Collective hydrogen-bond rearrangement dynamics in liquid water

Coexistence of Cationic and Anionic Phosphate Moieties in Solids: Unusual but Not Impossible

Phosphoric acid is commonly known either as a neutral molecule or as an anion (phosphate). We theoretically confirm by ab initio molecular dynamics simulations (AIMD) that a cationic form H4PO4+ coexists with the anionic form H2PO4- in the same salt. This paradoxical situation is achieved by partial substitution of Cs+ by H4PO4+ in CsH2PO4. Thus, HnPO4 acts simultaneously as both the positive and the negative ion of the salt. We analyze the dynamical protonation pattern within the unusual hydrogen bond network that is established between the ions. Our AIMD simulations show that a conventional assignment of protonation states of the phosphate groups is not meaningful. Instead, a better description of the protonation situation is achieved by an efficiently fractional assignment of the strongly hydrogen-bonded protons to both its nearest and next-nearest oxygen neighbors.

Role of Charge Ordering in the Dynamics of Cluster Formation in Associated Liquids

Liquids are archetypes of disordered systems, yet liquids of polar molecules are locally more ordered than nonpolar molecules, due to the Coulomb interaction based charge ordering phenomenon. Hydrogen bonded liquids, such as water or alcohols, for example, represent a special type of polar liquids, in that they form labile clustered local structures. For water, in particular, hydrogen bonding and the related local tetrahedrality, play an important role in the various attempts to understand this liquid. However, labile structures imply dynamics, and it is not clear how it affects the understanding of this type of liquids from purely static point of view. Herein, we propose to reconsider hydrogen bonding as a charge ordering process. This concept allows us to demonstrate the insufficiency of the analysis of the microscopic structure based solely on static pair correlation functions, and the need for dynamical correlation functions, both in real and reciprocal space. The subsequent analysis allows to recover several aspects of our understanding of hydrogen bonded liquids, but from the charge order perspective. For water, it confirms the jump rotation picture found recently, and it allows to rationalize the contradicting pictures that arise when following the interpretations based on hydrogen bonding. For alcohols, it allows to understand the dynamical origin of the scattering prepeak, which does not exist for water, despite the fact that both these liquids have very similar hydroxyl group chain clusters. The concept of charge ordering complemented by the analysis of dynamical correlation functions appear as a promising way to understand microheterogeneity in complex liquids and mixtures from kinetics point of view.

The collective burst mechanism of angular jumps in liquid water

Understanding the microscopic origins of collective reorientational motions in aqueous systems requires techniques that allow us to reach beyond our chemical imagination. Herein, we elucidate a mechanism using a protocol that automatically detects abrupt motions in reorientational dynamics, showing that large angular jumps in liquid water involve highly cooperative orchestrated motions. Our automatized detection of angular fluctuations, unravels a heterogeneity in the type of angular jumps occurring concertedly in the system. We show that large orientational motions require a highly collective dynamical process involving correlated motion of many water molecules in the hydrogen-bond network that form spatially connected clusters going beyond the local angular jump mechanism. This phenomenon is rooted in the collective fluctuations of the network topology which results in the creation of defects in waves on the THz timescale. The mechanism we propose involves a cascade of hydrogen-bond fluctuations underlying angular jumps and provides new insights into the current localized picture of angular jumps, and its wide use in the interpretations of numerous spectroscopies as well in reorientational dynamics of water near biological and inorganic systems. The role of finite size effects, as well as of the chosen water model, on the collective reorientation is also elucidated.

From room temperature to harsh temperature applications: Fundamentals and perspectives on electrolytes in zinc metal batteries

As one of the most competitive candidates for the next-generation energy storage systems, the emerging rechargeable zinc metal battery (ZMB) is inevitably influenced by beyond-room-temperature conditions, resulting in inferior performances. Although much attention has been paid to evaluating the performance of ZMBs under extreme temperatures in recent years, most academic electrolyte research has not provided adequate information about physical properties or practical testing protocols of their electrolytes, making it difficult to assess their true performance. The growing interest in ZMBs is calling for in-depth research on electrolyte behavior under harsh practical conditions, which has not been systematically reviewed yet. Hence, in this review, we first showcase the fundamentals behind the failure of ZMBs in terms of temperature influence and then present a comprehensive understanding of the current electrolyte strategies to improve battery performance at harsh temperatures. Last, we offer perspectives on the advance of ZMB electrolytes toward industrial application.

Time-Dependent Friction Effects on Vibrational Infrared Frequencies and Line Shapes of Liquid Water

From ab initio simulations of liquid water, the time-dependent friction functions and time-averaged nonlinear effective bond potentials for the OH stretch and HOH bend vibrations are extracted. The obtained friction exhibits not only adiabatic contributions at and below the vibrational time scales but also much slower nonadiabatic contributions, reflecting homogeneous and inhomogeneous line broadening mechanisms, respectively. Intermolecular interactions in liquid water soften both stretch and bend potentials compared to the gas phase, which by itself would lead to a red-shift of the corresponding vibrational bands. In contrast, nonadiabatic friction contributions cause a spectral blue shift. For the stretch mode, the potential effect dominates, and thus, a significant red shift when going from gas to the liquid phase results. For the bend mode, potential and nonadiabatic friction effects are of comparable magnitude, so that a slight blue shift results, in agreement with well-known but puzzling experimental findings. The observed line broadening is shown to be roughly equally caused by adiabatic and nonadiabatic friction contributions for both the stretch and bend modes in liquid water. Thus, the quantitative analysis of the time-dependent friction that acts on vibrational modes in liquids advances the understanding of infrared vibrational frequencies and line shapes.

Atomistic description of molecular binding processes based on returning probability theory

The efficiency of molecular binding such as host-guest binding is commonly evaluated in terms of kinetics, such as rate coefficients. In general, to compute the coefficient of the overall binding process, we need to consider both the diffusion of reactants and barrier crossing to reach the bound state. Here, we develop a methodology of quantifying the rate coefficient of binding based on molecular dynamics simulation and returning probability (RP) theory proposed by Kim and Lee [J. Chem. Phys. 131, 014503 (2009)]. RP theory provides a tractable formula of the rate coefficient in terms of the thermodynamic stability and kinetics of the intermediate state on a predefined reaction coordinate. In this study, the interaction energy between reactants is utilized as the reaction coordinate, enabling us to effectively describe the reactants' relative position and orientation on one-dimensional space. Application of this method to the host-guest binding systems, which consist of β-cyclodextrin and small guest molecules, yields the rate coefficients consistent with the experimental results.

A Machine Learning Model to Classify Dynamic Processes in Liquid Water*

The dynamics of water molecules plays a vital role in understanding water. We combined computer simulation and deep learning to study the dynamics of H-bonds between water molecules. Based on ab initio molecular dynamics simulations and a newly defined directed Hydrogen (H-) bond population operator, we studied a typical dynamic process in bulk water: interchange, in which the H-bond donor reverses roles with the acceptor. By designing a recurrent neural network-based model, we have successfully classified the interchange and breakage processes in water. We have found that the ratio between them is approximately 1 : 4, and it hardly depends on temperatures from 280 to 360 K. This work implies that deep learning has the great potential to help distinguish complex dynamic processes containing H-bonds in other systems.

Transition pathway of hydrogen bond switching in supercooled water analyzed by the Markov state model

In this work, we examine hydrogen-bond (H-bond) switching by employing the Markov State Model (MSM). During the H-bond switching, a water hydrogen initially H-bonded with water oxygen becomes H-bonded to a different water oxygen. MSM analysis was applied to trajectories generated from molecular dynamics simulations of the TIP4P/2005 model from a room-temperature state to a supercooled state. We defined four basis states to characterize the configuration between two water molecules: H-bonded ("H"), unbound ("U"), weakly H-bonded ("w"), and alternative H-bonded ("a") states. A 16 × 16 MSM matrix was constructed, describing the transition probability between states composed of three water molecules. The mean first-passage time of the H-bond switching was estimated by calculating the total flux from the HU to UH states. It is demonstrated that the temperature dependence of the mean first-passage time is in accordance with that of the H-bond lifetime determined from the H-bond correlation function. Furthermore, the flux for the H-bond switching is decomposed into individual pathways that are characterized by different forms of H-bond configurations of trimers. The dominant pathway of the H-bond switching is found to be a direct one without passing through such intermediate states as "w" and "a," the existence of which becomes evident in supercooled water. The pathway through "w" indicates a large reorientation of the donor molecule. In contrast, the pathway through "a" utilizes the tetrahedral H-bond network, which is revealed by the further decomposition based on the H-bond number of the acceptor molecule.

Volume-scaled common nearest neighbor clustering algorithm with free-energy hierarchy

The combination of Markov state modeling (MSM) and molecular dynamics (MD) simulations has been shown in recent years to be a valuable approach to unravel the slow processes of molecular systems with increasing complexity. While the algorithms for intermediate steps in the MSM workflow such as featurization and dimensionality reduction have been specifically adapted to MD datasets, conventional clustering methods are generally applied to the discretization step. This work adds to recent efforts to develop specialized density-based clustering algorithms for the Boltzmann-weighted data from MD simulations. We introduce the volume-scaled common nearest neighbor (vs-CNN) clustering that is an adapted version of the common nearest neighbor (CNN) algorithm. A major advantage of the proposed algorithm is that the introduced density-based criterion directly links to a free-energy notion via Boltzmann inversion. Such a free-energy perspective allows a straightforward hierarchical scheme to identify conformational clusters at different levels of a generally rugged free-energy landscape of complex molecular systems.

Equilibria and Dynamics of Sodium Citrate Aqueous Solutions: The Hydration of Citrate and Formation of the Na3Cit0 Ion Aggregate

Sodium citrate (Na₃Cit) has a crucial role in many biological and industrial processes. Yet, quantitative information on its hydration and the ion association between Na⁺ and Cit^3- ions in a broad range of salt concentrations is still lacking. In this work, we study both ion association equilibria and relaxation dynamics of sodium citrate solutions by combining potentiometry, spectrophotometry, and dielectric spectroscopy. From photometric and potentiometric measurements, we detect the formation of the NaCit^2- ion-pair and the neutral Na₃Cit⁰ ion aggregate in a wide range of ionic strengths (0.5-4 M). Due to its remarkable stability, the latter becomes the prevailing species at higher salt concentrations. In the dielectric spectra, we observe the dipolar relaxation of Cit^3- and NaCit^2- and two solvent-related processes, associated with the collective rearrangement of the H-bond network (cooperative water mode) and the H-bond flip of water molecules (fast water mode). Unlike numerous other salt solutions, the relaxation time of the cooperative mode scales with the viscosity indicating that the strongly hydrated anion fits well into the water network. That is, the stabilizing effect of anion-solvent interactions on the H-bond network outweighs the destructive impact of the cations as the latter are only present at low concentration, due to strong ion association. In conclusion, the affinity of citrate toward Na⁺ binding not only governs solution equilibria but also has a strong impact on water dynamics.

Highly precise characterization of the hydration state upon thermal denaturation of human serum albumin using a 65 GHz dielectric sensor

The biological functions of proteins depend on harmonization with hydration water surrounding them. Indeed, the dynamical transition of proteins, such as thermal denaturation, is dependent on the changes in the mobility of hydration water. However, the role of hydration water during dynamical transition is yet to be fully understood due to technical limitations in precisely characterizing the amount of hydration water. A state-of-the-art CMOS dielectric sensor consisting of 65 GHz LC resonators addressed this issue by utilizing the feature that oscillation frequency sensitively shifts in response to the complex dielectric constant at 65 GHz with extremely high precision. This study aimed to establish an analytical algorithm to derive the hydration number from the measured frequency shift and to demonstrate the transition of hydration number upon the thermal denaturation of human serum albumin. The determined hydration number in the native state drew a "global" hydration picture beyond the first solvation shell, with substantially reduced uncertainty of the hydration number (about ±1%). This allowed the detection of a rapid increase in the hydration number at about 55 °C during the heating process, which was in excellent phase with the irreversible rupture of the α-helical structure into solvent-exposed extended chains, whereas the hydration number did not trace the forward path in the subsequent cooling process. Our result indicates that the weakening of water hydrogen bonds trigger the unfolding of the protein structure first, followed by the changes in the number of hydration water as a consequence of thermal denaturation.

Strategy on Persisting in Distinct Activity of Plasmon-Activated Water

The innovative plasmon-activated water (PAW) with reduced hydrogen bonds exhibits intrinsically distinct properties at room temperature, which are significantly different from the properties of untreated conventional deionized (DI) water. Examples of this are their ability to scavenge free radicals and higher vapor pressure. However, distinct properties of energetic PAW decay within the day after its creation in a metastable liquid state. In this work, we report a facile method for persisting its distinct activities by letting as-prepared PAW be quickly frozen in liquid nitrogen and letting the frozen PAW (for one month before further measurements) be quickly melted to room temperature in a warm-water bath (called treated PAW). Experimental results indicate that the activity of the higher evaporation rate of treated PAW compared to DI water can be maintained ca. 90% of magnitude, as compared to the as-prepared PAW. Also, its abilities to scavenge free hydroxyl and 2,2-diphenyl-1-picrylhydrazyl radicals can be maintained at ca. 70 and 80% of magnitudes, respectively. Moreover, this strategy of quickly freezing and melting treatments to PAW on persisting in distinct activity of PAW is effective in oxygen evolution reactions. This promises the stored energy and the distinct property of created liquid PAW being available in water-related fields after long-term storage.

Entropic barriers in the kinetics of aqueous proton transfer

Aqueous proton transport is uniquely rapid among aqueous processes, mediated by fluctuating hydrogen bond reorganization in liquid water. In a process known as Grotthuss diffusion, the excess charge diffuses primarily by sequential proton transfers between water molecules rather than standard Brownian motion, which explains the anomalously high electrical conductivity of acidic solutions. Employing ultrafast IR spectroscopy, we use the orientational anisotropy decay of the bending vibrations of the hydrated proton complex to study the picosecond aqueous proton transfer kinetics as a function of temperature, concentration, and counterion. We find that the orientational anisotropy decay exhibits Arrhenius behavior, with an apparent activation energy of 2.4 kcal/mol in 1M and 2M HCl. Interestingly, acidic solutions at high concentration with longer proton transfer time scales display corresponding decreases in activation energy. We interpret this counterintuitive trend by considering the entropic and enthalpic contributions to the activation free energy for proton transfer. Halide counteranions at high concentrations impose entropic barriers to proton transfer in the form of constraints on the solution's collective H-bond fluctuations and obstruction of potential proton transfer pathways. The corresponding proton transfer barrier decreases due to weaker water-halide H-bonds in close proximity to the excess proton, but the entropic effects dominate and result in a net reduction in the proton transfer rate. We estimate the activation free energy for proton transfer as ∼1.0 kcal/mol at 280 K.

Graph dynamical networks for unsupervised learning of atomic scale dynamics in materials

Understanding the dynamical processes that govern the performance of functional materials is essential for the design of next generation materials to tackle global energy and environmental challenges. Many of these processes involve the dynamics of individual atoms or small molecules in condensed phases, e.g. lithium ions in electrolytes, water molecules in membranes, molten atoms at interfaces, etc., which are difficult to understand due to the complexity of local environments. In this work, we develop graph dynamical networks, an unsupervised learning approach for understanding atomic scale dynamics in arbitrary phases and environments from molecular dynamics simulations. We show that important dynamical information, which would be difficult to obtain otherwise, can be learned for various multi-component amorphous material systems. With the large amounts of molecular dynamics data generated every day in nearly every aspect of materials design, this approach provides a broadly applicable, automated tool to understand atomic scale dynamics in material systems.

Understanding local dynamical processes in materials is challenging due to the complexity of the local atomic environments. Here the authors propose a graph dynamical networks approach that is shown to learn the atomic scale dynamics in arbitrary phases and environments from molecular dynamics simulations.