Trung Dac Nguyen

Simulating chemically reactive phenomena such as proton transport on nanosecond to microsecond and beyond time- scales is a challenging task. Ab initio methods are unable to currently access these timescales routinely, and traditional molecular dynamics methods feature fixed bonding arrangements that cannot account for changes in the system’s bonding topology. The Mul- tiscale Reactive Molecular Dynamics (MS-RMD) method, as implemented in the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) software package for the LAMMPS molecular dynamics code, offers a method to routinely sample longer timescale reactive simulation data with statistical precision. RAPTOR may also be interfaced with enhanced sampling methods to drive simulations towards the analysis of reactive rare events, and a number of collective variables (CVs) have been developed to facilitate this. Key advances to this methodology, including GPU acceleration efforts and novel CVs to model water wire formation are reviewed, along with recent applications of the method which demonstrate its versatility and robustness.

Molecular simulations are an important tool for research in physics, chemistry, and biology. The capabilities of simulations can be greatly expanded by providing access to advanced sampling methods and techniques that permit calculation of the relevant underlying free energy landscapes. In this sense, software that can be seamlessly adapted to a broad range of complex systems is essential. Building on past efforts to provide open-source community-supported software for advanced sampling, we introduce PySAGES, a Python implementation of the Software Suite for Advanced General Ensemble Simulations (SSAGES) that provides full GPU support for massively parallel applications of enhanced sampling methods such as adaptive biasing forces, harmonic bias, or forward flux sampling in the context of molecular dynamics simulations. By providing an intuitive interface that facilitates the management of a system’s configuration, the inclusion of new collective variables, and the implementation of sophisticated free energy-based sampling methods, the PySAGES library serves as a general platform for the development and implementation of emerging simulation techniques. The capabilities, core features, and computational performance of this tool are demonstrated with clear and concise examples pertaining to different classes of molecular systems. We anticipate that PySAGES will provide the scientific community with a robust and easily accessible platform to accelerate simulations, improve sampling, and enable facile estimation of free energies for a wide range of materials and processes.

Colloidal nanocrystals of metals, semiconductors, and other functional materials can self-assemble into long-range ordered crystalline and quasicrystalline phases, but insulating organic surface ligands prevent the development of collective electronic states in ordered nanocrystal assemblies. We reversibly self-assembled colloidal nanocrystals of gold, platinum, nickel, lead sulfide, and lead selenide with conductive inorganic ligands into supercrystals exhibiting optical and electronic properties consistent with strong electronic coupling between the constituent nanocrystals. The phase behavior of charge-stabilized nanocrystals can be rationalized and navigated with phase diagrams computed for particles interacting through short-range attractive potentials. By finely tuning interparticle interactions, the assembly was directed either through one-step nucleation or nonclassical two-step nucleation pathways. In the latter case, the nucleation was preceded by the formation of two metastable colloidal fluids.

Mesoscopic clusters composed of oppositely charged particles are ubiquitous in synthetic and biological soft materials. The effective interaction between these clusters is influenced by their polarizability, that is, the ability of their constituent charges to re-arrange in response to an external electrical field. Here, using coarse-grained simulations, we show that the polarizability of electrically neutral ionic clusters decreases as the number of constituent charges increases and/or their Coulombic interaction strength increases for various ion valencies, ion densities, and degrees of cluster boundary hardness. For clusters of random ionomers and their counterions, their polarizability is shown to depend on the number of polymer chains. The variation of the cluster polarizability with the cluster size indicates that throughout the assembly, the induced-dipole interactions between the clusters may be reduced substantially as they acquire more charges while maintaining zero net charge. Under certain conditions, the induced-dipole interactions may become repulsive, as inferred from our simulations with a polarizable solvent. As a result, the dipole-induced related interactions can serve as a counterbalancing force that contributes to the self-limiting aggregation of charge-containing assemblies.

Significance: Molecular electrolytes under confinement are crucial materials for energy storage devices and commonly used model systems for understanding biomolecular functions. In particular, understanding the complex interplay of entropy and electrostatic interactions in a polyelectrolyte solution confined inside oppositely charged surfaces gives us important insights into its energy storage and capacitance properties. Here, using molecular dynamics simulations, we analyze polyelectrolyte solutions confined between two oppositely charged planar surfaces with a much lower dielectric constant. We find that such mismatch of dielectric constants and chain flexibility significantly influence the energy storage capability and capacitance of such a confined system. Dielectric mismatch enhances surface charge amplification in flexible polyelectrolyte solutions, increasing their energy storage capabilities.

Solid polymer electrolytes are considered a promising alternative to traditional liquid electrolytes in energy storage applications because of their good mechanical properties, and excellent thermal and chemical stability. A gap, however, still exists in understanding ion transport mechanisms and improving ion transport in solid polymer electrolytes. Therefore, it is crucial to bridge composition–structure and structure–property relationships. Here we demonstrate that size asymmetry, λ, represented by the ratio of counterion to charged monomer size, plays a key role in both the nanostructure and in the ionic dynamics. More specifically, when the nanostructure is modified by the external electric field such that the mobility cannot be described by linear response theory, two situations arise. The ionic mobility increases as λ decreases (small counterions) in the weak electrostatics (high dielectric constant) regime. Whereas in systems with strong electrostatic interactions, ionomers with higher size symmetry (λ ≈ 1) display higher ionic mobility. Moreover, ion transport is found to be dominated by the hopping of the ions and not by moving ionic clusters (also known as “vehicular” charge transport). These results serve as a guide for designing ion-containing polymers for ion transport related applications.

Significance: The hydration of molecules affects their physical and chemical properties. In particular, the functions and interactions of various proteins are determined by the conformation of water molecules around polar and nonpolar protein surface domains. Therefore, understanding the local interactions between water molecules and the polar and nonpolar protein surface domains such as water molecule conformations in protein hydration layers benefits targeted protein engineering, and recognition of molecules including proteins, DNA/RNA, cell membranes, and drugs. By using atomistic simulations, we show distinct correlations between the hydration water molecules and the different types of protein surface domains.