Crystal Prediction via Genetic Algorithms in a Model Chiral System.

Chiral crystals and their constituent molecules play a prominent role in theories about the origin of biological homochirality and in drug discovery, design, and stability. Although the prediction and identification of stable chiral crystal structures is crucial for numerous technologies, including separation processes and polymorph selection and control, predictive ability is often complicated by a combination of many-body interactions and molecular complexity and handedness. In this work, we address these challenges by applying genetic algorithms to predict the ground-state crystal lattices formed by a chiral tetramer molecular model, which we have previously shown to exhibit complex fluid-phase behavior. Using this approach, we explore the relative stability and structures of the model's conglomerate and racemic crystals, and present a structural phase diagram for the stable Bravais crystal types in the zero-temperature limit.

Effect of configuration-dependent multi-body forces on interconversion kinetics of a chiral tetramer model.

We describe a reformulation of the four-site molecular model for chiral phenomena introduced by Latinwo et al. ["Molecular model for chirality phenomena," J. Chem. Phys. 145, 154503 (2016)]. The reformulation includes an additional eight-body force that arises from an explicit configuration-dependent term in the potential energy function, resulting in a coarse-grained energy-conserving force field for molecular dynamics simulations of chirality phenomena. In this model, the coarse-grained interaction energy between two tetramers depends on their respective chiralities and is controlled by a parameter λ, where λ < 0 favors local configurations involving tetramers of opposite chirality and λ > 0 gives energetic preference to configurations involving tetramers of the same chirality. We compute the autocorrelation function for a quantitative chirality metric and demonstrate that the multi-body force modifies the interconversion kinetics such that λ ≠ 0 increases the effective barrier for enantiomer inversion. Our simulations reveal that for λ > 0 and temperatures below a sharply defined threshold value, this effect is dramatic, giving rise to spontaneous chiral symmetry breaking and locking molecules into their chiral identity.

Universal Gas Adsorption Mechanism for Flat Nanobubble Morphologies.

The adsorption of gas molecules at the substrate beneath interfacial nanobubbles modifies the energy of the solid-gas interface, and therefore affects their morphology. In this work, we describe a simple thermodynamic model that captures the influence of gas adsorption and gives flat bubble shapes with reduced gas-side contact angles relative to the zero-adsorption case, in agreement with experimental studies. We show that this effect is general to both hydrophilic and hydrophobic substrates and has a stabilizing influence that extends nanobubble lifetimes.

Coupling discrete and continuum concentration particle models for multiscale and hybrid molecular-continuum simulations.

Hybrid molecular-continuum simulation techniques afford a number of advantages for problems in the rapidly burgeoning area of nanoscale engineering and technology, though they are typically quite complex to implement and limited to single-component fluid systems. We describe an approach for modeling multicomponent hydrodynamic problems spanning multiple length scales when using particle-based descriptions for both the finely resolved (e.g., molecular dynamics) and coarse-grained (e.g., continuum) subregions within an overall simulation domain. This technique is based on the multiscale methodology previously developed for mesoscale binary fluids [N. D. Petsev, L. G. Leal, and M. S. Shell, J. Chem. Phys. 144, 084115 (2016)], simulated using a particle-based continuum method known as smoothed dissipative particle dynamics. An important application of this approach is the ability to perform coupled molecular dynamics (MD) and continuum modeling of molecularly miscible binary mixtures. In order to validate this technique, we investigate multicomponent hybrid MD-continuum simulations at equilibrium, as well as non-equilibrium cases featuring concentration gradients.

Multiscale simulation of ideal mixtures using smoothed dissipative particle dynamics.

Smoothed dissipative particle dynamics (SDPD) [P. Español and M. Revenga, Phys. Rev. E 67, 026705 (2003)] is a thermodynamically consistent particle-based continuum hydrodynamics solver that features scale-dependent thermal fluctuations. We obtain a new formulation of this stochastic method for ideal two-component mixtures through a discretization of the advection-diffusion equation with thermal noise in the concentration field. The resulting multicomponent approach is consistent with the interpretation of the SDPD particles as moving volumes of fluid and reproduces the correct fluctuations and diffusion dynamics. Subsequently, we provide a general multiscale multicomponent SDPD framework for simulations of molecularly miscible systems spanning length scales from nanometers to the non-fluctuating continuum limit. This approach reproduces appropriate equilibrium properties and is validated with simulation of simple one-dimensional diffusion across multiple length scales.

Hybrid molecular-continuum simulations using smoothed dissipative particle dynamics.

We present a new multiscale simulation methodology for coupling a region with atomistic detail simulated via molecular dynamics (MD) to a numerical solution of the fluctuating Navier-Stokes equations obtained from smoothed dissipative particle dynamics (SDPD). In this approach, chemical potential gradients emerge due to differences in resolution within the total system and are reduced by introducing a pairwise thermodynamic force inside the buffer region between the two domains where particles change from MD to SDPD types. When combined with a multi-resolution SDPD approach, such as the one proposed by Kulkarni et al. [J. Chem. Phys. 138, 234105 (2013)], this method makes it possible to systematically couple atomistic models to arbitrarily coarse continuum domains modeled as SDPD fluids with varying resolution. We test this technique by showing that it correctly reproduces thermodynamic properties across the entire simulation domain for a simple Lennard-Jones fluid. Furthermore, we demonstrate that this approach is also suitable for non-equilibrium problems by applying it to simulations of the start up of shear flow. The robustness of the method is illustrated with two different flow scenarios in which shear forces act in directions parallel and perpendicular to the interface separating the continuum and atomistic domains. In both cases, we obtain the correct transient velocity profile. We also perform a triple-scale shear flow simulation where we include two SDPD regions with different resolutions in addition to a MD domain, illustrating the feasibility of a three-scale coupling.

Dynamic equilibrium explanation for nanobubbles' unusual temperature and saturation dependence.

The dynamic equilibrium model suggests that surface nanobubbles can be stable due to an influx of gas in the vicinity of the bubble contact line, driven by substrate hydrophobicity, that balances the outflux of gas from the bubble apex. Here, we develop an alternate formulation of this mechanism that predicts rich behavior in agreement with recent experimental measurements. Namely, we find that stable nanobubbles exist in narrow temperature and dissolved gas concentration ranges, that there is a maximum and minimum possible bubble size, and that nanobubble radii decrease with temperature.