David M. Wilkins

Electrolytes induce long-range orientational order and free energy changes in the H-bond network of bulk water

Ions induce changes in the H-bond network of water that extend by >20 nm, vary for H2O and D2O, and lead to surface tension anomalies. Electrolytes interact with water in many ways: changing dipole orientation, inducing charge transfer, and distorting the hydrogen-bond network in the bulk and at interfaces. Numerous experiments and computations have detected short-range perturbations that extend up to three hydration shells around individual ions. We report a multiscale investigation of the bulk and surface of aqueous electrolyte solutions that extends from the atomic scale (using atomistic modeling) to nanoscopic length scales (using bulk and interfacial femtosecond second harmonic measurements) to the macroscopic scale (using surface tension experiments). Electrolytes induce orientational order at concentrations starting at 10 μM that causes nonspecific changes in the surface tension of dilute electrolyte solutions. Aside from ion-dipole interactions, collective hydrogen-bond interactions are crucial and explain the observed difference of a factor of 6 between light water and heavy water.

Why Quantum Coherence Is Not Important in the Fenna–Matthews–Olsen Complex

We develop and present an improvement to the conventional technique for solving the Hierarchical Equations of Motion (HEOM), which can reduce the memory cost by up to 75% while retaining the same (or even better) convergence rate and accuracy. This allows for a full calculation of the population dynamics of the 24-site FMO trimer for long time scales with very little effort, and we present the first fully converged, exact results for the 7-site subsystem of the monomer, and for the full 24-site trimer. We then show where our exact 7-site results deviate from the approximation of Ishizaki and Fleming [A. Ishizaki and G. R. Fleming, Proc. Natl. Acad. Sci. U.S.A., 2009, 106, 17255]. Our exact results are then compared to calculations using the incoherent Förster theory, and it is found that the time scale of energy transfer is roughly the same, regardless of whether or not coherence is considered. This means that coherence is not likely to improve the efficiency of the transfer. In fact, the incoherent theory often tends to overpredict the rates of energy transfer, suggesting that, in some cases, quantum coherence may actually slow the photosynthetic process.

Nuclear quantum effects in water exchange around lithium and fluoride ions

We employ classical and ring polymer molecular dynamics simulations to study the effect of nuclear quantum fluctuations on the structure and the water exchange dynamics of aqueous solutions of lithium and fluoride ions. While we obtain reasonably good agreement with experimental data for solutions of lithium by augmenting the Coulombic interactions between the ion and the water molecules with a standard Lennard-Jones ion-oxygen potential, the same is not true for solutions of fluoride, for which we find that a potential with a softer repulsive wall gives much better agreement. A small degree of destabilization of the first hydration shell is found in quantum simulations of both ions when compared with classical simulations, with the shell becoming less sharply defined and the mean residence time of the water molecules in the shell decreasing. In line with these modest differences, we find that the mechanisms of the exchange processes are unaffected by quantization, so a classical description of these reactions gives qualitatively correct and quantitatively reasonable results. We also find that the quantum effects in solutions of lithium are larger than in solutions of fluoride. This is partly due to the stronger interaction of lithium with water molecules, partly due to the lighter mass of lithium and partly due to competing quantum effects in the hydration of fluoride, which are absent in the hydration of lithium.

Nuclear Quantum Effects in Water Reorientation and Hydrogen-Bond Dynamics

We combine classical and ring polymer molecular dynamics simulations with the molecular jump model to provide a molecular description of the nuclear quantum effects (NQEs) on water reorientation and hydrogen-bond dynamics in liquid H2O and D2O. We show that while the net NQE is negligible in D2O, it leads to a ∼13% acceleration in H2O dynamics compared to a classical description. Large angular jumps-exchanging hydrogen-bond partners-are the dominant reorientation pathway (just as in a classical description); the faster reorientation dynamics arise from the increased jump rate constant. NQEs do not change the jump amplitude distribution, and no significant tunneling is found. The faster jump dynamics are quantitatively related to decreased structuring of the OO radial distribution function when NQEs are included. This is explained, via a jump model analysis, by competition between the effects of waters librational and OH stretch mode zero-point energies on the hydrogen-bond strength.

Communication: Mean-field theory of water-water correlations in electrolyte solutions

Long-range ion induced water-water correlations were recently observed in femtosecond elastic second harmonic scattering experiments of electrolyte solutions. To further the qualitative understanding of these correlations, we derive an analytical expression that quantifies ion induced dipole-dipole correlations in a non-interacting gas of dipoles. This model is a logical extension of the Debye-Huckel theory that can be used to qualitatively understand how the combined electric field of the ions induces correlations in the orientational distributions of the water molecules in an aqueous solution. The model agrees with the results from molecular dynamics simulations and provides an important starting point for further theoretical work.

Symmetry-Adapted Machine Learning for Tensorial Properties of Atomistic Systems

Statistical learning methods show great promise in providing an accurate prediction of materials and molecular properties, while minimizing the need for computationally demanding electronic structure calculations. The accuracy and transferability of these models are increased significantly by encoding into the learning procedure the fundamental symmetries of rotational and permutational invariance of scalar properties. However, the prediction of tensorial properties requires that the model respects the appropriate geometric transformations, rather than invariance, when the reference frame is rotated. We introduce a formalism that extends existing schemes and makes it possible to perform machine learning of tensorial properties of arbitrary rank, and for general molecular geometries. To demonstrate it, we derive a tensor kernel adapted to rotational symmetry, which is the natural generalization of the smooth overlap of atomic positions kernel commonly used for the prediction of scalar properties at the atomic scale. The performance and generality of the approach is demonstrated by learning the instantaneous response to an external electric field of water oligomers of increasing complexity, from the isolated molecule to the condensed phase.

Second-Harmonic Scattering as a Probe of Structural Correlations in Liquids

Second-harmonic scattering experiments of water and other bulk molecular liquids have long been assumed to be insensitive to interactions between the molecules. The measured intensity is generally thought to arise from incoherent scattering due to individual molecules. We introduce a method to compute the second-harmonic scattering pattern of molecular liquids directly from atomistic computer simulations, which takes into account the coherent terms. We apply this approach to large-scale molecular dynamics simulations of liquid water, where we show that nanosecond second-harmonic scattering experiments contain a coherent contribution arising from radial and angular correlations on a length scale of ≲1 nm, much shorter than had been recently hypothesized ( Shelton , D. P. J. Chem. Phys. 2014 , 141 ). By combining structural correlations from simulations with experimental data ( Shelton , D. P. J. Chem. Phys. 2014 , 141 ), we can also extract an effective molecular hyperpolarizability in the liquid phase. This work demonstrates that second-harmonic scattering experiments and atomistic simulations can be used in synergy to investigate the structure of complex liquids, solutions, and biomembranes, including the intrinsic intermolecular correlations.

Solvent fluctuations and nuclear quantum effects modulate the molecular hyperpolarizability of water

Second-harmonic scattering (SHS) experiments provide a unique approach to probe noncentrosymmetric environments in aqueous media, from bulk solutions to interfaces, living cells, and tissue. A central assumption made in analyzing SHS experiments is that each molecule scatters light according to a constant molecular hyperpolarizability tensor β(2). Here, we investigate the dependence of the molecular hyperpolarizability of water on its environment and internal geometric distortions, in order to test the hypothesis of constant β(2). We use quantum chemistry calculations of the hyperpolarizability of a molecule embedded in point-charge environments obtained from simulations of bulk water. We demonstrate that both the heterogeneity of the solvent configurations and the quantum mechanical fluctuations of the molecular geometry introduce large variations in the nonlinear optical response of water. This finding has the potential to change the way SHS experiments are interpreted: In particular, isotopic differences between H2O and D2O could explain recent SHS observations. Finally, we show that a machine-learning framework can predict accurately the fluctuations of the molecular hyperpolarizability. This model accounts for the microscopic inhomogeneity of the solvent and represents a step towards quantitative modeling of SHS experiments.

Fast-forward Langevin dynamics with momentum flips

Stochastic thermostats based on the Langevin equation, in which a system is coupled to an external heat bath, are popular methods for temperature control in molecular dynamics simulations due to their ergodicity and their ease of implementation. Traditionally, these thermostats suffer from sluggish behavior in the limit of high friction, unlike thermostats of the Nosé-Hoover family whose performance degrades more gently in the strong coupling regime. We propose a simple and easy-to-implement modification to the integration scheme of the Langevin algorithm that addresses the fundamental source of the overdamped behavior of high-friction Langevin dynamics: if the action of the thermostat causes the momentum of a particle to change direction, it is flipped back. This fast-forward Langevin equation preserves the momentum distribution and so guarantees the correct equilibrium sampling. It mimics the quadratic behavior of Nosé-Hoover thermostats and displays similarly good performance in the strong coupling limit. We test the efficiency of this scheme by applying it to a 1-dimensional harmonic oscillator, as well as to water and Lennard-Jones polymers. The sampling efficiency of the fast-forward Langevin equation thermostat, measured by the correlation time of relevant system variables, is at least as good as the traditional Langevin thermostat, and in the overdamped regime, the fast-forward thermostat performs much better, improving the efficiency by an order of magnitude at the highest frictions we considered.

The Molecular Mechanism of Nanodroplet Stability

Mixtures of nano- and microscopic oil droplets in water have recently been rediscovered as miniature reaction vessels in microfluidic environments and are important constituents of many environmental systems, food, personal care, and medical products. The oil nanodroplet/water interface stabilized by surfactants determines the physicochemical properties of the droplets. Surfactants are thought to stabilize nanodroplets by forming densely packed monolayers that shield the oil phase from the water. This idea has been inferred from droplet stability measurements in combination with molecular structural data obtained from extended planar interfaces. Here, we present a molecular level investigation of the surface structure and stability of nanodroplets and show that the surface structure of nanodroplets is significantly different from that of extended planar interfaces. Charged surfactants form monolayers that are more than 1 order of magnitude more dilute than geometrically packed ones, and there is no experimental correlation between stability and surfactant surface density. Moreover, dilute negatively charged surfactant monolayers produce more stable nanodroplets than dilute positively charged and dense geometrically packed neutral surfactant monolayers. Droplet stability is found to depend on the relative cooperativity between charge-charge, charge-dipole, and hydrogen-bonding interactions. The difference between extended planar interfaces and nanoscale interfaces stems from a difference in the thermally averaged total charge-charge interactions in the two systems. Low dielectric oil droplets with a size smaller than the Debye length in oil permit repulsive interactions between like charges from opposing interfaces in small droplets. This behavior is generic and extends up to the micrometer length scale.