with a=8.321(2), b=7.0520(2), c=10.743(3), β=91.758(5)°, , Z=2. The structures of KS1 and RbS1 contain chains of edge-sharing neptunyl hexagonal bipyramids, with sulfate tetrahedra attached to either side of the chain by sharing edges with the bipyramids. NaS1 and CaZnS1 both contain chains of neptunyl pentagonal bipyramids and sulfate tetrahedra in which each bipyramid is linked to four tetrahedra, three by sharing vertices and one by sharing an edge. Bipyramids are bridged by sharing vertices with sulfate tetrahedra. Each of these structures exhibits significant departures from those of uranyl sulfates.     

The polymerization of actin: extent of polymerization under pressure, volume change of polymerization, and relaxation after temperature jumps

The protein actin can polymerize from monomeric globular G-actin to polymeric filamentary F-actin, under the regulation of thermodynamic variables such as temperature, pressure, and compositions of G-actin and salts. We present here new measurements of the extent of polymerization (phi) of actin under pressure (P), for rabbit skeletal muscle actin in H2O buffer in the presence of adenosine triposphate and calcium ions and at low (5-15 mM) KCl concentrations. We measured phi using pyrene-labeled actin, as a function of time (t) and temperature (T), for samples of fixed concentrations of initial G-actin and KCl and at fixed pressure. The phi(T,P) measurements at equilibrium have the same form as reported previously at 1 atm: low levels of polymerization at low temperatures, representing dimerization of the actin; an increase in phi at the polymerization temperature (Tp); a maximum in phi(T) above Tp) with a decrease in phi(T) beyond the maximum, indicating a depolymerization at higher T. From phi(T,P) at temperatures below Tp, we estimate the change in volume for the dimerization of actin, DeltaVdim, to be -307+/-10 ml/mol at 279 K. The change of Tp with pressure dTp/dP=(0.3015+/-0.0009) K/MPa=(30.15+/-0.09) mK/atm. The phi(T,P) data at higher T indicate the change in volume on propagation, DeltaVprop, to be +401+/-48 ml/mol at 301 K. The phi(t) measurements yield initial relaxation times rp(T) that reflect the behavior of phi(T) and support the presence of a depolymerization temperature. We also measured the density of polymerizing actin with a vibrating tube density meter, the results of which confirm that the data from this instrument are affected by viscosity changes and can be erroneous.     

Reagent Selector: using Synthon Analysis to visualize reagent properties and assist in combinatorial library design

Reagent Selector is an intranet-based tool that aids in the selection of reagents for use in combinatorial library construction. The user selects an appropriate reagent group as a query, for example, primary amines, and further refines it on the basis of various physicochemical properties, resulting in a list of potential reagents. The results of this selection process are, in turn, converted into synthons: the fragments or R-groups that are to be incorporated into the combinatorial library. The Synthon Analysis interface graphically depicts the chemical properties for each synthon as a function of the topological bond distance from the scaffold attachment point. Displayed in this fashion, the user is able to visualize the property space for the universe of synthons as well as that of the synthons selected. Ultimately, the reagent list that embodies the selected synthons is made available to the user for reagent procurement. Application of the approach to a sample reagent list for a G-protein coupled receptor targeted library is described.     

Shock initiation of composition B and C-4 explosives: Experiments and modeling

Shock initiation experiments with composition B and C-4 HE were performed to obtain in situ pressure gauge data for the purpose of providing the ignition and growth reactive flow model with proper modeling parameters. A 100-mm-bore propellant-driven gas gun was utilized to initiate the explosive charges containing manganin piezoresistive pressure gauge packages embedded in the explosive sample. Experimental data provided new information on the shock velocity-particle velocity relationship for each of the investigated material in their respective pressure range. The run-to-detonation distance points in the pop plot for these experiments showed agreement with previously published data, and ignition and growth modeling calculations resulted in a good fit to the experimental data. Identical ignition and growth reaction rate parameters were used for C-4 and composition B, and the composition B model also included a third reaction rate to simulate the completion of reaction by the TNT component. This model can be applied to shock initiation scenarios that have not or cannot be tested experimentally with a high level of confidence in its predictions. This paper was presented at the International Conference “Shock Waves in Condensed Media,” St. Petersburg, September, 2006. The text was submitted by the authors in English.     

Exact Solution of Locomotive Scheduling Problems

Given a daily repeating timetable and locomotives of various types, each timetabled train must be assigned a locomotive. This paper presents an exact algorithm for the solution of this problem, based on an approach used to solve multiple-depot bus scheduling problems. The algorithm is used to solve moderately large scheduling problems drawn from real world data.