This study focuses on the microscopic modeling of 0–25 keV Bi1–3–5 and C60 cluster impacts on three different targets (Au crystal, adsorbed Au nanoparticle, and organic solid), using molecular dynamics simulations, and on the comparison of the calculated quantities with recent experimental results, reported in the literature or obtained in our laboratory. The sputtering statistics are reported, showing nonlinearity of the sputtering yields with the number of cluster atoms at the same incident velocity for Bi1–5 bombardment. They are compared to experiments (especially for the organic target), and the microscopic explanation of the observations is analyzed. The results show that the respective behaviors and performances of the different projectiles are strongly dependent on the target, with clusters of heavy Bi atoms being more efficient at sputtering gold and, conversely, fullerene clusters inducing the largest sputtering yields of the organic material (mass matching). For organic targets, some important and novel conclusions of this work are the following: (i) The increase of the sputtering yield when going from Bi atoms to Bi clusters is insufficient to explain the much larger increase of characteristic ion yields, suggesting a projectile-dependent ionization probability. (ii) The extent of molecular fragmentation follows the order of Bi > Bi3 > Bi5 > C60, that is, softer emission with larger clusters. (iii) Even 5–10 keV Bi atoms create collective molecular motions and craters in the polymeric solid, though the collision cascades are rather dilute. Finally, a second series of simulations performed at low energies predict that 0.1–1 keV Bi n clusters should not provide better results for sputtering and depth profiling than isoenergetic single atoms.

The compressive behavior of nanocomposite foams is studied by both experimental and computational micro-mechanics approaches with the aim of providing an efficient computational model for this kind of material.The nanocomposites based on polypropylene (PP) and different contents of multi-walled carbon nanotubes (CNTs) method. The nanocomposite samples are foamed using super-critical carbon dioxide (ScCO 2 ) as blowing agent at different soaking temperatures. The influence of this foaming parameter on the morphological characteristics of the foam micro-structure is discussed. Differential Scanning Calorimetry (DSC) measurements are used to quantify the crystallinity degree of both nanocomposites and foams showing that the crystallinity degree is reduced after the foaming process. This modification leads to mechanical properties of the foam cell walls that are different from the raw nanocomposite PP/CNTs material. Three-point bending tests are performed on the latter to measure the flexural modulus in terms of the crystallinity degree. Uniaxial compression tests are then performed on the foamed samples under quasi-static conditions in order to extract the macro-scale compressive response. Next, a two-level multi-scale approach is developed to model the behavior of the foamed nanocomposite material. On the one hand, the micromechanical properties of nanocomposite PP/CNTs cell walls are evaluated from a theoretical homogenization model accounting for the micro-structure of the semi-crystalline PP, for the degree of crystallinity, and for the CNT volume fraction. The applicability of this theoretical model is demonstrated via the comparison with experimental data from the described experimental measurements and from literature. On the other hand, the macroscopic behavior of the foamed material is evaluated using a computational micromechanics model using tetrakaidecahedron unit cells and periodic boundary conditions to estimate the homogenized properties. The unit cell is combined with several geometrical imperfections in order to capture the elastic collapse of the foamed material. The numerical results are compared to the experimental measurements and it is shown that the proposed unit cell computational micro-mechanics model can be used to estimate the homogenized behavior, including the linear and plateau regimes, of nanocomposite foams.

The present article introduces an automated procedure to construct geometrical representative volume elements (RVE) of open‐foam cellular materials from computerized tomography (CT) images, with the final aim of generating meshable geometries usable in the finite element method (FEM) used in order to analyse their mechanical behavior. The methodology consists in growing and fitting a set of ellipsoids to each of the foam cells. These ellipsoids are seeded by local maxima of the distance to the struts obtained from computer tomography images. This methodology is thus fully voxel‐based and does not depend on any assumption about statistical distributions of the foam cells. Therefore, it is able to reproduce an accurate geometrical model of the foam's microstructure and its possible irregularities. Moreover, this procedure allows the processing of large 3D data sets that do not fit the random access memory (RAM) by slicing it into smaller independent chunks. The effectiveness of the proposed approach is illustrated by comparing it to FEM simulations for which meshes are obtained from a feature reconstruction approach. Both FEM simulations are then compared with experimental results of uniaxial compressions of an open foam.

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