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During the past decades, atomic-scale simulations have emerged as a tool ofmaterials research and engineering both in academia and industry. Leadingindustrial research laboratories, public laboratories, and universities have startedto combine experimental data with the predictive power and the key tounderstanding materials properties as offered by atomistic simulations to solveengineering problems connected, e.g. to long-term stability of materials or toidentify novel and environment friendly materials. In this situation, as the computerpower is tremendously growing, comprehensive computational environments,which take away the burden of routine tasks, are coming to the fore allowingresearchers to focus on the scientific problem at hand. Using sophisticated modelbuilding and analysis tools, computational environments as the MedeA softwarecombine experimental structures and phase-diagrams with state-of-the-artcomputational procedures for property predictions for systems including alloys,semiconductors, ceramics, glasses, polymers, and fluids. Furthermore, these toolsfacilitate the simulation, e.g. of the electronic structure and mechanical properties,as well as the thermal behaviour for complex structures such as interfaces,heterostructures, grain boundaries, defect structures and random alloys. Thecomprehensive capabilities of such modelling tools will be illustrated byapplications including the development of low-strain cathode materials forbatteries, the analysis of grain-boundary stability in electronic devices, and thesearch for optimum materials for hydrogen storage in the automobile industry.
Mark A. Weiss, Data Structures And Algorithm Analysis In C 4th Keygen
Cerium is the most abundant rare earth. Its compounds are used in many applications. Depending on the application different materials properties are needed. Since these properties are widely determined by the electronic structure the understanding of the degree of localization of the 4f electron is essential. Aiming to classify the Ce compounds regarding to their itinerant character we studied the hybridization function Δ of a large body of data. The hybridization function has been calculated from first principles using a full-potential LMTO method. We show that the strength of Δ evaluated in this way allows conclusions about the level of 4f localization. The results are consistent with the available experimental information. The calculated information entropy for this set of data clearly hints to a high predictability. Furthermore, a more detailed analysis of the electronic structure and the hybridization function allows us to make precise statements about Kondo correlations in these systems. Technically we combine concepts of electronic structure theory, many body physics and information theory. This approach allows us to establish general trends of correlated electronic structures and we can address important questions such as how to find new materials and how to characterize them. 2ff7e9595c
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