Photocatalytic mineralisation of organic compounds: a comparison of flame-made TiO2 catalysts

A comparative photocatalytic analysis was carried out on TiO₂ made in a Flame Spray Pyrolysis (FSP) process and flame-made Degussa P25. Both have similar crystallinity, phase composition, phase segregation and a non-porous surface. Hence comparison was made based on their difference in specific surface area, organic adsorption and the amount of OH• generated upon illumination. The photocatalytic activity tests were carried out using the following series of organic compounds: sucrose, glucose, fructose, maleic acid, glyoxylic acid, oxalic acid, isobutyric acid, phenol and methanol. FSP-made TiO₂ outperformed P25 for saccharides mineralisation, while for phenol and methanol mineralisation P25 was better than FSP-made TiO₂. Similar mineralisation rates were observed for both FSP-made and P25 TiO₂ for the mineralisation of carboxylic acids. This shows that the relative performance of the photocatalysts depends on the type of organic compounds to be degraded. The high surface area and possibly a more efficient interfacial charge transfer of FSP-made TiO₂ provided an efficient pathway for saccharides mineralisation. As for phenol and methanol, the mineralisation rates were higher when using P25 due to the greater amount of OH• radicals generated by this photocatalyst. The fast mineralisation rates of carboxylic acids made degradation of these organic compounds to be less affected by the TiO₂ photocatalyst properties and conditions tested in this work.     

ON THE ROBUST PREDICTION AND INTERPOLATION OF TIME SERIES IN THE PRESENCE OF CORRELATED NOISE

Abstract. We consider the problem of predicting and interpolating linearly a time series which can be represented as the sum of a model process with known spectral density and a noise process. The spectral density of the noise process is unknown with the exception of an upper bound for its integral. Some partial information of quite general kind about the cross spectral density of model and noise is available. We prove the existence of a robust predictor which minimizes the maximal mean-square error, where the maximum is taken over all spectral densities which may arise from the circumstances described above as spectral density of the predicted time series. An analogous result holds for the related interpolation problem. We describe how to derive the minimax robust predictor and interpolator in concrete situations. The method is illustrated by determining the robust predictor explicitly for three examples where model and noise may be arbitrarily, only causally or not at all correlated.     

An architecture modeling framework for probabilistic prediction

In the design phase of business and IT system development, it is desirable to predict the properties of the system-to-be. A number of formalisms to assess qualities such as performance, reliability and security have therefore previously been proposed. However, existing prediction systems do not allow the modeler to express uncertainty with respect to the design of the considered system. Yet, in contemporary business, the high rate of change in the environment leads to uncertainties about present and future characteristics of the system, so significant that ignoring them becomes problematic. In this paper, we propose a formalism, the Predictive, Probabilistic Architecture Modeling Framework (P²AMF), capable of advanced and probabilistically sound reasoning about business and IT architecture models, given in the form of Unified Modeling Language class and object diagrams. The proposed formalism is based on the Object Constraint Language (OCL). To OCL, P²AMF adds a probabilistic inference mechanism. The paper introduces P²AMF, describes its use for system property prediction and assessment and proposes an algorithm for probabilistic inference.     

Dynamische Prozeßsimulation in der industriellen Praxis

Dynamic process simulation in industrial practice. Dynamic process simulation is gaining in importance in process development and plant design. In addition to simulation tools for steady state calculations and optimization, recent years have seen increased development of software tools suitable for dynamic simulation. In particular, dynamic process models have been developed for various unit operations at universities and in industry. Application of the models includes synthesis and analysis of the control structure, start-up and shut down, safety assessments, optimization, and training. In addition, dynamic flowsheet programs analogous to the steady state programs were developed. Wider use of these program systems requires increased flexibility, solving procedures, user interfaces, model library, interfaces to external programs, etc. The present article is intended not only to describe the state of the art and describe some typical applications, but in particular to examine the demands placed on dynamic process simulation and the simulators and to delineate the current limitations of dynamic process simulation from an industrial viewpoint.     

A second-generation system for unbiased reading frame selection

Reading frame selection of nucleic acids has important implications for protein engineering and genomics. Current methods are limited because selection of the gene of interest inevitably depends on the solubility of its translated product. Here we report the construction of the pInSALect vector, which provides strict reading frame selection without concomitant selection for protein solubility or folding. This plasmid incorporates the cis-splicing VMA intein sequence from Saccharomyces cerevisiae to facilitate the post-translational self-excision of the protein of interest, thereby eliminating potential aggregation problems. Results from two libraries of chimeric glycinamide ribonucleotide formyltransferases confirm the superior performance of pInSALect over existing reading frame selection systems.     

Tripodal amido complexes: molecular "claws" in main group and transition metal chemistry

The chemistry of transition metal amides has received new impetus in recent years due to the systematic exploitation of the amido function [NR(2)](-) in ligand design. A class of 3-fold symmetrical tripodal amido ligands has proved to be a valuable tool in the stabilization of early transition metal and main group metal complexes and complex fragments. Moreover, promising strategies for their use as chemical reagents and homogeneous catalysts have been developed. An overwiew of the current state of this field is given and the potential for further development will be highlighted.     

Wearable cognitive assistants in a factory setting: a critical review of a promising way of enhancing cognitive performance and well-being

Cognition, Technology & Work - Rapid technological innovations are constantly influencing the complexification and automatization of the work lines pushing human operators to use diverse...     

Guided architecture trade space exploration: fusing model-based engineering and design by shopping

Software and Systems Modeling - Advances in model-based system engineering have greatly increased the predictive power of models and the analyses that can be run on them. At the same time, designs...     

Dealuminated Y Zeolite for Water-Driven Adsorption Heat Pumps: Hydrothermal Stability

Silica gel or zeolites AlPO-5 and SAPO-34 are recommended as adsorbents in water-driven heat pumps because of their selective water uptake. Secondary energy, like solar energy, can be used for regeneration of loaded adsorbers. In case of the availability of only low energy levels, the use of dealuminated Y zeolite (DAY) is the better choice because of the infinitely variation of its hydrophilic properties by tailoring of the framework Si/Al ratio. Actual data on the hydrothermal stability of DAY are lacking. Thus, we report on the long-term behavior of DAY zeolites with different Si/Al ratios.