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A GPU-accelerated version of the lattice Boltzmann method for efficient simulation of soft materials is introduced. Unlike standard approaches, this method reconstructs the distribution functions from available hydrodynamic variables (density, momentum, and pressure tensor) without storing the full set of discrete populations. This scheme shows satisfactory numerical stability, significantly lower memory requirements, and data access cost. A series of benchmark tests of relevance to soft matter, such as collisions of fluid droplets, is discussed to validate the method. The results can be of particular interest for high-performance simulations of soft matter systems on future exascale computers., Comment: 12 pages, 7 figures

We introduce a combined Restrained MD/Parallel Tempering approach to study the difference in free energy as a function of a set of collective variables between two states in presence of unknown slow degrees of freedom. We applied this method to study the relative stability of the amorphous vs crystalline nanoparticles of size ranging between 0.8 and 1.8 nm as a function of the temperature. We found that, at variance with bulk systems, at low T small nanoparticles are amorphous and undergo an amorphous-to-crystalline phase transition at higher T. On the contrary, large nanoparticles recover the bulk-like behavior: crystalline at low $T$ and amorphous at high T.

We review a dynamical approach to non-equilibrium MD (D-NEMD). We show how, using a proper simulation setup, is possible to treat interesting cases in which the initial condition is a stationary non-equilibrium state produced by a suitable dynamical system. We then extend the class of non-equilibrium phenomena that can be studied by atomistic simulations to the case of complex initial conditions consisting in assigning a macroscopic value of a scalar or vector observable or a field. We illustrate the functioning of this method by applying it to the relaxation of an interface between two immiscible liquids. We have shown that our method generate unbiased results while this might not be the case for the often used short time average approach.

We investigated the relative stability of the amorphous vs crystalline nanoparticles of size ranging between 0.8 and 1.8 nm. We found that, at variance from bulk systems, at low T small nanoparticles are amorphous and they undergo to an amorphous-to-crystalline phase transition at high T. On the contrary, large nanoparticles recover the bulk-like behavior: crystalline at low T and amorphous at high T. We also investigated the structure of crystalline nanoparticles, providing evidence that they are formed by an ordered core surrounded by a disordered periphery. Furthermore, we also provide evidence that the details of the structure of the crystalline core depend on the size of the nanoparticle, Comment: 8 pages, 5 figures