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This article compares the experimental results obtained in metal-assisted secondary ion mass spectrometry of polymers, with molecular dynamics simulations involving hybrid metal-organic surfaces. The theoretical sputtering yields are in agreement with the trends highlighted in recent experiments, in which different projectiles (Ga + , C + 60 ) were used to bombard pristine and Au-covered polymer samples. In the experiments, the link between the organic ion yield enhancement/decrease and the fraction of the surface covered by the metal is clearly established. On the other hand, the simulations show that the position of the impact point on the metal-covered surface critically influences the calculated yields of metal and organic material, in a manner that depends on the projectile. The discussion analyzes the information obtained from the simulations and the experiments to propose a mechanism of yield enhancement.

The properties of materials, even at the atomic level, evolve on macroscopic time scales. Following this evolution through simulation has been a challenge for many years. For lattice-based activated di↵usion, kinetic Monte Carlo has turned out to be an almost perfect solution. Various accelerated molecular dynamical schemes, for their part, have allowed the study on long time scale of relatively simple systems. There is still a need, however, for methods able to handle complex materials such as alloys and disordered systems. Here, we review the kinetic Activation-Relaxation Technique (k-ART), one of a handful of o↵-lattice kinetic Monte Carlo methods, with on-the-fly cataloging, that have been proposed in the last few years.

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Oil and gas infrastructures are submitted to extreme conditions and off‐shore rigs and petrochemical installations require expensive high‐quality materials to limit damaging failures. Yet, due to a lack of microscopic understanding, most of these materials are developed and selected based on empirical evidence leading to over‐qualified infrastructures. Computational efforts are necessary, therefore, to identify the link between atomistic and macroscopic scales and support the development of better targeted materials for this and other energy industry. As a first step towards understanding carburization and metal dusting, we assess the capabilities of an embedded atom method (EAM) empirical force field as well as those of a ReaxFF force field using two different parameter sets to describe carbon diffusion at the surface of Fe, comparing the adsorption and diffusion of carbon into the 110 surface and in bulk of α‐iron with equivalent results produced by density functional theory (DFT). The EAM potential has been previously used successfully for bulk Fe–C systems. Our study indicates that preference for C adsorption site, the surface to subsurface diffusion of C atoms and their migration paths over the 110 surface are in good agreement with DFT. The ReaxFF potential is more suited for simulating the hydrocarbon reaction at the surface while the subsequent diffusion to subsurface and bulk is better captured with the EAM potential. This result opens the door to a new approach for using empirical potentials in the study of complex material set‐ups.

In this contribution, we compare the results of our recent molecular dynamics simulations with data already published by us and by other authors to identify the relevant physical parameters governing observables such as the range, the damaged volume, the crater shape, the sputtering yield, the emission of molecules and fragments, and the chemical reactions induced in organic solids by cluster projectiles. Among the considered physical quantities, we show for instance that the total cluster energy, the energy per atom/per nucleon in the cluster and, importantly, the mass matching between the cluster and target constituents have a major effect on the physics of the interaction. The evolution of the observables as a function of these basic physical parameters is illustrated and discussed as well as certain implications for organic surface characterization using cluster ion beams.