Ultrasonic degradation of trichloroethylene and chlorobenzene at micromolar concentrations: kinetics and modelling

Although most papers in the field of sonochemical degradation of volatile organics in aqueous media describe experiments at the millimolar concentration range, this study focuses on the degradation kinetics of chlorobenzene (CB) and trichloroethylene (TCE) in the micromolar range. It was found that the reaction kinetics increase with decreasing initial substrate concentrations. For example, the pseudo-first-order reaction rate constant of CB increases by a factor of 14.3, if the initial concentration drops from 3440 to 1 microM. Previous work in the millimolar range has shown that the degradation of these volatiles is mainly due to pyrolytic reactions. The enhancement of the reaction kinetics at lower concentrations, in this work, could no longer be explained by this mechanism, even by taking into account the effect of the concentration of the solutes on the reaction temperature. Therefore, a new model was developed, incorporating gas phase OH radical induced degradation, next to pyrolysis. The model, fitting the experimental results, illustrated that at micromolar concentrations the OH radical induced degradation becomes significant. Simulations showed that at initial concentrations of CB > 1000 microM degradation is due to pyrolysis for over 99.97%, but it was also demonstrated that at concentrations between 1 and 5 microM, the OH radical mechanism contributed 48.5% of the total degradation.     

Towards logistics systems parameter optimisation through the use of response surfaces

Logistics systems have to cope with uncertainties in demand, in lead times, in transport times, in availability of resources and in quality. Management decisions have to take these uncertainties into consideration. An evaluation of decisions may be done by means of simulation. However, not all stochastic phenomena are of equal importance. By design of simulation experiments and making use of response surfaces, the most important phenomena are detected and their influence on performance estimated. Once the influence of the phenomena is known, this knowledge may be used to determine the optimal values of some decision parameters. An illustration is given on how to use response surfaces in a real-world case. A model is built in a logistics modelling software. The decision parameters have to be optimised for a specific objective function. Experiments are run to estimate the response surface. The validity of the response surface with few observations is also tested.     

Magnetic resonance study of Rh complexes in AgCl microcrystals

X-ray or UV irradiation at room temperature of Rh3+ doped AgCl emulsion powders leads to the production of three paramagnetic Rh2+ related centres, labeled R4, R5 and R6. A combined X and Q band electron paramagnetic resonance (EPR) and electron nuclear double resonance (ENDOR) study allowed the determination of a nearly complete structural model for these centres. In the X band ENDOR spectra of R4 and R5 interactions of the unpaired electron with nearby protons have been identified, indicating that for these centres Cl- ligands have been exchanged by H2O or OH-. The R6 centre, identified as a (RhCl6)4- complex, has been found to be fundamentally different from the dominant centre in large Rh2+ doped AgCl single crystals grown from the melt. The results are compared with recent work by other researchers in the same field.     

A general method for the computation of probabilities in systems of first order chemical reactions

We present a general method for the computation of molecular population distributions in a system of first-order chemical reactions. The method is based on the observation that the molecules in first-order reactions do not interact with each other. Therefore, the population distributions are a convolution of densities for one molecule. With this method one can study reactions involving any number of molecules. Such analysis is demonstrated on several examples, including an enzyme catalyst reaction and a first-order reaction chain.     

Experimental parameters affecting sensitivity and specificity of a yeast assay for estrogenic compounds: results of an interlaboratory validation exercise

In vitro assays are considered as the first step in a tiered approach to compound screening for hormonal activity. Although many new assays have been developed in recent years, little attention has been paid towards assay validation. Our objective was to identify critical experimental parameters in a yeast estrogen screen (YES) that affect its sensitivity and specificity. We investigated the role of incubation time, solvent type, yeast inoculum growth stage and concentration on the outcome of the YES. Compounds tested included new and established agonists, antagonists and negative controls, and results were evaluated according to prefixed statistical criteria. In addition, we assessed the assay’s performance in a blind interlaboratory validation exercise (IVE). An incubation time of five days was necessary to positively identify the estrogenic properties of all agonists tested, when dissolved in DMSO. Longer incubation times were required when using an ethanol protocol. Similar estrogenic activity was reported for benzyl butyl phthalate, bisphenol-A, methoxychlor, permethrin and genistein in the IVE. One out of the three laboratories did not classify α,β-endosulfan, dissolved in DMSO, as an estrogen. The same was true for 4,4′-DDE and lindane, dissolved in ethanol, a result that might be attributable to an inappropriate yeast start concentration and/or growth stage. These validation experiments show that under appropriate experimental conditions the YES yields sensitive, specific and reliable results. Therefore it fulfills the requirements as a first step screening assay to evaluate the capacity of chemicals to interact with the estrogen receptor.