Real-space grids are a powerful alternative for the simulation of electronic systems. One of the main advantages of the approach is the flexibility and simplicity of working directly in real space where the different fields are discretized on a grid, combined with competitive numerical performance and great potential for parallelization. These properties constitute a great advantage at the time of implementing and testing new physical models. Based on our experience with the Octopus code, in this article we discuss how the real-space approach has allowed for the recent development of new ideas for the simulation of electronic systems. Among these applications are approaches to calculate response properties, modeling of photoemission, optimal control of quantum systems, simulation of plasmonic systems, and the exact solution of the Schrödinger equation for low-dimensionality systems.

A bidimensional cellular automaton model is used to simulate the process of evacuation of pedestrians in a room with fixed obstacles. A floor field is defined so that moving to a cell with lower floor field means approaching an exit door. The model becomes non-deterministic by introducing a ''panic'' parameter, given by a probability of not moving, and by a random choice to resolve conflicts in the update of pedestrian positions. Two types of exit doors are considered: single (where only one person can pass) and double (two persons can pass simultaneously). For a double door, the longest evacuation time turns out to occur for a very traditional location of the door. The optimum door position is determined. Replacing the double door by two single doors does not improve evacuation times noticeably. On the other hand, for a room without obstacles, a simple scaling law is proposed to model the dependence of evacuation time with the number of persons and exit width. This model fails when obstacles are present, as their presence introduces local bottlenecks whose effect outweighs the benefits of increasing door width beyond a certain threshold. r

Light-matter interaction in plasmonic nanostructures is often treated within the realm of classical optics. However, recent experimental findings show the need to go beyond the classical models to explain and predict the plasmonic response at the nanoscale. A prototypical system is a nanoparticle dimer, extensively studied using both classical and quantum prescriptions. However, only very recently, fully ab initio time-dependent density functional theory (TDDFT) calculations of the optical response of these dimers have been carried out. Here, we review the recent work on the impact of the atomic structure on the optical properties of such systems. We show that TDDFT can be an invaluable tool to simulate the time evolution of plasmonic modes, providing fundamental understanding into the underlying microscopical mechanisms

We present an ab initio study of the anisotropy and atomic relaxation effects on the optical properties of nanoparticle dimers. Special emphasis is placed on the hybridization process of localized surface plasmons, plasmon-mediated photoinduced currents, and electric-field enhancement in the dimer junction. We show that there is a critical range of separations between the clusters (0.1-0.5 nm) in which the detailed atomic structure in the junction and the relative orientation of the nanoparticles have to be considered to obtain quantitative predictions for realistic nanoplasmonic devices. It is worth noting that this regime is characterized by the emergence of electron tunneling as a response to the driven electromagnetic field. The orientation of the particles not only modifies the attainable electric field enhancement but can lead to qualitative changes in the optical absorption spectrum of the system.

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An unbiased strategy to search for the global and local minimal energy structures of free standing nanoclusters is presented. Our objectives are twofold: to find a diverse set of low lying local minima, as well as the global minimum. To do so, we use massively the fast inertial relaxation engine algorithm as an efficient local minimizer. This procedure turns out to be quite efficient to reach the global minimum, and also most of the local minima. We test the method with the Lennard-Jones (LJ) potential, for which an abundant literature does exist, and obtain novel results, which include a new local minimum for LJ13 , 10 new local minima for LJ14 , and thousands of new local minima for 15≤N≤65. Insights on how to choose the initial configurations, analyzing the effectiveness of the method in reaching low-energy structures, including the global minimum, are developed as a function of the number of atoms of the cluster. Also, a novel characterization of the potential energy surface, analyzing properties of the local minima basins, is provided. The procedure constitutes a promising tool to generate a diverse set of cluster conformations, both two- and three-dimensional, that can be used as an input for refinement by means of ab initio methods.

The existence of polycrystalline shells has been widely reported in the synthesis of hollow nanoparticles; however, the exact role displayed by the grain boundaries on the stability has been scarcely studied. By including them, in this work, we study for the first time the contribution of the polycrystalline structure in the stability of this unique kind of nanostructures, addressing at the same time, a more realistic modeling of hollow nanoparticles. The role of the polycrystalline structure was studied in gold hollow nanoparticles using molecular dynamics simulations for a wide range of shell thickness and grain sizes. One of the main findings is that the shell thickness necessary for transition from a spherical to a shrunk structure is related to the grain size reduction. The results suggest that to achieve larger hollow nanoparticles, less defective shells are necessary, with single-crystal shells establishing an upper limit in the size that a structure can attain. The cavity shrinkage in a polycrystalline HNP is due to a complex combination of grain diffusion, rotations, dislocation emission, and twining, all of them activated from the grain boundary regions. Our findings suggest that the polycrystalline structure is a crucial parameter to control and improve the stability of the hollow nanoparticles.

Hollow nanoparticle structures play a major role in nanotechnology and nanoscience since their surface to volume ratio is significantly larger than that of filled ones. While porous hollow nanoparticles offer a significant improvement of the available surface area, there is a lack of theoretical understanding, and scarce experimental information, on how the porosity controls or dominates the stability. Here we use classical molecular dynamics simulations to shed light on the particular characteristics and properties of gold porous hollow nanoparticles and how they differ from the nonporous ones. Adopting gold as a prototype, we show how, as the temperature increases, the porosity introduces surface stress and minor transitions that lead to various scenarios, from partial shrinkage for small filling factors to abrupt compression and the loss of spherical shape for large filling. Our work provides new insights into the stability limits of porous hollow nanoparticles, with important implications for the design and practical use of these enhanced geometries.