Cluster model computational process

The underlying motivation of the work presented in this paper is to provide a theoretical understanding of basic physical and chemical properties and processes of relevance in photoelectrochemical devices based on nanostructured transition metal oxides. In this context, fundamental problems concerning the binding of adsorbed molecules to complex surfaces, electron transfer between adsorbate and solid, effects of intercalated ions and defects on electronic and geometric structure, etc., must be addressed, as well as methodological aspects, such as efficiency and reliability of different computational schemes, cluster models versus periodic ones, etc.. 

The process of adsorption and interaction of probe molecules such as ammonia, carbon monoxide as well as the whole spectrum of organic reactant molecules with zeolite catalysts has been the subject of numerous experimental and computational studies. These interaction processes are studied using several computational methods involving force fields (Monte Carlo, molecular dynamics emd energy minimization) or quantum chemical methods. Another paper [1] discusses the application of force field methods for studying several problems in zeolite chemistry. Theoretical quantum chemical studies on cluster models of zeolites help us to understand the electronic and catalytic properties of zeolite catalysts. Here we present a brief summary of the application of quantum chemical methods to understand the structure and reactivity of zeolites. 

Some fundamental aspects of the nucleation process have been investigated by molecular dynamics (MD) methods. In a recent review [44] the advantages and limitations of molecular cluster models in simulating the dynamics of nucleation and phase changes have been discussed. In this approach, molecular dynamic simulations are correlated with experimental nucleation rates extracted from electron diffraction patterns of molecular supersonic jets. The dynamics of freezing of ammonia, CCI4 and water, and the phase transformations of t-butyl chloride have been analysed. A useful feature of the MD computational... 

This is clearly a more complex reaction than that of HKMT just described. Of the seven steps shown in the movie all but one involve conformational changes of the enzyme that are more in the domain of Molecular Mechanics than in that of quantum chemistry (we are studying these conformational steps, but they are not the topic of the present chapter). The sole exception is step 4, catalytic incorporation, which actually involves a multistep mechanism of chemical reactions. This is where theory and computation have to step in to help elucidate the mechanism. The first steps of the process involve the construction of cluster models for the calculation of relevant portions of the potential energy surface corresponding to proposed reaction steps. Several key choices have to be made for which reactions to consider. 

Red giant stars, both in the field and in globular clusters, present abundance anomalies that can not be explained by standard stellar evolution models. Some of these peculiarities, such as the decline of 12C/13C, and that of Li and 12C surface abundances for stars more luminous than the bump, clearly point towards the existence of extra-mixing processes at play inside the stars, the nature of which remains unclear. Rotation has often been invoked as a possible source for mixing inside Red Giant Branch (RGB) stars ([8], [1], [2]). In this framework, we present the first fully consistent computations of rotating low mass and low metallicity stars from the Zero Age Main Sequence (ZAMS) to the upper RGB. 

In a similar fashion, the introduction of angle-dependent electron densities into the EAM suggests that this formalism may be successfully extended to chemical reactions. This would allow the study, for example, of the reaction of a metal-ligand cluster with a metal surface. This would enhance the applicability of the EAM, and would increase the realm of processes which computer simulations can effectively model. 

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