The extremely narrow production peak of N2 and CO2 which occurs in the reaction of NO+CO on Pt(100), a phenomenon known as "surface explosion," is studied using a dynamic Monte Carlo method on a square lattice at low pressure under isothermal conditions. This analysis incorporates recent experimental evidence obtained for the same reaction on a Rh(111) surface, which has shown that N2 production occurs either from the classical N+N recombination step or by the formation and successive decay of a (N-NO)* intermediary species. Moreover, the NO dissociation rate is inhibited by coadsorbed NO and CO molecules and is enhanced both by the presence of empty sites and adsorbed N atoms as nearest neighbors. These effects are taken into account in this study, along with the experimental adsorption, desorption, and diffusion rates of the reactants. The "explosive" phenomenon is analyzed through the evolution over time of an adsorbed NO+CO monolayer at a fixed temperature of 400 K. Furthermore, as the diffusion processes of the adsorbates are included, cellular structures are observed. Our simulations show quantitative agreement in the position of maxima with those obtained through experiments using isothermal desorption mass spectroscopy.

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Kinetic oscillations in the catalytic reduction of NO by CO on a reconstructing Pt(100) surface are simulated by using a dynamic Monte Carlo method. The simulation is based on the HS model and takes into account an alternative reaction mechanism arising from recent experimental findings for the catalytic reduction of No on Rh(111), which replaces the classical N+N recombination step by the formation of a (N-NO)(*) intermediary species for the production of molecular nitrogen. A synchronized mechanism and spatiotemporal patterns are observed during the oscillations. Oscillations are analyzed in terms of the controlling parameters involved in the reaction mechanism. Different values of these parameters lead to sustained, attenuated, and modulated oscillations.

Intracellular protein folding (PF) is performed in a highly inhomogeneous, crowded, and correlated environment. Due to this inherent complexity, the study and understanding of PF phenomena is a fundamental issue in the field of computational systems biology. In particular, it is important to use a modeled medium that accurately reflects PF in natural systems. In the current study, we present a simulation wherein PF is carried out within an inhomogeneous modeled medium. Simulation resources included a two-dimensional hydrophobic-polar (HP) model, evolutionary algorithms, and the dual site-bond model. The dual site-bond model was used to develop an environment where HP beads could be folded. Our modeled medium included correlation lengths and fractal-like behavior, which were selected according to HP sequence lengths to induce folding in a crowded environment. Analysis of three benchmark HP sequences showed that the modeled inhomogeneous space played an important role in deeper energy folding and obtained better performance and convergence compared with homogeneous environments. Our computational approach also demonstrated that our correlated network provided a better space for PF. Thus, our approach represents a major advancement in PF simulations, not only for folding but also for understanding functional chemical structure and physicochemical properties of proteins in crowded molecular systems, which normally occur in nature.