Diffusion Monte Carlo applications

The material presented above was selected to describe from a unified point of view Monte Carlo algorithms as employed in seemingly unrelated areas in quantum and statistical mechanics. Details of applications were given only to explain general ideas or important technical problems, such as encountered in diffusion Monte Carlo. We ignored a whole body of literature, but we wish to just mention a few topics. Domain Green function Monte Carlo [25-28] is one that comes very close to topics that were... 

The first applications in diffusion Monte Carlo were made for the nodeless ground state of the molecular ion The effect was a substantial improvement in accuracy from -1.3414 0.0043 hartree (-841.74 kcal/mol) for the total energy in an earlier calculation to -1.3439 0.0002 hartree in a similar calculation using importance sampling. The statistical error is reduced by a factor of about 20, and any systematic error is presumed to be similarly reduced. 

J. Xu and K. D. Jordan,/. Phys. Chem. A, 114,1364-1366 (2010). Application of the Diffusion Monte Carlo Method to the Binding of Excess Electrons to Water Clusters. 

Ra]agopal G, Needs R J, James A, Kenney S D and Foulkes W M C 1995 Variational and diffusion quantum Monte Carlo calculations at nonzero wave vectors theory and application to diamond-structure germanium Phys. Rev. B 51 10 591-600... 

This section has illustrated a relatively simple application of the Monte Carlo technique for simulating atmospheric diffusion. With the availability of large-scale computing capacities, Monte Carlo methods can be envi-... 

We review Monte Carlo calculations of phase transitions and ordering behavior in lattice gas models of adsorbed layers on surfaces. The technical aspects of Monte Carlo methods are briefly summarized and results for a wide variety of models are described. Included are calculations of internal energies and order parameters for these models as a function of temperature and coverage along with adsorption isotherms and dynamic quantities such as self-diffusion constants. We also show results which are applicable to the interpretation of experimental data on physical systems such as H on Pd(lOO) and H on Fe(110). Other studies which are presented address fundamental theoretical questions about the nature of phase transitions in a two-dimensional geometry such as the existence of Kosterlitz-Thouless transitions or the nature of dynamic critical exponents. Lastly, we briefly mention multilayer adsorption and wetting phenomena and touch on the kinetics of domain growth at surfaces. 

While the advection-dispersion equation has been used widely over the last half century, there is now widespread recognition that this equation has serious limitations. As noted previously, laboratory and field-scale application of the advection-dispersion equation is based on the assumption that dispersion behaves macroscopically as a Fickian diffusive process, with the dispersivity being assumed constant in space and time. However, it has been observed consistently through field, laboratory, and Monte Carlo analyses that the dispersivity is not constant but, rather, dependent on the time or length scale of measurement (Gelhar et al. 1992),... 

Accdg to Hammersley Handscomb (Addnl Ref N, p 8), S. Ulam, J. von Neumann and E. Fermi independently rediscovered Monte Carlo methods ca 1944 and started its systematic development. They also ensured that their scientific colleagues should become aware of the possibilities, potentialities and physical applications. The real use of Monte Carlo methods as research tools is attributed to von Neumann Ulam who applied them to random neutron diffusion in fissile material... 

Whereas selective diffusion can be better investigated using classical dynamic or Monte Carlo simulations, or experimental techniques, quantum chemical calculations are required to analyze molecular reactivity. Quantum chemical dynamic simulations provide with information with a too limited time scale range (of the order of several himdreds of ps) to be of use in diffusion studies which require time scale of the order of ns to s. However, they constitute good tools to study the behavior of reactants and products adsorbed in the proximity of the active site, prior to the reaction. Concerning reaction pathways analysis, static quantum chemistry calculations with molecular cluster models, allowing estimates of transition states geometries and properties, have been used for years. The application to solids is more recent. 

The main application that was discussed was a microscopic model for the oxidation of CO, catalyzed by a Pt(lOO) single crystal surface. The simulations show kinetic oscillations as well as spatio-temporal pattern formation in the form of target patterns, rotating spirals and turbulent patterns. Finally, mean-field simulations of the same model were compared with the Monte Carlo simulations. When diffusion is fast and the simulation grids are small, the results of Monte Carlo simulations approach those of the mean-field simulations. 

The next section gives a brief overview of the main computational techniques currently applied to catalytic problems. These techniques include ab initio electronic structure calculations, (ab initio) molecular dynamics, and Monte Carlo methods. The next three sections are devoted to particular applications of these techniques to catalytic and electrocatalytic issues. We focus on the interaction of CO and hydrogen with metal and alloy surfaces, both from quantum-chemical and statistical-mechanical points of view, as these processes play an important role in fuel-cell catalysis. We also demonstrate the role of the solvent in electrocatalytic bondbreaking reactions, using molecular dynamics simulations as well as extensive electronic structure and ab initio molecular dynamics calculations. Monte Carlo simulations illustrate the importance of lateral interactions, mixing, and surface diffusion in obtaining a correct kinetic description of catalytic processes. Finally, we summarize the main conclusions and give an outlook of the role of computational chemistry in catalysis and electrocatalysis. 

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