Force field methods atom types

Atoms are assigned types , much as in force field methods, i.e. the parameters depend on the nuclear charge and the bonding situation. The a a and /3ab parameters for atom types A and B are related to the corresponding parameters for sp -hybridized carbon by means of dimensionless constants /ia and /cab-... 

Force fields split naturally into two main classes all-atom force fields and united atom force fields. In the former, each atom in the system is represented explicitly by potential functions. In the latter, hydrogens attached to heavy atoms (such as carbon) are removed. In their place single united (or extended) atom potentials are used. In this type of force field a CH2 group would appear as a single spherical atom. United atom sites have the advantage of greatly reducing the number of interaction sites in the molecule, but in certain cases can seriously limit the accuracy of the force field. United atom force fields are most usually required for the most computationally expensive tasks, such as the simulation of bulk liquid crystal phases via molecular dynamics or Monte Carlo methods (see Sect. 5.1). 

To make an accurate FEP calculation, a good description of the system is required. This means that the parameters for the chosen force field must reproduce the dynamic behaviour of both species correctly. A realistic description of the environment, e.g. size of water box, and the treatment of the solute-solvent interaction energy is also required. The majority of the parameters can usually be taken from the standard atom types of a force field. The electrostatic description of the species at both ends of the perturbation is, however, the key to a good simulation of many systems. This is also the part that usually requires tailoring to the system of interest. Most force fields require atom centered charges obtained by fitting to the molecular electrostatic potential (MEP), usually over the van der Waals surface. Most authors in the studies discussed above used RHF/6-31G or higher methods to obtain the MEP. 

A quantitative measure of thermal stability is the lattice energy of the compound. This may be evaluated by the method of atom-atom potentials using the refined atomic positions derived from accurate crystal structure determinations. One may employ force fields of the type ... 

Although a valence-type force field of the type illustrated by Eq. [1] is most suitable for modeling molecular systems, the electronegativity equalization approach to treating polarization can be coupled equally well to other types of potentials. Streitz and Mintmire used an EE-based model in conjunction with an embedded atom method (EAM) potential to treat polarization effects in bulk metals and oxides. The resulting ES + EAM model has been parameterized for aluminum and titanium oxides, and has been used to study both charge-transfer effects and reactivity at interfaces. 

Force field methods use mathematical functions—interatomic potentials— to describe the attraction of different atom types to each other and the strain exerted on the molecular configuration by the presence of other atoms. They have become more elaborate over time, progressing from mainly non-bonded van der Waals interactions to more complicated 4-body terms and shell models of atomic distortion. CmciaUy, however, force field methods do not allow for drastic changes in the electronic configuration of a system—i.e. bond making or breaking—and only describe the system well when the configuration is near equilibrium. 

Force-field methods form the basis of molecular dynamics. They use a parameterised quasi-classical description of interatomic forces to model the trajectory of systems typically composed of hundreds or even thousands of atoms. One good feature of these types of calculations is that with large systems the computational effort increases linearly with the size of the problem. This means that increased computational power allows considerably larger systems to be studied. Further gains can also be made by using parallel processors since energy calculations in molecular dynamics simulations are inherently parallel. 

Molecular modeling has been demonstrated to be a useful tool in the characterization of many different types of chemical systems, including bulk materials. Many properties can be computed with an accuracy that is comparable to experimental capabilities [6]. Simulation of properties is especially important for systems that are challenging to study experimentally due to their limited solubility in common solvents. In some other cases, the experiment itself may be difficult due either to sensitivity to sample preparation or to ambiguities in the interpretation of the results. When the system consists of a relatively small number of atoms, both traditional ab initio and density functional methods can be employed. In the case of sugar molecules and disaccharides, a number of studies have been carried out to develop force field methods [7] to be used in molecular dynamics simulations while studying the conformations of cellulose and its interactions with water and other molecules [8-16]. 

While simulations reach into larger time spans, the inaccuracies of force fields become more apparent on the one hand properties based on free energies, which were never used for parametrization, are computed more accurately and discrepancies show up on the other hand longer simulations, particularly of proteins, show more subtle discrepancies that only appear after nanoseconds. Thus force fields are under constant revision as far as their parameters are concerned, and this process will continue. Unfortunately the form of the potentials is hardly considered and the refinement leads to an increasing number of distinct atom types with a proliferating number of parameters and a severe detoriation of transferability. The increased use of quantum mechanics to derive potentials will not really improve this situation ab initio quantum mechanics is not reliable enough on the level of kT, and on-the-fly use of quantum methods to derive forces, as in the Car-Parrinello method, is not likely to be applicable to very large systems in the foreseeable future. 

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