Density functional theory quantum mechanics/molecular dynamic

Schwenk CF, Loffler HH et al (2001) Molecular dynamics simulations of Ca2+ in water comparison of a classical simulation including three-body corrections and Born-Oppenheimer ab initio and density functional theory quantum mechanical/molecular mechanics simulations. I Chem Phys 115 10808... 

It is now 15 years after the publication of the famous paper by Roberto Car and Michele ParrineUo (1985) on the integration of the quantum mechanical method, density-functional theory, with classical molecular dynamics. By... 

Hybrid Quantum Mechanical/Molecular Dynamics Simulations for Parallel Computers Density Functional Theory on Real-Space Multigrids. 

Equation (4-5) can be directly utilized in statistical mechanical Monte Carlo and molecular dynamics simulations by choosing an appropriate QM model, balancing computational efficiency and accuracy, and MM force fields for biomacromolecules and the solvent water. Our group has extensively explored various QM/MM methods using different quantum models, ranging from semiempirical methods to ab initio molecular orbital and valence bond theories to density functional theory, applied to a wide range of applications in chemistry and biology. Some of these studies have been discussed before and they are not emphasized in this article. We focus on developments that have not been often discussed. 

Quantum mechanical methods follow a similar path, except that the starting point is the solution of the Schrodinger equation for the system under investigation. The most successful and widely used method is that of Density Functional Theory. Once again, a key point is the development of a realistic model that can serve as the input to the computer investigation. Energy minimization, molecular dynamics, and Monte Carlo methods can all be employed in this process. 

A review of the Journal of Physical Chemistry A, volume 110, issues 6 and 7, reveals that computational chemistry plays a major or supporting role in the majority of papers. Computational tools include use of large Gaussian basis sets and density functional theory, molecular mechanics, and molecular dynamics. There were quantum chemistry studies of complex reaction schemes to create detailed reaction potential energy surfaces/maps, molecular mechanics and molecular dynamics studies of larger chemical systems, and conformational analysis studies. Spectroscopic methods included photoelectron spectroscopy, microwave spectroscopy circular dichroism, IR, UV-vis, EPR, ENDOR, and ENDOR induced EPR. The kinetics papers focused on elucidation of complex mechanisms and potential energy reaction coordinate surfaces. 

Abbreviations MD, molecular dynamics TST, transition state theory EM, energy minimization MSD, mean square displacement PFG-NMR, pulsed field gradient nuclear magnetic resonance VAF, velocity autocorrelation function RDF, radial distribution function MEP, minimum energy path MC, Monte Carlo GC-MC, grand canonical Monte Carlo CB-MC, configurational-bias Monte Carlo MM, molecular mechanics QM, quantum mechanics FLF, Hartree-Fock DFT, density functional theory BSSE, basis set superposition error DME, dimethyl ether MTG, methanol to gasoline. 

During the past few decades, various theoretical models have been developed to explain the physical properties and to find key parameters for the prediction of the system behaviors. Recent technological trends focus toward integration of subsystem models in various scales, which entails examining the nanophysical properties, subsystem size, and scale-specified numerical analysis methods on system level performance. Multi-scale modeling components including quantum mechanical (i.e., density functional theory (DFT) and ab initio simulation), atom-istic/molecular (i.e., Monte Carlo (MC) and molecular dynamics (MD)), mesoscopic (i.e., dissipative particle dynamics (DPD) and lattice Boltzmann method (LBM)), and macroscopic (i.e., LBM, computational... 

The above experimental developments represent powerful tools for the exploration of molecular structure and dynamics complementary to other techniques. However, as is often the case for spectroscopic techniques, only interactions with effective and reliable computational models allow interpretation in structural and dynamical terms. The tools needed by EPR spectroscopists are from the world of quantum mechanics (QM), as far as the parameters of the spin Hamiltonian are concerned, and from the world of molecular dynamics (MD) and statistical thermodynamics for the simulation of spectral line shapes. The introduction of methods rooted into the Density Functional Theory (DFT) represents a turning point for the calculations of spin-dependent properties [7],... 

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]. 

Figure 5. Molecular modeling methods at various scales. MO-miolecular orbital DFT-density functional theory TB-tight binding QM/MM-4iybrid quantum mechanics/molecular mechanics MD nolecnlar dynamics.

Twenty years ago Car and Parrinello introduced an efficient method to perform Molecular Dynamics simulation for classical nuclei with forces computed on the fly by a Density Functional Theory (DFT) based electronic calculation [1], Because the method allowed study of the statistical mechanics of classical nuclei with many-body electronic interactions, it opened the way for the use of simulation methods for realistic systems with an accuracy well beyond the limits of available effective force fields. In the last twenty years, the number of applications of the Car-Parrinello ab-initio molecular d3mam-ics has ranged from simple covalent bonded solids, to high pressure physics, material science and biological systems. There have also been extensions of the original algorithm to simulate systems at constant temperature and constant pressure [2], finite temperature effects for the electrons [3], and quantum nuclei [4]. 

By far the major computational quantum mechanical method used to compute the electronic state in Car-Parrinello simulations is density-functional theory (DFT) (Hohenberg and Kohn, 1964 Kohn and Sham, 1965 Parr and Yang, 1989). It is the method used originally by Roberto Car and Michele Parrinello in 1985, and it provides the highest level of accuracy for the computational cost. For these reasons, in this section the only computational quantum mechanical method discussed is DFT. Section A consists of a brief review of classical molecular dynamics methods. Following this is a description of DFT in general (Section B) and then a description of practical DFT computations of chemical systems using the plane-wave pseudopotential method (Section C). The section ends with a description of the Car-Parrinello method and some basic issues involved in its use (Section D). 

A comprehensive overview of quantum mechanics is given by Cohen-Tannoudji et al. (1977), and another good book is by Levine (2000). A staple text on solid-state physics is by Ashcroft and Mermin (1976). A thorough introduction to density-functional theory is given by Parr and Yang (1989). Two good books to learn more about molecular dynamics simulations are by Allen and Tildesley (1987) and Frenkel and Smit (1996). To learn more about pseudopotential methods, two sources with which to begin are by Pickett (1989) and Bachelet et al. (1982). 

The role of CI2 and monochloroacetic acid in the selective chlorination is a difficult problem to understand from the experimental studies. There are several possible orientations for the reactant, product and promoter molecules inside the complex structure of zeolite-L. In this context, it is pertinent to note that molecular modelling techniques are contributing in considerable amount to understand the reaction mechanisms. Molecular modelling includes force field based calculations [3] such as energy minimisation, Monte Carlo, and molecular dynamics calculations and quantum chemical calculations [4 ] such as EHMO, CNDO/INDO, MOPAC, Hartree-Fock and density functional theory calculations. In this study, we have attempted to apply the combination of molecular graphics, force field calculations and quantum chemical calculations to understand the mechanism of selective chlorination of DCB to TCB over zeolite K-L promoted by monochloroacetic acid. 

---