Nuclear quantum effects in the acetylene:ammonia plastic co-crystal.

Organic molecular solids can exhibit rich phase diagrams. In addition to structurally unique phases, translational and rotational degrees of freedom can melt at different state points, giving rise to partially disordered solid phases. The structural and dynamic disorder in these materials can have a significant impact on the physical properties of the organic solid, necessitating a thorough understanding of disorder at the atomic scale. When these disordered phases form at low temperatures, especially in crystals with light nuclei, the prediction of material properties can be complicated by the importance of nuclear quantum effects. As an example, we investigate nuclear quantum effects on the structure and dynamics of the orientationally disordered, translationally ordered plastic phase of the acetylene:ammonia (1:1) co-crystal that is expected to exist on the surface of Saturn's moon Titan. Titan's low surface temperature (∼90 K) suggests that the quantum mechanical behavior of nuclei may be important in this and other molecular solids in these environments. By using neural network potentials combined with ring polymer molecular dynamics simulations, we show that nuclear quantum effects increase orientational disorder and rotational dynamics within the acetylene:ammonia (1:1) co-crystal by weakening hydrogen bonds. Our results suggest that nuclear quantum effects are important to accurately model molecular solids and their physical properties in low-temperature environments.

Electronic paddle-wheels in a solid-state electrolyte.

Solid-state superionic conductors (SSICs) are promising alternatives to liquid electrolytes in batteries and other energy storage technologies. The rational design of SSICs and ultimately their deployment in battery technologies is hindered by the lack of a thorough understanding of their ion conduction mechanisms. In SSICs containing molecular ions, rotational dynamics couple with translational diffusion to create a paddle-wheel effect that facilitates conduction. The paddle-wheel mechanism explains many important features of molecular SSICs, but an explanation for ion conduction and anharmonic lattice dynamics in SSICs composed of monatomic ions is still needed. We predict that ion conduction in the classic SSIC AgI involves electronic paddle-wheels, rotational motion of localized electron pairs that couples to and facilitates ion diffusion. The electronic paddle-wheel mechanism creates a universal perspective for understanding ion conductivity in both monatomic and molecular SSICs that will create design principles for engineering solid-state electrolytes from the electronic level up to the macroscale.

Modeling nuclear quantum effects on long-range electrostatics in nonuniform fluids.

Nuclear quantum effects play critical roles in a variety of molecular processes, especially in systems that contain hydrogen and other light nuclei, such as water. For water under ambient conditions, nuclear quantum effects are often interpreted as local effects resulting from a smearing of the hydrogen atom distribution. However, the orientational structure of water at interfaces determines long-range effects, such as electrostatics, through the O-H bond ordering that is impacted by nuclear quantum effects. In this work, I examine nuclear quantum effects on long-range electrostatics of water confined between hydrophobic walls using path integral simulations. To do so, I combine concepts from local molecular field theory with path integral methods at varying levels of approximation to develop efficient and physically intuitive approaches for describing long-range electrostatics in nonuniform quantum systems. Using these approaches, I show that quantum water requires larger electrostatic forces to achieve interfacial screening than the corresponding classical system. This work highlights the subtleties of electrostatics in nonuniform classical and quantum molecular systems, and the methods presented here are expected to be of use to efficiently model nuclear quantum effects in large systems.

Oxide- and Silicate-Water Interfaces and Their Roles in Technology and the Environment.

Interfacial reactions drive all elemental cycling on Earth and play pivotal roles in human activities such as agriculture, water purification, energy production and storage, environmental contaminant remediation, and nuclear waste repository management. The onset of the 21st century marked the beginning of a more detailed understanding of mineral aqueous interfaces enabled by advances in techniques that use tunable high-flux focused ultrafast laser and X-ray sources to provide near-atomic measurement resolution, as well as by nanofabrication approaches that enable transmission electron microscopy in a liquid cell. This leap into atomic- and nanometer-scale measurements has uncovered scale-dependent phenomena whose reaction thermodynamics, kinetics, and pathways deviate from previous observations made on larger systems. A second key advance is new experimental evidence for what scientists hypothesized but could not test previously, namely, interfacial chemical reactions are frequently driven by "anomalies" or "non-idealities" such as defects, nanoconfinement, and other nontypical chemical structures. Third, progress in computational chemistry has yielded new insights that allow a move beyond simple schematics, leading to a molecular model of these complex interfaces. In combination with surface-sensitive measurements, we have gained knowledge of the interfacial structure and dynamics, including the underlying solid surface and the immediately adjacent water and aqueous ions, enabling a better definition of what constitutes the oxide- and silicate-water interfaces. This critical review discusses how science progresses from understanding ideal solid-water interfaces to more realistic systems, focusing on accomplishments in the last 20 years and identifying challenges and future opportunities for the community to address. We anticipate that the next 20 years will focus on understanding and predicting dynamic transient and reactive structures over greater spatial and temporal ranges as well as systems of greater structural and chemical complexity. Closer collaborations of theoretical and experimental experts across disciplines will continue to be critical to achieving this great aspiration.

Dielectric Saturation in Water from a Long-Range Machine Learning Model.

Machine learning-based neural network potentials have the ability to provide ab initio-level predictions while reaching large length and time scales often limited to empirical force fields. Traditionally, neural network potentials rely on a local description of atomic environments to achieve this scalability. These local descriptions result in short-range models that neglect long-range interactions necessary for processes like dielectric screening in polar liquids. Several approaches to including long-range electrostatic interactions within neural network models have appeared recently, and here we investigate the transferability of one such model, the self-consistent field neural network (SCFNN), which focuses on learning the physics associated with long-range response. By learning the essential physics, one can expect that such a neural network model should exhibit at least partial transferability. We illustrate this transferability by modeling dielectric saturation in a SCFNN model of water. We show that the SCFNN model can predict nonlinear response at high electric fields, including saturation of the dielectric constant, without training the model on these high field strengths and the resulting liquid configurations. We then use these simulations to examine the nuclear and electronic structure changes underlying dielectric saturation. Our results suggest that neural network models can exhibit transferability beyond the linear response regime and make genuine predictions when the relevant physics is properly learned.

Local Molecular Field Theory for Coulomb Interactions in Aqueous Solutions.

Coulomb interactions play a crucial role in a wide array of processes in aqueous solutions but present conceptual and computational challenges to both theory and simulations. We review recent developments in an approach addressing these challenges─local molecular field (LMF) theory. LMF theory exploits an exact and physically suggestive separation of intermolecular Coulomb interactions into strong short-range and uniformly slowly varying long-range components. This allows us to accurately determine the averaged effects of the long-range components on the short-range structure using effective single particle fields and analytical corrections, greatly reducing the need for complex lattice summation techniques used in most standard approaches. The simplest use of these ideas in aqueous solutions leads to the short solvent (SS) model, where both solvent-solvent and solute-solvent Coulomb interactions have only short-range components. Here we use the SS model to give a simple description of pairing of nucleobases and biologically relevant ions in water.

Superhydrophilicity of α-alumina surfaces results from tight binding of interfacial waters to specific aluminols.

HYPOTHESIS: Understanding the microscopic driving force of water wetting is challenging and important for design of materials. The relations between structure, dynamics and hydrogen bonds of interfacial water can be investigated using molecular dynamics simulations. EXPERIMENTS AND SIMULATIONS: Contact angles at the alumina (0001) and (112‾0) surfaces are studied using both classical molecular dynamics simulations and experiments. To test the superhydrophilicity, the free energy cost of removing waters near the interfaces are calculated using the density fluctuations method. The strength of hydrogen bonds is determined by their lifetime and geometry. FINDINGS: Both surfaces are superhydrophilic and the (0001) surface is more hydrophilic. Interactions between surfaces and interfacial waters promote a templating effect whereby the latter are aligned in a pattern that follows the underlying lattice of the surfaces. Translational and rotational dynamics of interfacial water molecules are slower than in bulk water. Hydrogen bonds between water and both surfaces are asymmetric, water-to-aluminol ones are stronger than aluminol-to-water ones. Molecular dynamics simulations eliminate the impacts of surface contamination when measuring contact angles and the results reveal the microscopic origin of the macroscopic superhydrophilicity of alumina surfaces: strong water-to-aluminol hydrogen bonds.

Self-consistent determination of long-range electrostatics in neural network potentials.

Machine learning has the potential to revolutionize the field of molecular simulation through the development of efficient and accurate models of interatomic interactions. Neural networks can model interactions with the accuracy of quantum mechanics-based calculations, but with a fraction of the cost, enabling simulations of large systems over long timescales. However, implicit in the construction of neural network potentials is an assumption of locality, wherein atomic arrangements on the nanometer-scale are used to learn interatomic interactions. Because of this assumption, the resulting neural network models cannot describe long-range interactions that play critical roles in dielectric screening and chemical reactivity. Here, we address this issue by introducing the self-consistent field neural network - a general approach for learning the long-range response of molecular systems in neural network potentials that relies on a physically meaningful separation of the interatomic interactions - and demonstrate its utility by modeling liquid water with and without applied fields.

Uptake, Trapping, and Release of Organometallic Cations by Redox-Active Cationic Hosts.

The host-guest chemistry of metal-organic nanocages is typically driven by thermodynamically favorable interactions with their guests such that uptake and release of guests can be controlled by switching this affinity on or off. Herein, we achieve this effect by reducing porphyrin-walled cationic nanoprisms 1a12+ and 1b12+ to zwitterionic states that rapidly uptake organometallic cations Cp*2Co+ and Cp2Co+, respectively. Cp*2Co+ binds strongly (Ka = 1.3 × 103 M-1) in the neutral state 1a0 of host 1a12+, which has its three porphyrin walls doubly reduced and its six (bipy)Pt2+ linkers singly reduced (bipy = 2,2'-bipyridine). The less-reduced states of the host 1a3+ and 1a9+ also bind Cp*2Co+, though with lower affinities. The smaller Cp2Co+ cation binds strongly (Ka = 1.7 × 103 M-1) in the 3e- reduced state 1b9+ of the (tmeda)Pt2+-linked host 1b12+ (tmeda = N,N,N',N'-tetramethylethylenediamine). Upon reoxidation of the hosts with Ag+, the guests become trapped to provide unprecedented metastable cation-in-cation complexes Cp*2Co+@1a12+ and Cp2Co+@1b12+ that persist for >1 month. Thus, dramatic kinetic effects reveal a way to confine the guests in thermodynamically unfavorable environments. Experimental and DFT studies indicate that PF6- anions kinetically stabilize Cp*2Co+@1a12+ through electrostatic interactions and by influencing conformational changes of the host that open and close its apertures. However, when Cp*2Co+@1a12+ was prepared using ferrocenium (Fc+) instead of Ag+ to reoxidize the host, dissociation was accelerated >200× even though neither Fc+ nor Fc have any observable affinity for 1a12+. This finding shows that metastable host-guest complexes can respond to subtler stimuli than those required to induce guest release from thermodynamically favorable complexes.

Ion-dependent protein-surface interactions from intrinsic solvent response.

The phyllosilicate mineral muscovite mica is widely used as a surface template for the patterning of macromolecules, yet a molecular understanding of its surface chemistry under varying solution conditions, required to predict and control the self-assembly of adsorbed species, is lacking. We utilize all-atom molecular dynamics simulations in conjunction with an electrostatic analysis based in local molecular field theory that affords a clean separation of long-range and short-range electrostatics. Using water polarization response as a measure of the electric fields that arise from patterned, surface-bound ions that direct the adsorption of charged macromolecules, we apply a Landau theory of forces induced by asymmetrically polarized surfaces to compute protein-surface interactions for two muscovite-binding proteins (DHR10-mica6 and C98RhuA). Comparison of the pressure between surface and protein in high-concentration KCl and NaCl aqueous solutions reveals ion-specific differences in far-field protein-surface interactions, neatly capturing the ability of ions to modulate the surface charge of muscovite that in turn selectively attracts one binding face of each protein over all others.

Intercalation-deintercalation of water-in-salt electrolytes in nanoscale hydrophobic confinement.

Intercalation-deintercalation of water-in-salt (WIS) electrolytes in nanoscale confinement is an important phenomenon relevant to energy storage and self-assembly applications. In this article, we use molecular simulations to investigate the effects of intersurface separation on the structure and free energy underlying the intercalation-deintercalation of the Li bis(trifluoromethane)sulfonimide ([Li][TFSI]) water-in-salt (WIS) electrolyte confined between nanoscale hydrophobic surfaces. We employ enhanced sampling to estimate the free energy profiles for the intercalation behaviour of WIS in confining sheets at several intersurface separations. We observe that the relative stability of the condensed and vapour phases of WIS in the confinement depends on the separation between the confining surfaces and the WIS concentration. We find that the critical separation at which the condensed and vapour phases are equally stable in confinement depends on the concentration of WIS. The relative height of the free energy barrier also strongly depends on the concentration of [Li][TFSI] inside the confined space, and we find that this concentration dependence can be attributed to changes in line tension. The process of deintercalation passes through vapour tube formation inside the confined space, and this process is initiated by vapour bubble formation. The size of the critical vapour tube required for spontaneous evaporation of WIS from the confinement is also found to depend on the intersurface separation and WIS concentration.

Effective mass path integral simulations of quasiparticles in condensed phases.

The quantum many-body problem in condensed phases is often simplified using a quasiparticle description, such as effective mass theory for electron motion in a periodic solid. These approaches are often the basis for understanding many fundamental condensed phase processes, including the molecular mechanisms underlying solar energy harvesting and photocatalysis. Despite the importance of these effective particles, there is still a need for computational methods that can explore their behavior on chemically relevant length and time scales. This is especially true when the interactions between the particles and their environment are important. We introduce an approach for studying quasiparticles in condensed phases by combining effective mass theory with the path integral treatment of quantum particles. This framework incorporates the generally anisotropic electronic band structure of materials into path integral simulation schemes to enable modeling of quasiparticles in quantum confinement, for example. We demonstrate the utility of effective mass path integral simulations by modeling an exciton in solid potassium chloride and electron trapping by a sulfur vacancy in monolayer molybdenum disulfide.

Liquid-Liquid Phase Transitions in Silicon.

We use computationally simple neutral pseudoatom ("average atom") density functional theory (DFT) and standard DFT to elucidate liquid-liquid phase transitions (LPTs) in liquid silicon. An ionization-driven transition and three LPTs including the known LPT near 2.5 g/cm^{3} are found. They are robust even to 1 eV. The pair distributions functions, pair potentials, electrical conductivities, and compressibilites are reported. The LPTs are elucidated within a Fermi liquid picture of electron scattering at the Fermi energy that complements the transient covalent bonding picture.

Molecular Simulation of Covalent Bond Dynamics in Liquid Silicon.

Many atomic liquids can form transient covalent bonds reminiscent of those in the corresponding solid states. These directional interactions dictate many important properties of the liquid state, necessitating a quantitative, atomic-scale understanding of bonding in these complex systems. A prototypical example is liquid silicon, wherein transient covalent bonds give rise to local tetrahedral order and consequent nontrivial effects on liquid-state thermodynamics and dynamics. To further understand covalent bonding in liquid silicon, and similar liquids, we present an ab initio-simulation-based approach for quantifying the structure and dynamics of covalent bonds in condensed phases. Through the examination of structural correlations among silicon nuclei and maximally localized Wannier function centers, we develop a geometric criterion for covalent bonds in liquid Si. We use this to monitor the dynamics of transient covalent bonding in the liquid state and estimate a covalent bond lifetime. We compare covalent bond dynamics to other processes in liquid Si and similar liquids and suggest experiments to measure the covalent bond lifetime.

Lone Pair Rotational Dynamics in Solids.

Traditional classifications of crystalline phases focus on nuclear degrees of freedom. Through the examination of both electronic and nuclear structure, we introduce the concept of an electronic plastic crystal. Such a material is classified by crystalline nuclear structure, while localized electronic degrees of freedom-here lone pairs-exhibit orientational motion at finite temperatures. This orientational motion is an emergent phenomenon arising from the coupling between electronic structure and polarization fluctuations generated by collective motions, such as phonons. Using ab initio molecular dynamics simulations, we predict the existence of electronic plastic crystal motion in halogen crystals and halide perovskites, and suggest that such motion may be found in a broad range of solids with lone pair electrons. Such fluctuations in the charge density should be observable, in principle, via synchrotron scattering.

Short solvent model for ion correlations and hydrophobic association.

Coulomb interactions play a major role in determining the thermodynamics, structure, and dynamics of condensed-phase systems, but often present significant challenges. Computer simulations usually use periodic boundary conditions to minimize corrections from finite cell boundaries but the long range of the Coulomb interactions generates significant contributions from distant periodic images of the simulation cell, usually calculated by Ewald sum techniques. This can add significant overhead to computer simulations and hampers the development of intuitive local pictures and simple analytic theory. In this paper, we present a general framework based on local molecular field theory to accurately determine the contributions from long-ranged Coulomb interactions to the potential of mean force between ionic or apolar hydrophobic solutes in dilute aqueous solutions described by standard classical point charge water models. The simplest approximation leads to a short solvent (SS) model, with truncated solvent-solvent and solute-solvent Coulomb interactions and long-ranged but screened Coulomb interactions only between charged solutes. The SS model accurately describes the interplay between strong short-ranged solute core interactions, local hydrogen-bond configurations, and long-ranged dielectric screening of distant charges, competing effects that are difficult to capture in standard implicit solvent models.

Halogen Bond Structure and Dynamics from Molecular Simulations.

Halogen bonding has emerged as an important noncovalent interaction in a myriad of applications, including drug design, supramolecular assembly, and catalysis. The current understanding of the halogen bond is informed by electronic structure calculations on isolated molecules and/or crystal structures that are not readily transferable to liquids and disordered phases. To address this issue, we present a first-principles simulation-based approach for quantifying halogen bonds in molecular systems rooted in an understanding of nuclei-nuclei and electron-nuclei spatial correlations. We then demonstrate how this approach can be used to quantify the structure and dynamics of halogen bonds in condensed phases, using solid and liquid molecular chlorine as prototypical examples with high concentrations of halogen bonds. We close with a discussion of how the knowledge generated by our first-principles approach may inform the development of classical empirical models, with a consistent representation of halogen bonding.

Characterizing Solvent Density Fluctuations in Dynamical Observation Volumes.

Hydrophobic effects drive diverse aqueous assemblies, such as micelle formation or protein folding, wherein the solvent plays an important role. Consequently, characterizing the free energetics of solvent density fluctuations can lead to important insights into these processes. Although techniques such as the indirect umbrella sampling (INDUS) method can be used to characterize solvent fluctuations in static observation volumes of various sizes and shapes, characterizing how the solvent mediates inherently dynamic processes, such as self-assembly or conformational change, remains a challenge. In this work, we generalize the INDUS method to facilitate the enhanced sampling of solvent fluctuations in dynamical observation volumes, whose positions and shapes can evolve. We illustrate the usefulness of this generalization by characterizing water density fluctuations in dynamical volumes pertaining to the hydration of flexible solutes, the assembly of small hydrophobes, and conformational transitions in a model peptide. We also use the method to probe the dynamics of hard spheres.

Exponential Scaling of Water Exchange Rates with Ion Interaction Strength from the Perspective of Dynamic Facilitation Theory.

Water exchange reactions around ionic solutes are ubiquitous in aqueous solution-phase chemistry. However, the extreme sensitivity of exchange rates to perturbations in the chemistry of an ionic solute is not well understood. We examine water exchange around model ions within the language of dynamic facilitation theory, typically used to describe glassy and other systems with collective, facilitated dynamics. Through the development of a coarse-grained, kinetically constrained lattice model of water exchange, we show that the time scale for water exchange scales exponentially with the strength of the solute-solvent interactions.