We combine an analytically solvable mean-field elasto-plastic model with molecular dynamics simulations of a generic glass former to demonstrate that, depending on their preparation protocol, amorphous materials can yield in two qualitatively distinct ways. We show that well-annealed systems yield in a discontinuous brittle way, as metallic and molecular glasses do. Yielding corresponds in this case to a first-order nonequilibrium phase transition. As the degree of annealing decreases, the first-order character becomes weaker and the transition terminates in a second-order critical point in the universality class of an Ising model in a random field. For even more poorly annealed systems, yielding becomes a smooth crossover, representative of the ductile rheological behavior generically observed in foams, emulsions, and colloidal glasses. Our results show that the variety of yielding behaviors found in amorphous materials does not necessarily result from the diversity of particle interactions or microscopic dynamics but is instead unified by carefully considering the role of the initial stability of the system.

We combine an analytically solvable mean-field elasto-plastic model with molecular dynamics simulations of a generic glass former to demonstrate that, depending on their preparation protocol, amorphous materials can yield in two qualitatively distinct ways. We show that well-annealed systems yield in a discontinuous brittle way, as metallic and molecular glasses do. Yielding corresponds in this case to a first-order nonequilibrium phase transition. As the degree of annealing decreases, the first-order character becomes weaker and the transition terminates in a second-order critical point in the universality class of an Ising model in a random field. For even more poorly annealed systems, yielding becomes a smooth crossover, representative of the ductile rheological behavior generically observed in foams, emulsions, and colloidal glasses. Our results show that the variety of yielding behaviors found in amorphous materials does not necessarily result from the diversity of particle interactions or microscopic dynamics but is instead unified by carefully considering the role of the initial stability of the system.

Understanding the fracture behavior of glasses at the atomic scale is of fundamental impor-tance for improving the mechanical properties of these materials. Using an interaction potentialthat has been parametrized via ab initio calculations [1,2], we have carried out molecular dy-namics simulations in order to investigate the influences of system size, sample geometry, andstrain rate on the fracture behavior of sodium silicate glasses. In contrast to earlier simulationstudies on fracture, in which the bulk glass sample has often been put directly under stress, wehave applied here uniaxial tension to a glass sample that has stress-free surfaces, i.e. we adopta setup that is close to the one used in experiments on fracture studies. Our results show thatthe used interatomic potential captures reasonably well the brittle fracture on the nanoscale ofsilica glass and the enhanced ductility when sodium oxide is added to the glass network. Wehave found that below a critical strain rate of around 0.5/ns the stress-strain curve remainsbasically unchanged. By investigating the formation, growth and coalescence of cavities in thestrained glass samples we find that in sodium silicate glasses the formation of cavities is beingmore pronounced than in silica glass. The analysis of atomic energy, local stress and strain, andatomic displacements have confirmed the presence and the development of mechanically weakzones in the glass network, resulting in paths along which the cracks advance.A. Carré, S. Ispas, J. Horbach, and W. Kob, ”Developing empirical potentials from ab initiosimulations: The case of amorphous silica,” Comput. Mater. Sci., vol. 124, pp. 323–334, Nov.2016.S. Sundararaman, L. Huang, S. Ispas, and W. Kob, ”New optimization scheme to obtain inter-action potentials for oxide glasses”, to be sumitted (2017)

The vibrational properties of silica glass under pressure have been intensively studied experimentally during the last four decades, in particular using Raman spectroscopy. However there are few theoretical studies of the evolution of the vibrational properties under pressure.By using a combination of classical and first principles molecular simulations, we have generated a series of structural models for amorphous silica for pressures between 0 and 12 GPa. Further, their vibrational density of states and infrared spectra have been calculated within the density functional theory framework, known to reliably predict these properties, at least at zero pressure.In this talk, we will discuss the evolution of the vibrational features (band positions and peak intensities) of our models under pressure, focusing on their correlation to the structural changes as well as to the variation of their elastic moduli.

Many theoretical works have attempted to coarse grain gene expression at the level of transcription and translation via frameworks based on exclusion processes. Usually in these models the three-dimensional conformation of the substrates (DNA and mRNA) is neglected, and particles move on a static unidimensional lattice in contact to an infinite reservoir. In this work we generalise the paradigmatic exclusion process and study the transport of particles along a unidimensional polymer-like flexible lattice immersed in a three-dimensional particle reservoir. We study the recycling of particles in the reservoir, how the transport is influenced by the conformation of the lattice and, in turn, how particle density dictates the structure of the polymer.

One of the greatest challenges in biophysical models of translation is to identify coding sequence features that affect the rate of translation and therefore the overall protein production in the cell. We propose an analytic method to solve a translation model based on the inhomogeneous totally asymmetric simple exclusion process, which allows us to unveil simple design principles of nucleotide sequences determining protein production rates. Our solution shows an excellent agreement when compared to numerical genome-wide simulations of S. cerevisiae transcript sequences and predicts that the first 10 codons, which is the ribosome footprint length on the mRNA, together with the value of the initiation rate, are the main determinants of protein production rate under physiological conditions. Finally, we interpret the obtained analytic results based on the evolutionary role of the codons’ choice for regulating translation rates and ribosome densities.