Kristof M. Bal

Merging Metadynamics into Hyperdynamics: Accelerated Molecular Simulations Reaching Time Scales from Microseconds to Seconds

The hyperdynamics method is a powerful tool to simulate slow processes at the atomic level. However, the construction of an optimal hyperdynamics potential is a task that is far from trivial. Here, we propose a generally applicable implementation of the hyperdynamics algorithm, borrowing two concepts from metadynamics. First, the use of a collective variable (CV) to represent the accelerated dynamics gives the method a very large flexibility and simplicity. Second, a metadynamics procedure can be used to construct a suitable history-dependent bias potential on-the-fly, effectively turning the algorithm into a self-learning accelerated molecular dynamics method. This collective variable-driven hyperdynamics (CVHD) method has a modular design: both the local system properties on which the bias is based, as well as the characteristics of the biasing method itself, can be chosen to match the needs of the considered system. As a result, system-specific details are abstracted from the biasing algorithm itself, making it extremely versatile and transparent. The method is tested on three model systems: diffusion on the Cu(001) surface and nickel-catalyzed methane decomposition, as examples of “reactive” processes with a bond-length-based CV, and the folding of a long polymer-like chain, using a set of dihedral angles as a CV. Boost factors up to 109, corresponding to a time scale of seconds, could be obtained while still accurately reproducing correct dynamics.

On the time scale associated with Monte Carlo simulations

Uniform-acceptance force-bias Monte Carlo (fbMC) methods have been shown to be a powerful technique to access longer timescales in atomistic simulations allowing, for example, phase transitions and growth. Recently, a new fbMC method, the time-stamped force-bias Monte Carlo (tfMC) method, was derived with inclusion of an estimated effective timescale; this timescale, however, does not seem able to explain some of the successes the method. In this contribution, we therefore explicitly quantify the effective timescale tfMC is able to access for a variety of systems, namely a simple single-particle, one-dimensional model system, the Lennard-Jones liquid, an adatom on the Cu(100) surface, a silicon crystal with point defects and a highly defected graphene sheet, in order to gain new insights into the mechanisms by which tfMC operates. It is found that considerable boosts, up to three orders of magnitude compared to molecular dynamics, can be achieved for solid state systems by lowering of the apparent activation barrier of occurring processes, while not requiring any system-specific input or modifications of the method. We furthermore address the pitfalls of using the method as a replacement or complement of molecular dynamics simulations, its ability to explicitly describe correct dynamics and reaction mechanisms, and the association of timescales to MC simulations in general.

Establishing Uniform Acceptance in Force Biased Monte Carlo Simulations.

Uniform acceptance force biased Monte Carlo (UFMC) simulations have previously been shown to be a powerful tool to simulate atomic scale processes, enabling one to follow the dynamical path during the simulation. In this contribution, we present a simple proof to demonstrate that this uniform acceptance still complies with the condition of detailed balance, on the condition that the characteristic parameter λ = 1/2 and that the maximum allowed step size is chosen to be sufficiently small. Furthermore, the relation to Metropolis Monte Carlo (MMC) is also established, and it is shown that UFMC reduces to MMC by choosing the characteristic parameter λ = 0 [Rao, M. et al. Mol. Phys.1979, 37, 1773]. Finally, a simple example compares the UFMC and MMC methods.

Effect of plasma-induced surface charging on catalytic processes: application to CO2 activation

Although significant insights have been obtained into chemical and physical properties that govern to the performance of catalysts in traditional thermal processes, the work on electro-, photo-, or plasma-catalytic approaches has been comparatively limited. The effect of (local) surface charges in these processes, while most likely a crucial factor of their activity, has not been well-characterized and is difficult to study in a consistent, isolated manner. Even theoretical calculations, which have traditionally allowed for the untangling of the atomic-level mechanisms underpinning the catalytic process, cannot be readily applied to this class of problems because of their inability to properly treat systems carrying a net charge. Here, we report on a new, generic, and practical approach to deal with charged semiperiodic systems in density functional calculations, which can be readily applied to problems across surface science. Using this method, we investigate the effect of a negative catalyst surface charge on CO

Modelling molecular adsorption on charged or polarized surfaces: a critical flaw in common approaches

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Temperature influence on the reactivity of plasma species on a nickel catalyst surface: An atomic scale study

activation by supported M/Al

Direct observation of realistic-temperature fuel combustion mechanisms in atomistic simulations

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Effect of electric fields on plasma catalytic hydrocarbon oxidation from atomistic simulations

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Atomistic simulations of graphite etching at realistic time scales

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Mechanisms of elementary hydrogen ion-surface interactions during multilayer graphene etching at high surface temperature as a function of flux

(M = Ti, Ni, Cu) single atom catalysts. The presence of an excess electron dramatically improves the reductive power of the catalyst, strongly promoting the splitting of CO