879 resultados para Metals Bank
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In order to improve the sulfur resistance of noble metal catalysts in the aromatic hydrogenation of diesel fuel, the alloying effect of non-noble metals with Pd was studied. Toluene hydrogenation over Pd and Pd-M bimetallic catalysts (M = Cr, W,La, Mn, Mo, Ag) on a mixed HY-Al2O3 support was investigated in the presence of 3000 ppm sulfur as thiophene in the feedstock. The results showed that the addition of the second metals strongly affected the activity of toluene hydrogenation, which suggests that the sulfur resistibility of Pd-M bimetallic catalysts is much different from single Pd. La, Mn, Mo and Ag decreased the sulfur resistance of the palladium catalysts. For example, the toluene conversion at 553 K was observed to decrease sharply from 39.4 wt.% on Pd to 1.6 wt.% on Pd-Ag, which is by a factor of 25. One of the important findings in this article is that Cr and W increase hydrogenation activity of Pd catalysts. The reactions occurring on these catalysts include hydrogenation, isomerization and hydrocracking, The addition of the second metals has no noticeable effects on the hydrogenation and isomerization selectivity, but it slightly suppresses hydrocracking reactions. The four typical catalysts, Pd-Cr, Pd-W, Pd-Ag and Pd were characterized by infrared (IR) spectroscopy of pyridine and CO. LR spectra of CO revealed the strong interaction between Pd and the second metal as Cr, W and Ag (or their oxide), indicating that the improvement in sulfur resistance originates from electron-deficient Pd with the addition of second metals. (C) 2001 Elsevier Science B.V. All rights reserved.
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info:eu-repo/semantics/published
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info:eu-repo/semantics/nonPublished
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Congrès du GIRSO, Lille, avril 2011
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The ability to predict the existence and crystal type of ordered structures of materials from their components is a major challenge of current materials research. Empirical methods use experimental data to construct structure maps and make predictions based on clustering of simple physical parameters. Their usefulness depends on the availability of reliable data over the entire parameter space. Recent development of high-throughput methods opens the possibility to enhance these empirical structure maps by ab initio calculations in regions of the parameter space where the experimental evidence is lacking or not well characterized. In this paper we construct enhanced maps for the binary alloys of hcp metals, where the experimental data leaves large regions of poorly characterized systems believed to be phase separating. In these enhanced maps, the clusters of noncompound-forming systems are much smaller than indicated by the empirical results alone. © 2010 The American Physical Society.
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Neurodegenerative diseases like Alzheimer's and Parkinson's disease are associated with elevated levels of iron, copper, and zinc and consequentially high levels of oxidative stress. Given the multifactorial nature of these diseases, it is becoming evident that the next generation of therapies must have multiple functions to combat multiple mechanisms of disease progression. Metal-chelating agents provide one such function as an intervention for ameliorating metal-associated damage in degenerative diseases. Targeting chelators to adjust localized metal imbalances in the brain, however, presents significant challenges. In this perspective, we focus on some noteworthy advances in the area of multifunctional metal chelators as potential therapeutic agents for neurodegenerative diseases. In addition to metal chelating ability, these agents also contain features designed to improve their uptake across the blood-brain barrier, increase their selectivity for metals in damage-prone environments, increase antioxidant capabilities, lower Abeta peptide aggregation, or inhibit disease-associated enzymes such as monoamine oxidase and acetylcholinesterase.
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We report a comprehensive study of the binary systems of the platinum-group metals with the transition metals, using high-throughput first-principles calculations. These computations predict stability of new compounds in 28 binary systems where no compounds have been reported in the literature experimentally and a few dozen of as-yet unreported compounds in additional systems. Our calculations also identify stable structures at compound compositions that have been previously reported without detailed structural data and indicate that some experimentally reported compounds may actually be unstable at low temperatures. With these results, we construct enhanced structure maps for the binary alloys of platinum-group metals. These maps are much more complete, systematic, and predictive than those based on empirical results alone.
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p.19-29
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p.19-29
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Metals casting is a process governed by the interaction of a range of physical phenomena. Most computational models of this process address only what are conventionally regarded as the primary phenomena-heat conduction and solidification. However, to predict the formation of porosity (a factor of key importance in cast quality) requires the modelling of the interaction of the fluid flow, heat transfer, solidification and the development of stress-deformation in the solidified part of a component. In this paper, a model of the casting process is described which addresses all the main continuum phenomena involved in a coupled manner. The model is solved numerically using novel finite volume unstructured mesh techniques, and then applied to both the prediction of shape deformation (plus the subsequent formation of a gap at the metal-mould interface and its impact on the heat transfer behaviour) and porosity formation in solidifying metal components. Although the porosity prediction model is phenomenologically simplistic it is based on the interaction of the continuum phenomena and yields good comparisons with available experimental results. This work represents the first of the next generation of casting simulation tools to predict aspects of the structure of cast components.
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The recovery of platinum group metals (PGMs) from catalytic converters of spent exhaust systems is considered in this paper. To be cost-effective, recovery processes must be well over 90% efficient and so the optimisation of their operation is vital. Effective optimisation requires a sound understanding of the operation and the underlying process mechanisms. This paper focuses on pyrometallurgical recovery operations used and typified by the Johnson–Matthey process. Analysis of this process reveals that it cannot be simply explained by the gravity model that is normally assumed. The analysis reveals that the affinity of PGM particles for the melted collector metal is a key factor in the behaviour of the process. A rational explanation of the key issues that govern the process behaviour is proposed and shown to be consistent with available operational data. The results generated would be applicable to other similar processes.
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A commercial pyrometallurgical process for the extraction of platinum-group metals (PGM) from a feedstock slag was analysed with the use of a model based on computational fluid dynamics. The results of the modelling indicate that recovery depends on the behaviour of the collector phase. A possible method is proposed for estimation of the rate at which PGM particles in slag are absorbed into an iron collector droplet that falls through it. Nanoscale modelling techniques (for particle migration or capture) are combined with a diffusion-controlled mass-transfer model to determine the iron collector droplet size needed for >95% PGM recovery in a typical process bath (70 mm deep) in a realistic time-scale (<1 h). The results show that an iron droplet having a diameter in the range 0.1–0.3 mm gives good recovery (>90%) within a reasonable time. This finding is compatible with published experimental data. Pyrometallurgical processes similar to that investigated should be applicable to other types of waste that contain low levels of potentially valuable metals.