Mapping continuous potentials to discrete forms

Fast event-driven simulations for soft spheres: from dynamics to Laves phase nucleation

Conventional molecular dynamics (MD) simulations struggle when simulating particles with steeply varying interaction potentials due to the need to use a very short time step. Here, we demonstrate that an event-driven Monte Carlo (EDMC) approach was first introduced by Peters and de With [Phys. Rev. E 85, 026703 (2012)] and represents an excellent substitute for MD in the canonical ensemble. In addition to correctly reproducing the static thermodynamic properties of the system, the EDMC method closely mimics the dynamics of systems of particles interacting via the steeply repulsive Weeks-Chandler-Andersen (WCA) potential. In comparison to time-driven MD simulations, EDMC runs faster by over an order of magnitude at sufficiently low temperatures. Moreover, the lack of a finite time step in EDMC circumvents the need to trade accuracy against the simulation speed associated with the choice of time step in MD. We showcase the usefulness of this model to explore the phase behavior of the WCA model at extremely low temperatures and to demonstrate that spontaneous nucleation and growth of the Laves phases are possible at temperatures significantly lower than previously reported.

Generalized equation of state for fluids: From molecular liquids to colloidal dispersions

In this work, a new parameterization for the Statistical Association Fluid Theory for potentials of Variable Range (SAFT-VR) is coupled to the discrete potential theory to represent the thermodynamic properties of several fluids, ranging from molecular liquids to colloidal-like dispersions. In this way, this version of the SAFT-VR approach can be straightforwardly applied to any kind of either simple or complex fluid. In particular, two interaction potentials, namely, the Lennard-Jones and the hard-core attractive Yukawa potentials, are discretized to study the vapor-liquid equilibrium properties of both molecular and complex liquids, respectively. Our results are assessed with Monte Carlo computer simulations and available and accurate theoretical results based on the self-consistent Ornstein-Zernike approximation.

A Discontinuous Potential Model for Protein-Protein Interactions

Protein-protein interactions play an important role in many biologic and industrial processes. In this work, we develop a two-bead-per-residue model that enables us to account for protein-protein interactions in a multi-protein system using discontinuous molecular dynamics simulations. This model deploys discontinuous potentials to describe the non-bonded interactions and virtual bonds to keep proteins in their native state. The geometric and energetic parameters are derived from the potentials of mean force between sidechain-sidechain, sidechain-backbone, and backbone-backbone pairs. The energetic parameters are scaled with the aim of matching the second virial coefficient of lysozyme reported in experiment. We also investigate the performance of several bond-building strategies.