Quantum mechanical simulation technique

In this section we look briefly at the problem of including quantum mechanical effects in computer simulations. We shall only examine tire simplest technique, which exploits an isomorphism between a quantum system of atoms and a classical system of ring polymers, each of which represents a path integral of the kind discussed in [193]. For more details on work in this area, see [22, 194] and particularly [195, 196, 197]. 

Car and Parrinello [202] proposed a teclmique for efficiently solving the Scluodinger equation which has had an enonuous impact on materials simulation (for reviews, see [203. 204. 205. 206]). The technique is an ab initio one, i.e., free of empirical parameters, and is based on the use of a quantum mechanical orthononual... 

This technique for finding a weighted average is used for ideal gas properties and quantum mechanical systems with quantized energy levels. It is not a convenient way to design computer simulations for real gas or condensed-phase... 

Combined Quantum and Molecular Mechanical Simulations. A recentiy developed technique is one wherein a molecular dynamics simulation includes the treatment of some part of the system with a quantum mechanical technique. This approach, QM/MM, is similar to the coupled quantum and molecular mechanical methods introduced by Warshel and Karplus (45) and at the heart of the MMI, MMP2, and MM3 programs by AUinger (60). These latter programs use quantum mechanical methods to treat the TT-systems of the stmctures in question separately from the sigma framework. 

These apparent restrictions in size and length of simulation time of the fully quantum-mechanical methods or molecular-dynamics methods with continuous degrees of freedom in real space are the basic reason why the direct simulation of lattice models of the Ising type or of solid-on-solid type is still the most popular technique to simulate crystal growth processes. Consequently, a substantial part of this article will deal with scientific problems on those time and length scales which are simultaneously accessible by the experimental STM methods on one hand and by Monte Carlo lattice simulations on the other hand. Even these methods, however, are too microscopic to incorporate the boundary conditions from the laboratory set-up into the models in a reahstic way. Therefore one uses phenomenological models of the phase-field or sharp-interface type, and finally even finite-element methods, to treat the diffusion transport and hydrodynamic convections which control a reahstic crystal growth process from the melt on an industrial scale. 

Despite advent of theoretical methods and techniques and faster computers, no single theoretical method seems to be capable of reliable computational studies of reactivities of biocatalysts. Ab initio quantum mechanical (QM) methods may be accurate but are still too expensive to apply to large systems like biocatalysts. Semi-empirical quantum methods are not as accurate but are faster, but may not be fast enough for long time simulation of large molecular systems. Molecular mechanics (MM) force field methods are not usually capable of dealing with bond-breaking and formation... 

Beyond the clusters, to microscopically model a reaction in solution, we need to include a very big number of solvent molecules in the system to represent the bulk. The problem stems from the fact that it is computationally impossible, with our current capabilities, to locate the transition state structure of the reaction on the complete quantum mechanical potential energy hypersurface, if all the degrees of freedom are explicitly included. Moreover, the effect of thermal statistical averaging should be incorporated. Then, classical mechanical computer simulation techniques (Monte Carlo or Molecular Dynamics) appear to be the most suitable procedures to attack the above problems. In short, and applied to the computer simulation of chemical reactions in solution, the Monte Carlo [18-21] technique is a numerical method in the frame of the classical Statistical Mechanics, which allows to generate a set of system configurations... 

Molecular dynamics simulations, with quantum-mechanically derived energy and forces, can provide valuable insights into the dynamics and structure of systems in which electronic excitations or bond breaking processes are important. In these cases, conventional techniques with classical analytical potentials, are not appropriate. Since the quantum mechanical calculation has to be performed many times, one at each time step, the choice of a computationally fast method is crucial. Moreover, the method should be able to simulate electronic excitations and breaking or forming of bonds, in order to provide a proper treatment of those properties for which classical potentials fail. 

Contemporary computer-assisted molecular simulation methods and modern computer technology has contributed to the actual numerical calculation of solvent effects on chemical reactions and molecular equilibria. Classical statistical mechanics and quantum mechanics are basic pillars on which practical approaches are based. On top of these, numerical methods borrowed from different fields of physics and engineering and computer graphics techniques have been integrated into computer programs running in graphics workstations and modem supercomputers (Zhao et al., 2000). 

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