Corner-Turning Distance and Retonation Radius

All high explosives, at least the ones used in military applications, have a specific minimum detonation radius, R_min with which the detonation can change its direction through 90° or 180°. It is to be emphasized that this applies not only to thc so-called insensitive high explosives, but the sensitive explosives of course have smaller radii than the insensitive ones. The corner-turning distance, As, determined in the radial test, also corresponds to the minimum radius, R_min for the detonation wave to invert its direction through 180°. The radial test is a simple method, with regard to both design and analysis, that is suitable for determining the 90°-distance, or the minimum detonation radius, R_min.     

CNT Based Elastomer‐Hybrid‐Nanocomposites with Promising Mechanical and Electrical Properties

CNT based elastomer‐hybrid‐nanocomposites prepared by melt mixing have been investigated showing promising results in technologically relevant electrical, mechanical, and fracture‐mechanical properties. It is demonstrated that the incorporation of CNT in silica‐filled natural rubber results in a good dispersion of the CNT. The materials show an enhanced mechanical stiffness and tensile strength, an increased modulus, and a high electrical conductivity with quite low amounts of CNT, though the tear resistance under dynamical loading is slightly reduced. Using DMA and dielectric spectra, a better understanding of the conduction mechanism, the polymer/tube interaction, and the filler networking in CNT nanocomposites is achieved.

     

Kinetic Analysis of Terminal and Unactivated C?H Bond Oxyfunctionalization in Fatty Acid Methyl Esters by Monooxygenase‐Based Whole‐Cell Biocatalysis

The alkane monooxygenase AlkBGT from Pseudomonas putida GPo1 constitutes a versatile enzyme system for the ω‐oxyfunctionalization of medium chain‐length alkanes. In this study, recombinant Escherichia coli W3110 expressing alkBGT was investigated as whole‐cell catalyst for the regioselective biooxidation of fatty acid methyl esters to terminal alcohols. The ω‐functionalized products are of general economic interest, serving as building blocks for polymer synthesis. The whole‐cell catalysts proved to functionalize fatty acid methyl esters with a medium length alkyl chain specifically at the ω‐position. The highest specific hydroxylation activity of 104 U g_CDW⁻¹ was obtained with nonanoic acid methyl ester as substrate using resting cells of E. coli W3110 (pBT10). In an optimized set‐up, maximal 9‐hydroxynonanoic acid methyl ester yields of 95% were achieved. For this specific substrate, apparent whole‐cell kinetic parameters were determined with a V_max of 204±9 U g_CDW⁻¹, a substrate uptake constant (K_S) of 142±17 μM, and a specificity constant V_max/K_S of 1.4 U g_CDW⁻¹ μM ⁻¹ for the formation of the terminal alcohol. The same E. coli strain carrying additional alk genes showed a different substrate selectivity. A comparison of biocatalysis with whole cells and enriched enzyme preparations showed that both substrate availability and enzyme specificity control the efficiency of the whole‐cell bioconversion of the longer and more hydrophobic substrate dodecanoic acid methyl ester. The efficient coupling of redox cofactor oxidation and product formation, as determined in vitro, combined with the high in vivo activities make E. coli W3110 (pBT10) a promising biocatalyst for the preparative synthesis of terminally functionalized fatty acid methyl esters.     

SkaSim – Skalierbare HPC‐Software für molekulare Simulationen in der chemischen Industrie

This article outlines advances in molecular modeling and simulation using massively parallel high‐performance computers (HPC). In the SkaSim project, partners from the HPC community collaborated with users from science and industry. The aim was to optimize the prediction of thermodynamic property data in terms of efficiency, quality and reliability using HPC methods. In this context, various topics were dealt with: atomistic simulation of homogeneous gas bubble formation, surface tension of classical fluids and ionic liquids, multicriteria optimization of molecular models, the development of the molecular simulation codes ls1 mardyn and ms2, atomistic simulation of gas separation processes, molecular membrane structure generators, transport resistors and the evaluation of predictive property data models based on specific mixture types.     

Modification of CaCO3 precipitation rates by water-soluble nacre proteins

Mineral growth in nacre and other CaCO₃-containing biominerals is controlled by biopolymers. Water-soluble proteins were extracted from nacre of the sea snail Haliotis laevigata by dissolving the mineral phase with 6% acetic acid. The influence of this protein mixture on CaCO₃ precipitation rates was investigated at different concentrations. A well-established assay for measuring the pH-value during CaCO₃ precipitation with and without protein additives was extended by calculating maximum precipitation rates from the pH-values. It could be shown that precipitation rates are greatly influenced by the mixtures of water-soluble nacre proteins. At very low protein concentrations (0.02 μg/ml) a rate enhancement in comparison to the pure supersaturated calcium carbonate solution by a factor of 1.4 was observed. At higher protein concentrations, a strong inhibitory effect occurred, with total inhibition at concentrations of 1.0 μg/ml and higher. Two unspecific proteins (bovine serum albumin and lysozyme) showed little or no modification of precipitation rates. In vivo, the function of the strong inhibition of CaCO₃ precipitation by nacre proteins at higher concentrations is presumably to prevent uncontrolled crystallization in the extrapallial fluid. The rate-enhancing capability of proteins at low concentrations may be explained by the presence of acidic and/or hydrophilic moieties.     

Polymerization of epoxy resins initiated by metal complexes

BACKGROUND: Processing parameters and material properties of epoxy resins can be vastly influenced by choice of curing agent. In this work, metal complexes were investigated as initiators for anionic and cationic epoxide polymerization. Systems for thermally induced and electron beam‐induced curing are described. RESULTS: Zinc or cobalt imidazole complexes of the type [M(imidazole)₂(anion)₂] are efficient initiators for anionic polymerization of glycidyl‐based epoxy resins. The complexes can be employed to prepare tailored resin systems ranging from fast curing systems at slightly elevated temperatures to systems with very high thermal latencies curable at temperatures far above 150 °C. Silver complexes [Ag(L)_n]SbF₆ (L = crown ether or alkene) are highly efficient initiators for cationic curing and low initiator contents of around 1% are sufficient to reach high degrees of crosslinking. The complexes are excellent initiators for both thermally induced and electron beam‐induced polymerizations. CONCLUSION: Metal complexes are powerful initiators for the homopolymerization of epoxy resins and can be designed not only for anionic and cationic polymerization but also for thermal and radiation curing. Based on this study and additional work, a library can be compiled which allows retrieval of optimized metal–ligand–anion combinations and adjustment of the initiators to the respective processing and material demands. Copyright © 2009 Society of Chemical Industry     

Forschungsgesellschaft Computer Automation

SciencenewsNeugrünoung

Forschungsgesellschaft Computer Automation     

Sparse on-line gaussian processes

We develop an approach for sparse representations of gaussian process (GP) models (which are Bayesian types of kernel machines) in order to overcome their limitations for large data sets. The method is based on a combination of a Bayesian on-line algorithm, together with a sequential construction of a relevant subsample of the data that fully specifies the prediction of the GP model. By using an appealing parameterization and projection techniques in a reproducing kernel Hilbert space, recursions for the effective parameters and a sparse gaussian approximation of the posterior process are obtained. This allows for both a propagation of predictions and Bayesian error measures. The significance and robustness of our approach are demonstrated on a variety of experiments.