Avoidance and Coalescence of Delamination Patterns

Delamination of coatings and thin films from substrates generates a fascinating variety of patterns, from circular blisters to wrinkles and labyrinth domains, in a way that is not completely understood. We report on large-scale numerical simulations of the universal problem of avoidance and coalescence of delamination wrinkles, focusing on a case study of graphene sheets on patterned substrates. By nucleating and growing wrinkles in a controlled way, we are able to characterize how their interactions, mediated by long-range stress fields, determine their formation and morphology. We also study how the interplay between geometry and stresses drives a universal transition from conformation to delamination when sheets are deposited on particle-decorated substrates. Our results are directly applicable to strain engineering of graphene and also uncover universal phenomena observed at all scales, as for example in geomembrane deposition

Universal Features in the Genome-level Evolution of Protein Domains

Protein domains are found on genomes with notable statistical distributions, which bear a high degree of similarity. Previous work has shown how these distributions can be accounted for by simple models, where the main ingredients are probabilities of duplication, innovation, and loss of domains. However, no one so far has addressed the issue that these distributions follow definite trends depending on protein-coding genome size only. We present a stochastic duplication/innovation model, falling in the class of so-called Chinese Restaurant Processes, able to explain this feature of the data. Using only two universal parameters, related to a minimal number of domains and to the relative weight of innovation to duplication, the model reproduces two important aspects: (a) the populations of domain classes (the sets, related to homology classes, containing realizations of the same domain in different proteins) follow common power-laws whose cutoff is dictated by genome size, and (b) the number of domain families is universal and markedly sublinear in genome size. An important ingredient of the model is that the innovation probability decreases with genome size. We propose the possibility to interpret this as a global constraint given by the cost of expanding an increasingly complex interactome. Finally, we introduce a variant of the model where the choice of a new domain relates to its occurrence in genomic data, and thus accounts for fold specificity. Both models have general quantitative agreement with data from hundreds of genomes, which indicates the coexistence of the well-known specificity of proteomes with robust self-organizing phenomena related to the basic evolutionary ``moves'' of duplication and innovation

A link between short-range and long-range properties of random sphere packings

We present a high precision particle-by-particle 3D reconstruction of granular systems composed of monodispersed spheres (sphere packings); the experimental approach is based on magnetic resonance imaging techniques. Our measurements revealed a strong correlation between the volume defined by the distance to the first nearest neighbor and the long-range average density. The main contribution to the amplitude decay of the correlation function can be described as exponential rather than power law up to a range equal to 7 sphere diameters. No evidence of geometrical structural changes as a function of the density was observed and neither regular crystallites nor any other statistically significant structures could be ascribed to a specific local arrangement. We concluded that granular compaction is the result of a process through which the system changes the average size of local structures without changing their local geometrical characteristics. These conclusions are supported by two-body correlation functions and Voronoi polyhedra space decomposition. The results provide a different perspective on the mechanisms underlying compaction with respect to previous works, and allow to discriminate between the different existing theoretical approaches

Fractional Brownian motion and anomalous diffusion in vibrated granular materials

We propose a new approach to the study of diffusion dynamics in vibrated granular systems. The dynamic of a granular material is mainly defined by dry friction interactions. This type of interaction is difficult to model for a large quantity of particles. In this work, we study a granular system by analyzing the angular position time series of an immersed torsion oscillator and of an identical, torsionally unconstrained probe. In order to interpret the behavior of our mechanical system, the experiments are compared to simulations. We generate simulated time series using a simple model of a confined random walk. The global properties of the recorded signals, both experimental and simulated, are extracted by applying fractal signal processing analysis. We show that the Hurst exponent of the time series can be employed to discriminate the dynamics of the system. We conclude that the immersed probe behaves as a Brownian particle that can switch between three distinct dynamical regimes, depending on the strength of the torsional constraint applied to it. If the probe is strongly constrained, its trail can be described with a fractal Brownian motion showing anomalous diffusion (subdiffusive behavior). As the strength of the constraint is reduced, the system 'unjams' in a ordinary Brownian motion (normal diffusion). Finally, as the constraints are further reduced, we observe the onset of convection phenomena, which in turn induce a superdiffusive behavior

High-Precision MRI Reconstruction Algorithm for 3D Sphere Packings

Packings of granular materials are complex systems consisting of large sets of particles interacting via contact forces. Their internal structure is interesting for several theoretical and practical reasons, especially when the model system consists in a large amount (up to 105) of identical spheres. We herein present a method to process three-dimensional water density maps recorded in wet granular packings of mm-size spheres by magnetic resonance imaging (MRI). Packings of spheres with highly mono-dispersed diameter are considered and the implementation of an ad hoc reconstruction algorithm tailored for this feature allows for the determination of the position of each single sphere with an unprecedented precision (with respect to the scale of the system) while ensuring that all spheres are identified and no non-existing sphere is introduced in the reconstructed packing. The reconstruction of a 0.5 L sample containing about 2 × 104 spheres is presented to demonstrate the robustness of the method

Direct Observation of Percolation in the Yielding Transition of Colloidal Glasses

When strained beyond the linear regime, soft colloidal glasses yield to steady-state plastic flow in a way that is similar to the deformation of conventional amorphous solids. Because of the much larger size of the colloidal particles with respect to the atoms comprising an amorphous solid, colloidal glasses allow us to obtain microscopic insight into the nature of the yielding transition, as we illustrate here combining experiments, atomistic simulations, and mesoscopic modeling. Our results unanimously show growing clusters of nonaffine deformation percolating at yielding. In agreement with percolation theory, the spanning cluster is fractal with a fractal dimension df≃2, and the correlation length diverges upon approaching the critical yield strain. These results indicate that percolation of highly nonaffine particles is the hallmark of the yielding transition in disordered glassy systems.Peer reviewe

Atomic-Scale Front Propagation at the Onset of Frictional Sliding

Macroscopic frictional sliding emerges from atomic-scale interactions and processes at the contact interface, but bridging the gap between micro and macro scales still remains an unsolved challenge. Direct imaging of the contact surface and simultaneous measurement of stress fields during macroscopic frictional slip revealed the formation of crack precursors, questioning the traditional picture of frictional contacts described in terms of a single degree of freedom. Here we study the onset of frictional slip on the atomic scale by simulating the motion of an aluminum block pushed by a slider on a copper substrate. We show the formation of dynamic slip front propagation and precursory activity that resemble macroscopic observations. The analysis of stress patterns during slip, however, reveals subtle effects due to the lattice structures that hinder a direct application of linear elastic fracture mechanics. Our results illustrate that dynamic front propagation arises already on the atomic scales and shed light on the connections between atomic-scale and macroscopic friction

Atomic-Scale Front Propagation at the Onset of Frictional Sliding

Macroscopic frictional sliding emerges from atomic-scale interactions and processes at the contact interface, but bridging the gap between micro and macro scales still remains an unsolved challenge. Direct imaging of the contact surface and simultaneous measurement of stress fields during macroscopic frictional slip revealed the formation of crack precursors, questioning the traditional picture of frictional contacts described in terms of a single degree of freedom. Here we study the onset of frictional slip on the atomic scale by simulating the motion of an aluminum block pushed by a slider on a copper substrate. We show the formation of dynamic slip front propagation and precursory activity that resemble macroscopic observations. The analysis of stress patterns during slip, however, reveals subtle effects due to the lattice structures that hinder a direct application of linear elastic fracture mechanics. Our results illustrate that dynamic front propagation arises already on the atomic scales and shed light on the connections between atomic-scale and macroscopic friction