Electron-beam treatment of aromatic hydrocarbons that can be air-stripped from contaminated groundwater. 2. Gas-phase studies

The electron-beam (EB) degradation of volatile aromatics (benzene, toluene, ethylbenzene, xylenes: BTEX) in groundwater strip gas, which in the present work has been modeled by the introduction of the desired aromatic(s) to a stream of air or another gas, such as oxygen, is initiated essentially by the addition of *OH radicals to the aromatic ring, giving rise to hydroxycyclohexadienyl radicals, which form the corresponding peroxyl radicals upon addition of oxygen. As studied in some detail with benzene as a BTEX representative, various reactions of these lead to numerous oxidation products in a cascade of reactions, including the decomposition of products under the prevailing conditions of high turnover of the initial aromatic. Importantly, hydroxycyclohexadienylperoxyl radical formation is partly reversible, and the reactions of the hydroxycyclohexadienyl radicals, which thus have a significant presence in these systems, must therefore also be taken into consideration. In the gas phase, in contrast to the aqueous phase (see Part 1), the reactions of the hydroxycyclohexadienyl radicals lead to oligomeric products that appear to contribute, in addition to ionic clusters, to nucleation for the aerosols observed. Various nitrated products, among them nitrophenols, are observed when air is used for the stripping. However, these studies did not clear the pilot plant stage, since BTEX degradation using a bioreactor carried out in parallel was so successful that the EB technology was judged to be noncompetitive. As for the latter, expensive equipment consisting of a stripper, the EB machine, and an aerosol precipitator would be required. The condensed aerosols are biorefractory and would require further treatment for detoxification.     

POLYCHAR-10 World Forum on Polymer Applications &; Theory in 2002

A report from POLYCHAR-10 is provided. An introduction to the following papers presented at the POLYCHAR-10 Forum is given. A small selection of the authors and titles of the papers presented is listed. Prizes awarded are listed along with the composition of the Prize Committee. Some research groups of high activity which are represented at POLYCHAR every year are named. Electronic Publication     

Nitrous oxide emission as affected by liming an acidic mineral soil used for arable agriculture

The effect of liming an acidic mineral soil (Dystric Nitosol from southern China), used for arable agriculture, on N₂O emission was studied in an incubation experiment. After the soil pH had been raised from pH 4.4 to 5.2, 6.7 and 8.1, soil samples were either amended with NH₄ ⁺ and incubated aerobically, favoring nitrification or, after application of NO₃ ^–, the incubation took place under anaerobic conditions, favoring denitrification. Gas sampling for N₂O determination and soil analyses were performed at regular intervals up to 13 days. Under nitrification conditions only small N₂O emission rates were observed (max. 6 g N kg^–1 d^–1) with significant differences between high and low pH values during the first 2 days of incubation. The nitrifying activity was low, even with high pH, and this, together with good aeration conditions, could partly explain the small N₂O evolution. During denitrification, however, cumulative N₂O emissions reached much higher values (1600 g N kg^–1 in comparison to 40 g N kg^–1 under nitrification conditions). N₂O emission during denitrification was significantly enhanced by increasing soil pH. Under alkaline conditions (pH 8.1) a large nitrite accumulation occurred, which was in line with the highest nitrate reductase activity determined in this treatment. The limited availability of organic carbon is probably the main reason for the absence of further reduction of NO₂ ^– to N₂O or N₂. At pH 6.7 the total N₂O emission was slightly higher than at pH 8.1, although the start of pronounced emissions was retarded and only small amounts of NO₂ ^– accumulated. Acid soil conditions caused either negligible (pH 4.4) or only small (pH 5.2) N₂O emissions. It can be concluded that these kinds of soil, used alternatively for production of upland crops or paddy rice, are prone to high N₂O emissions after flooding, particularly under neutral to alkaline conditions. In order to avoid major N₂O evolution and accumulation of nitrite, which can be leached into groundwater, the pH should not be raised to values above 5.5–6.     

Future trends in data mining

Over recent years data mining has been establishing itself as one of the major disciplines in computer science with growing industrial impact. Undoubtedly, research in data mining will continue and even increase over coming decades. In this article, we sketch our vision of the future of data mining. Starting from the classic definition of “data mining”, we elaborate on topics that — in our opinion — will set trends in data mining.     

Metallo‐Supramolecular Block Copolymers

Supramolecular copolymers have become of increasing interest in recent years for the search of new materials with tunable properties. In particular, metallo‐supramolecular block copolymers—copolymers in which the blocks are linked together by a metal–ligand complex—have seen important progresses, allowing better control over the synthetic strategies for various architectures, and providing a better understanding of the parameters governing their self‐assembly. We review here recent developments on the synthesis and self‐assembly of such materials achieved in this field.     

Cover Picture: Magnetorheological Fluids Based on Ionic Liquids (Adv. Mater. 13/2007)

The use of ionic liquids as carriers of magnetorheological fluids is described by Schubert and co‐workers on p. 1740. Combining the properties of ionic liquids with magnetorheological technology may lead to new, “smart” fluids for application in medical therapies, engineering devices, or multiphase biological and chemical systems. In the presence of a magnetic field the fluids behave as solids owing to a stronger interaction between their suspended magnetic particles. In the absence of the magnetic field, they become liquids again in a fully reversible process.     

Influence of Molybdenum Silicide Additions on High-Temperature Oxidation Resistance of Silicon Nitride Materials

The influence of additions of molybdenum disilicide (MoSi₂) on the microstructure and the mechanical properties of a silicon nitride (Si₃N₄) material, with neodymium oxide (Nd₂O₃) and aluminum nitride (AIN) as sintering aids, was studied. The composites, containing 5, 10, and 17.6 wt% MoSi₂, were fabricated by hot pressing. All materials exhibited a similar phase composition, detected by X-ray diffractometry. Up to MoSi₂ additions of 10 wt%, mechanical properties such as strength, fracture toughness, or creep at 1400°C were not affected significantly, in comparison to that of monolithic Si₃N₄. The oxidation resistance of the composites, in terms of weight gain, degraded. After 1000 h of oxidation at 1400° and 1450°C in air, a greater weight gain (by a factor of approximately three) was obtained, in comparison to that of the material without MoSi₂. Nevertheless, after 1000 h of oxidation, the degradation in strength of the composites was considerably less severe than that of the material without MoSi₂. An additional layer was formed, caused by processes at the surface of the Si₃N₄ material, preventing the formation of pores, cracks, or glassy-phase-rich areas, which are common features of oxidation damage in Si₃N₄ materials. This surface layer, containing Mo₅Si₃ and silicon oxynitride (Si₂ON₂), was the result of reactions between MoSi₂, Si₃N₄, and the oxygen penetrating by diffusion into the material during the hightemperature treatment.     

On the evaluation of unsupervised outlier detection: measures,datasets, and an empirical study

The evaluation of unsupervised outlier detection algorithms is a constant challenge in data mining research. Little is known regarding the strengths and weaknesses of different standard outlier detection models, and the impact of parameter choices for these algorithms. The scarcity of appropriate benchmark datasets with ground truth annotation is a significant impediment to the evaluation of outlier methods. Even when labeled datasets are available, their suitability for the outlier detection task is typically unknown. Furthermore, the biases of commonly-used evaluation measures are not fully understood. It is thus difficult to ascertain the extent to which newly-proposed outlier detection methods improve over established methods. In this paper, we perform an extensive experimental study on the performance of a representative set of standard k nearest neighborhood-based methods for unsupervised outlier detection, across a wide variety of datasets prepared for this purpose. Based on the overall performance of the outlier detection methods, we provide a characterization of the datasets themselves, and discuss their suitability as outlier detection benchmark sets. We also examine the most commonly-used measures for comparing the performance of different methods, and suggest adaptations that are more suitable for the evaluation of outlier detection results.