The Synergy Between Dynamics and Reactivity at Clusters and Surfaces (NATO Science Series C: (closed))

!±8± The Synergy Between Dynamics and Reactivity at Clusters and Surfaces (NATO Science Series C: (closed))

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The analogy between the chemistry of molecular transition metal clusters and the processes of chemisorption and catalysis at metal surfaces (the Cluster Surface analogy) has for a number of years provided an interplay between experimental and theoretical inorganic and physical chemists. This collaborative approach has born fruit in the use of well defined modes of metal-ligand bonding in discrete molecular clusters, models for metal-ligand binding on surfaces. Some of the key topics discussed in The Synergy betweenDynamics and Reactivity at Clusters and Surfaces are: (1) Mechanisms of the fluxional behaviour in clusters in the liquid phase and the connections with diffusion processes on extended surfaces. The role of metal-metal bond breaking in diffusion. (2) Analogies in the structure of chemisorbed species and related ligands on metallic clusters. (3) Analogies between benzene surface chemistry on extended metal surfaces and on metal surfaces in molecular cluster compounds with particular reference to structural distortions. (4) The role of mobile precursors for dissociation of chemisorption on extended metals and on clusters. Are there analogies in the ligand attachment during cluster compound synthesis? (5) The role of defect sites on metal surfaces in catalyzing chemical reactions and the connection to the special bonding properties of sites on metal clusters having lowest metal-metal coordination. (6) The size of metal clusters needed to mimic surface phenomena on bulk metal surfaces. Different sites needed for different phenomena.

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Synergy and Duality of Identification and Control (Series in Systems and Control)

!±8± Synergy and Duality of Identification and Control (Series in Systems and Control)

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Post Date : Dec 11, 2011 02:18:07 | N/A

Synergy and Duality of Identification and Control examines the relationship between modelling and control of dynamic systems. Both stochastic and worst-case design approaches are presented. System identification is introducted in worst-case and stochastic frameworks. Interaction between modelling and control is studied at four levels: separate identification and control design, iterative identification and control design, dual control and synergistic interaction of modelling and control. The last part of the book focuses on fast learning control systems via parametric models. This comprehensive monograph is equally suitable for graduate students as well as for researchers in the fields of control engineering and digital signal processing.

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