Molecular dynamics cluster applications

Bartell and co-workers have made significant progress by combining electron diffraction studies from beams of molecular clusters with molecular dynamics simulations [14, 51, 52]. Due to their small volumes, deep supercoolings can be attained in cluster beams however, the temperature is not easily controlled. The rapid nucleation that ensues can produce new phases not observed in the bulk [14]. Despite the concern about the appropriateness of the classic model for small clusters, its application appears to be valid in several cases [51]. 

Valiev M, Kowalski K (2006) Hybrid coupled cluster and molecular dynamics approach Application to the excitation spectrum of cytosine in the native DNA environment. J Chem Phys 125 211101... 

I Andricioaei, JE Straub. On Monte Carlo and molecular dynamics methods inspired by Tsallis statistics Methodology, optimization, and application to atomic clusters. J Chem Phys 107 9117-9124, 1997. 

REM has already been used in many applications in protein systems [76-91]. Other molecular simulation fields have also been studied by this method in various ensembles [92-96]. Moreover, REM was applied to cluster studies in quantum chemistry field [97]. The details of molecular dynamics algorithm have been worked out for REM in [77]. This led to a wide application of REM in the protein folding and related problems (see, e.g., [98-115]). 

Unfortunately, quantitatively reliable quantum chemical calculations of nucleation rates for atmospherically relevant systems would require the application of both high-level electronic structure methods and complicated anharmonic thermochemical analysis to large cluster structures. Such computations are therefore computationally too expensive for currently available computer systems, and will likely remain so for the foreseeable future. Instead, a synthesis of different approaches will probably be necessary. In the future, successful nucleation studies are likely to contain combinations of the best features of both classical (Monte Carlo and molecular dynamics) and quantum chemical methods, with the ultimate objective being a chemically accurate, complete configurational sampling. 

First principles approaches are important as they avoid many of the pitfalls associated with using parameterized descriptions of the interatomic interactions. Additionally, simulation of chemical reactivity, reactions and reaction kinetics really requires electronic structure calculations [108]. However, such calculations were traditionally limited in applicability to rather simplistic models. Developments in density functional theory are now broadening the scope of what is viable. Car-Parrinello first principles molecular dynamics are now being applied to real zeolite models [109,110], and the combined use of classical and quantum mechanical methods allows quantum chemical methods to be applied to cluster models embedded in a simpler description of the zeoUte cluster environment [105,111]. 

Bandemer considered the role of fuzzy set theory in analytical chemistry. The applications they described focused on pattern recognition problems, the calibration of analytical methods,quality control, and component identification and mixture evaluation. Gordon and Somorjai applied a fuzzy clustering technique to the detection of similarities among protein substructures. A molecular dynamics trajectory of a protein fragment was analyzed. In the following subsections, some applications based on the hierarchical fuzzy clustering techniques presented in this chapter are reviewed. 

Analysis and control of ultrafast processes in atomic clusters in the size regime in which each atom counts are of particular importance from a conceptual point of view and for opening new perspectives for many applications in the future. Simultaneously, this research area calls for the challenging development of theoretical and computational methods from different directions, including quantum chemistry, molecular dynamics, and optimal control theory, removing borders between them. Moreover, it provides stimulation for new experiments. 

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. 

The first part of the chapter is devoted to non-carbon and fiillerene-like clusters and describes the role of the fullerene molecule in cluster research. The second part addresses one of the most controversial questions concerning the mechanism of formation of the fullerene molecule. The third part reveals the role of of defects of the fullerene molecule and their possible applications. The results of molecular dynamic simulations show the possibility for the production of selected types of defects in the process of atomic implantation. Solid state properties of the fullerene molecule are discussed in the fourth part of the chapter. 

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