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Protein–calixarenes binding plays an increasingly central role in many applications, spanning from molecular recognition to drug delivery strategies and protein inhibition. These ligands obey a specific bio-supramolecular chemistry, which can be revealed by computational approaches, such as molecular dynamics simulations. In this paper, we rely on all-atom, explicit-solvent molecular dynamics simulations to capture the electrostatically driven association of a phosphonated calix-[4]-arene with cytochome-C, which critically relies on surface-exposed paired lysines. Beyond two binding sites identified in direct agreement with the x-ray structure, the association has a larger structural impact on the protein dynamics. Then, our simulations allow a direct comparison to analogous calixarenes, namely, sulfonato, similarly reported as "molecular glue." Our work can contribute to a robust in silico predictive tool to assess binding sites for any given protein of interest for crystallization, with the specificity of a macromolecular cage whose endo/exo orientation plays a role in the binding. [ABSTRACT FROM AUTHOR]

The large discrepancy among the nucleation kinetics extracted from experimental measurements and computer simulations and the prediction of the classical nucleation theory (CNT) has stimulated intense arguments about its origin in the past decades, which is crucially relevant to the validity of the CNT. In this paper, we investigate the atomistic mechanism of the nucleation in liquid Al in contact with amorphous substrates with atomic-level smooth/rough surfaces, using molecular dynamics (MD) simulations. This study reveals that the slightly distorted local fcc/hcp structures in amorphous substrates with smooth surfaces can promote heterogeneous nucleation through a structural templating mechanism, and on the other hand, homogeneous nucleation will occur at a larger undercooling through a fluctuation mechanism if the surface is rough. Thus, some impurities, previously thought to be impotent, could be activated in the homogeneous nucleation experiments. We further find that the initial growth of the nucleus on smooth surfaces of amorphous substrates is one order of magnitude faster than that in homogeneous nucleation. Both these factors could significantly contribute to the discrepancy in the nucleation kinetics. This study is also supported by a recent study of the synthesis of high-entropy alloy nanoparticles assisted with the liquid metal Ga [Cao et al., Nature 619, 73 (2023)]. In this study, we established that the boundary existed between homogeneous and heterogeneous nucleation, i.e., the structural templating is a general mechanism for heterogeneous nucleation, and in its absence, homogeneous nucleation will occur through the fluctuation mechanism. This study provides an in-depth understanding of the nucleation theory and experiments. [ABSTRACT FROM AUTHOR]

In order to prepare highly heat-resistant packaging insulation materials, in this paper, bismaleimide/epoxy resin (BMI/EP55) composites with different contents of BMI were prepared by melt blending BMI into amino tetrafunctional and phenolic epoxy resin (at a ratio of 5:5). The microstructures and thermal and electrical properties of the composites were tested. The electrostatic potential distribution, energy level distribution, and molecular orbitals of BMI were calculated using Gaussian. The results showed that the carbonyl group in BMI is highly electronegative, implying that the carbonyl group has a strong electron trapping ability. The thermal decomposition temperature of the composites gradually increased with the increase of BMI content, and the 20% BMI/EP55 composites had the highest heat-resistance index, along with a glass transition temperature (Tg) of >250 °C. At different test temperatures, with increase in the BMI content, the conductivity of epoxy resin composites showed a tendency to first decrease and then increase, the breakdown field strength showed a tendency to first increase and then decrease, and the dielectric constant was gradually decreased. Two trap centers were present simultaneously in the composites, where the shallow trap energy level is the deepest in 20% BMI/EP composites and the deep trap energy level is the deepest in 10% BMI/EP55 composites. Correspondingly, the 10% BMI/EP55 composite had a slower charge decay rate, while the 20% BMI/EP55 had a faster charge decay rate. In summary, the BMI/EP55 composites with high heat resistance and insulating properties were prepared in this study, which provided ideas for preparing high-temperature packaging insulating materials. [ABSTRACT FROM AUTHOR]

Hydration and, in particular, the coordination number of a metal ion is of paramount importance as it defines many of its (bio)physicochemical properties. It is not only essential for understanding its behavior in aqueous solutions but also determines the metal ion reference state and its binding energy to (bio)molecules. In this paper, for divalent metal cations Ca 2 + , Cd 2 + , Cu 2 + , Fe 2 + , Hg 2 + , Mg 2 + , Ni 2 + , Pb 2 + , and Zn 2 + , we compare two approaches for predicting hydration numbers: (1) a mixed explicit/continuum DFT-D3//COSMO-RS solvation model and (2) density functional theory based ab initio molecular dynamics. The former approach is employed to calculate the Gibbs free energy change for the sequential hydration reactions, starting from [M( H 2 O)2]2+ aqua complexes to [M( H 2 O) 9]2+, allowing explicit water molecules to bind in the first or second coordination sphere and determining the most stable [M( H 2 O) n]2+ structure. In the latter approach, the hydration number is obtained by integrating the ion–water radial distribution function. With a couple of exceptions, the metal ion hydration numbers predicted by the two approaches are in mutual agreement, as well as in agreement with the experimental data. [ABSTRACT FROM AUTHOR]

Biased and accelerated molecular simulations (BAMS) are widely used tools to observe relevant molecular phenomena occurring on time scales inaccessible to standard molecular dynamics, but evaluation of the physical time scales involved in the processes is not directly possible from them. For this reason, the problem of recovering dynamics from such kinds of simulations is the object of very active research due to the relevant theoretical and practical implications of dynamics on the properties of both natural and synthetic molecular systems. In a recent paper [A. Rapallo et al., J. Comput. Chem. 42, 586–599 (2021)], it has been shown how the coupling of BAMS (which destroys the dynamics but allows to calculate average properties) with Extended Diffusion Theory (EDT) (which requires input appropriate equilibrium averages calculated over the BAMS trajectories) allows to effectively use the Smoluchowski equation to calculate the orientational time correlation function of the head–tail unit vector defined over a peptide in water solution. Orientational relaxation of this vector is the result of the coupling of internal molecular motions with overall molecular rotation, and it was very well described by correlation functions expressed in terms of weighted sums of suitable time-exponentially decaying functions, in agreement with a Brownian diffusive regime. However, situations occur where exponentially decaying functions are no longer appropriate to capture the actual dynamical behavior, which exhibits persistent long time correlations, compatible with the so called subdiffusive regimes. In this paper, a generalization of EDT will be given, exploiting a fractional Smoluchowski equation (FEDT) to capture the non-exponential character observed in the relaxation of intramolecular distances and molecular radius of gyration, whose dynamics depend on internal molecular motions only. The calculation methods, proper to EDT, are adapted to implement the generalization of the theory, and the resulting algorithm confirms FEDT as a tool of practical value in recovering dynamics from BAMS, to be used in general situations, involving both regular and anomalous diffusion regimes. [ABSTRACT FROM AUTHOR]

A Markov state model is a powerful tool that can be used to track the evolution of populations of configurations in an atomistic representation of a protein. For a coarse-grained linear chain model with discontinuous interactions, the transition rates among states that appear in the Markov model when the monomer dynamics is diffusive can be determined by computing the relative entropy of states and their mean first passage times, quantities that are unchanged by the specification of the energies of the relevant states. In this paper, we verify the folding dynamics described by a diffusive linear chain model of the crambin protein in three distinct solvent systems, each differing in complexity: a hard-sphere solvent, a solvent undergoing multi-particle collision dynamics, and an implicit solvent model. The predicted transition rates among configurations agree quantitatively with those observed in explicit molecular dynamics simulations for all three solvent models. These results suggest that the local monomer–monomer interactions provide sufficient friction for the monomer dynamics to be diffusive on timescales relevant to changes in conformation. Factors such as structural ordering and dynamic hydrodynamic effects appear to have minimal influence on transition rates within the studied solvent densities. [ABSTRACT FROM AUTHOR]

The network structure within polymers significantly influences their mechanical properties, including their strength, toughness, and fatigue resistance. All-atom molecular dynamics (AAMD) simulations offer a method to investigate the energy dissipation mechanism within polymers during deformation and fracture; Such an approach is, however, computationally inefficient when used to analyze polymers with complex network structures, such as the common chemically double-networked hydrogels. Alternatively, coarse-grained molecular dynamics (CGMD) models, which reduce the computational degrees of freedom by concentrating a set of adjacent atoms into a coarse-grained bead, can be employed. In CGMD simulations, a coarse-grained force field (CGFF) is a critical factor affecting the simulation accuracy. In this paper, we proposed a data-based method for predicting the CGFF parameters to improve the simulation efficiency of complex cross-linked network in polymers. Here, we utilized a typical chemically double-networked hydrogel as an example. An artificial neural network was selected, and it was trained with the tensile stress–strain data from the CGMD simulations using different CGFF parameters. The CGMD simulations using the predicted CGFF parameters show good agreement with the AAMD simulations and are almost fifty times faster. The data-inspired CGMD model presented here broadens the applicability of molecular dynamics simulations to cross-linked polymers and has the potential to provide insights that will aid the design of polymers with desirable mechanical properties. [ABSTRACT FROM AUTHOR]

The fewest switches surface hopping (FSSH) method proposed by Tully in 1990 [Tully, J. Chem. Phys. 93, 1061 (1990)]—along with its many later variations—forms the basis for most practical simulations of molecular dynamics with electronic transitions in realistic systems. Despite its popularity, a rigorous formal derivation of the algorithm has yet to be achieved. In this paper, we derive the energy-conserving momentum jumps employed by FSSH from the perspective of quantum trajectory surface hopping (QTSH) [Martens, J. Phys. Chem. A 123, 1110 (2019)]. In the limit of localized nonadiabatic transitions, simple mathematical and physical arguments allow the FSSH algorithm to be derived from first principles. For general processes, the quantum forces characterizing the QTSH method provide accurate results for nonadiabatic dynamics with rigorous energy conservation, at the ensemble level, within the consistency of the underlying stochastic surface hopping without resorting to the artificial momentum rescaling of FSSH. [ABSTRACT FROM AUTHOR]

This paper series aims to establish a complete correspondence between fine-grained (FG) and coarse-grained (CG) dynamics by way of excess entropy scaling (introduced in Paper I). While Paper II successfully captured translational motions in CG systems using a hard sphere mapping, the absence of rotational motions in single-site CG models introduces differences between FG and CG dynamics. In this third paper, our objective is to faithfully recover atomistic diffusion coefficients from CG dynamics by incorporating rotational dynamics. By extracting FG rotational diffusion, we unravel, for the first time reported to our knowledge, a universality in excess entropy scaling between the rotational and translational diffusion. Once the missing rotational dynamics are integrated into the CG translational dynamics, an effective translation-rotation coupling becomes essential. We propose two different approaches for estimating this coupling parameter: the rough hard sphere theory with acentric factor (temperature-independent) or the rough Lennard-Jones model with CG attractions (temperature-dependent). Altogether, we demonstrate that FG diffusion coefficients can be recovered from CG diffusion coefficients by (1) incorporating "entropy-free" rotational diffusion with translation-rotation coupling and (2) recapturing the missing entropy. Our findings shed light on the fundamental relationship between FG and CG dynamics in molecular fluids. [ABSTRACT FROM AUTHOR]

Molecular dynamics (MD) is the method of choice for understanding the structure, function, and interactions of molecules. However, MD simulations are limited by the strong metastability of many molecules, which traps them in a single conformation basin for an extended amount of time. Enhanced sampling techniques, such as metadynamics and replica exchange, have been developed to overcome this limitation and accelerate the exploration of complex free energy landscapes. In this paper, we propose Vendi Sampling, a replica-based algorithm for increasing the efficiency and efficacy of the exploration of molecular conformation spaces. In Vendi sampling, replicas are simulated in parallel and coupled via a global statistical measure, the Vendi Score, to enhance diversity. Vendi sampling allows for the recovery of unbiased sampling statistics and dramatically improves sampling efficiency. We demonstrate the effectiveness of Vendi sampling in improving molecular dynamics simulations by showing significant improvements in coverage and mixing between metastable states and convergence of free energy estimates for four common benchmarks, including Alanine Dipeptide and Chignolin. [ABSTRACT FROM AUTHOR]

Interpreting high-dimensional data from molecular dynamics simulations is a persistent challenge. In this paper, we show that for a small peptide, deca-alanine, metastable states can be identified through a neural net based on structural information alone. While processing molecular dynamics data, dimensionality reduction is a necessary step that projects high-dimensional data onto a low-dimensional representation that, ideally, captures the conformational changes in the underlying data. Conventional methods make use of the temporal information contained in trajectories generated through integrating the equations of motion, which forgoes more efficient sampling schemes. We demonstrate that EncoderMap, an autoencoder architecture with an additional distance metric, can find a suitable low-dimensional representation to identify long-lived molecular conformations using exclusively structural information. For deca-alanine, which exhibits several helix-forming pathways, we show that this approach allows us to combine simulations with different biasing forces and yields representations comparable in quality to other established methods. Our results contribute to computational strategies for the rapid automatic exploration of the configuration space of peptides and proteins. [ABSTRACT FROM AUTHOR]

In this paper, we study the permeation of polyatomic gas molecules through 2D graphene membranes. Using equilibrium molecular dynamics simulations, we investigate the permeation of pure gas compounds (CH4, CO2, O2, N2, and H2) through nanoporous graphene membranes with varying pore sizes and geometries. Our simulations consider the recrossing mechanism, often neglected in previous studies, which has a significant effect on permeation for intermediate pore size to molecular diameter ratios. We find that the permeation process can be decoupled into two steps: the crossing process of gas molecules through the pore plane and the escaping process from the pore region to a neighboring adsorption site, which prevents recrossing. To account for these mechanisms, we use a permeance model expressed as the product of the permeance for the crossing process and the probability of molecule escape. This phenomenological model is extended to account for small polyatomic gas molecules and to describe permeation regimes ranging from molecular sieving to effusion. The proposed model captures the temperature dependence and provides insights into the key parameters of the gas/membrane interaction controlling the permeance of the system. This work lays the foundation for predicting gas permeance and exploring membrane separation factors in 2D materials such as graphene. [ABSTRACT FROM AUTHOR]

In liquid water, there is a natural tendency to form aggregates that consist of water molecules linked by hydrogen bonds. Such spontaneously formed aggregates are surrounded by a "sea" of disordered water molecules, with both forms remaining in equilibrium. The process of creating water aggregates also takes place in the solvation water of proteins, but in this case, the interactions of water molecules with the protein surface shift the equilibrium of the process. In this paper, we analyze the structural properties of the solvation water in antifreeze proteins (AFPs). The results of molecular dynamics analysis with the use of various parameters related to the structure of solvation water on the protein surface are presented. We found that in the vicinity of the active region responsible for the binding of AFPs to ice, the equilibrium is clearly shifted toward the formation of "ice-like aggregates," and the solvation water has a more ordered ice-like structure. We have demonstrated that a reduction in the tendency to create "ice-like aggregates" results in a significant reduction in the antifreeze activity of the protein. We conclude that shifting the equilibrium in favor of the formation of "ice-like aggregates" in the solvation water in the active region is a prerequisite for the biological functionality of AFPs, at least for AFPs having a well-defined ice binding area. In addition, our results fully confirm the validity of the "anchored clathrate water" concept, formulated by Garnham et al. [Proc. Natl. Acad. Sci. U. S. A. 108, 7363 (2011)]. [ABSTRACT FROM AUTHOR]

This paper presents the molecular dynamics simulation of 1 mol kg−1 LiPF6 in a binary solvent of ethylene carbonate (EC) and dimethylcarbonate, which is a representative electrolyte solution for lithium-ion batteries. The simulation successfully reproduced the diffusion coefficient, ionic conductivity, and shear viscosity as functions of EC content at 300 K, which had been experimentally determined in our previous study. The Yukawa potential was adopted to model intercharge interactions to reduce computational costs, which consequently allowed us to precisely calculate the conductivity and viscosity by directly integrating time-correlation functions without explicitly modeling the molecular polarization. Breaking down microscopic current correlation functions into components revealed that, whereas the cation–anion attractive interaction dominantly impedes the conduction when the EC content is low, it is the cation–cation and anion–anion repulsive interactions that reduce the conductivity at a high EC content. An analysis of the pressure correlations revealed that all components positively contribute to the viscosity in the binary solvent without the electrolyte. On the other hand, negative terms are observed in five out of six cross correlations in the presence of the electrolyte, implying that these correlations negatively contribute to the shear stress and entropy production, both of which are net positive. [ABSTRACT FROM AUTHOR]

The collective coupling of an ensemble of molecules to a light field is commonly described by the Tavis–Cummings model. This model includes numerous eigenstates that are optically decoupled from the optically bright polariton states. Accessing these dark states requires breaking the symmetry in the corresponding Hamiltonian. In this paper, we investigate the influence of non-unitary processes on the dark state dynamics in the molecular Tavis–Cummings model. The system is modeled with a Lindblad equation that includes pure dephasing, as it would be caused by weak interactions with an environment, and photon decay. Our simulations show that the rate of pure dephasing, as well as the number of two-level systems, has a significant influence on the dark state population. [ABSTRACT FROM AUTHOR]

This study investigates the behavior of two different mixtures of monomers of polyvinylpyrrolidone (PVP)-based battery binders, polyvinylpyrrolidone:polyvinylidene difluoride (PVP:PVDF) and polyvinylpyrrolidone:polyacrylic acid (PVP:PAA), at graphene and graphite interfaces using classical molecular dynamics simulations. The aim is to identify the best performing monomer binder blend and carbon-based material for the design of battery-optimized energy devices. The PVP:PAA monomer binder blend and graphite are found to have the best interaction energies, densification upon adsorption, and more ordered structure. The adsorption of both monomer binder blends is strongly guided by the higher affinity of PVP and PAA monomeric molecules for the surfaces compared to PVDF. The structure of adsorbed layers of PVP:PVDF monomer binder blend on graphene and graphite develops more quickly than PVP:PAA, indicating faster kinetics. This study complements a previous density functional theory study recently reported by our group and contributes to a better understanding of the nanoscopic features of relevant interfacial regions involving mixtures of monomers of PVP-based battery binders and different carbon-based materials. The effect of a blend of commonly used monomer binders on carbon-based materials is essential for obtaining tightly bound anode and cathode active materials in lithium-ion batteries, which is crucial for designing battery-optimized energy devices. [ABSTRACT FROM AUTHOR]

The MACE architecture represents the state of the art in the field of machine learning force fields for a variety of in-domain, extrapolation, and low-data regime tasks. In this paper, we further evaluate MACE by fitting models for published benchmark datasets. We show that MACE generally outperforms alternatives for a wide range of systems, from amorphous carbon, universal materials modeling, and general small molecule organic chemistry to large molecules and liquid water. We demonstrate the capabilities of the model on tasks ranging from constrained geometry optimization to molecular dynamics simulations and find excellent performance across all tested domains. We show that MACE is very data efficient and can reproduce experimental molecular vibrational spectra when trained on as few as 50 randomly selected reference configurations. We further demonstrate that the strictly local atom-centered model is sufficient for such tasks even in the case of large molecules and weakly interacting molecular assemblies. [ABSTRACT FROM AUTHOR]

As biomolecules vibrate and rotate in the terahertz band, the biological effects of terahertz electromagnetic fields have drawn considerable attention from the physiological and medical communities. Ion channels are the basis of biological electrical signals, so studying the effect of terahertz electromagnetic fields on ion channels is significant. In this paper, the effect of a terahertz electromagnetic field with three different frequencies, 6, 15, and 25 THz, on the Kv1.2 potassium ion channel was investigated by molecular dynamics simulations. The results show that an electromagnetic field with a 15 THz frequency can significantly enhance the permeability of the Kv1.2 potassium ion channel, which is 1.7 times higher than without an applied electric field. By analyzing the behavior of water molecules, it is found that the electromagnetic field with the 15 THz frequency shortens the duration of frozen and relaxation processes when potassium ions pass through the channel, increases the proportion of the direct knock-on mode, and, thus, enhances the permeability of the Kv1.2 potassium ion channel. [ABSTRACT FROM AUTHOR]

This work follows a companion article, which will be referred to as Paper I [Campeggio et al., J. Chem. Phys. 158, 244104 (2023)] in which a quantum-stochastic Liouville equation for the description of the quantum–classical dynamics of a molecule in a dissipative bath has been formulated in curvilinear internal coordinates. In such an approach, the coordinates of the system are separated into three subsets: the quantum coordinates, the classical relevant nuclear degrees of freedom, and the classical irrelevant (bath) coordinates. The equation has been derived in natural internal coordinates, which are bond lengths, bond angles, and dihedral angles. The resulting equation needs to be parameterized. In particular, one needs to compute the potential energy surfaces, the friction tensor, and the rate constants for the nonradiative jumps among the quantum states. While standard methods exist for the calculation of energy and dissipative properties, an efficient evaluation of the transition rates needs to be developed. In this paper, an approximated treatment is introduced, which leads to a simple explicit formula with a single adjustable parameter. Such an approximated expression is compared with the exact calculation of transition rates obtained via molecular dynamics simulations. To make such a comparison possible, a simple sandbox system has been used, with two quantum states and a single internal coordinate (together with its conjugate momentum). Results show that the adjustable parameter, which is an effective decoherence time, can be parameterized from the effective relaxation times of the autocorrelation functions of the conjugated momenta of the relevant nuclear coordinates. [ABSTRACT FROM AUTHOR]

Inelastic collisions of OH with an inert liquid perfluoropolyether (PFPE) surface have been studied experimentally. A pulsed molecular beam of OH with a kinetic energy distribution peaking at 35 kJ mol−1 was directed at a continually refreshed PFPE surface. OH molecules were detected state-selectively with spatial and temporal resolution by pulsed, planar laser-induced fluorescence. The scattered speed distributions were confirmed to be strongly superthermal, regardless of the incidence angle (0° or 45°). Angular scattering distributions were measured for the first time; their reliability was confirmed through extensive Monte Carlo simulations of experimental averaging effects, described in Paper II [A. G. Knight et al., J. Chem. Phys. 158, 244705 (2023)]. The distributions depend markedly on the incidence angle and are correlated with scattered OH speed, consistent with predominantly impulsive scattering. For 45° incidence, the angular distributions are distinctly asymmetric to the specular side but peak at sub-specular angles. This, along with the breadth of the distributions, is incompatible with scattering from a surface that is flat on a molecular scale. New molecular dynamics simulations corroborate the roughness of the PFPE surface. A subtle but unexpected systematic dependence of the angular distribution on the OH rotational state was found, which may be dynamical in origin. The OH angular distributions are similar to those for kinematically similar Ne scattering from PFPE and hence not strongly perturbed by OH being a linear rotor. The results here are broadly compatible with prior predictions from independent quasiclassical trajectory simulations of OH scattering from a model-fluorinated self-assembled monolayer surface. [ABSTRACT FROM AUTHOR]

A large number of force fields have been proposed for describing the behavior of liquid water within classical atomistic simulations, particularly molecular dynamics. In the past two decades, models that incorporate molecular polarizability and even charge transfer have become more prevalent, in attempts to develop more accurate descriptions. These are frequently parameterized to reproduce the measured thermodynamics, phase behavior, and structure of water. On the other hand, the dynamics of water is rarely considered in the construction of these models, despite its importance in their ultimate applications. In this paper, we explore the structure and dynamics of polarizable and charge-transfer water models, with a focus on timescales that directly or indirectly relate to hydrogen bond (H-bond) making and breaking. Moreover, we use the recently developed fluctuation theory for dynamics to determine the temperature dependence of these properties to shed light on the driving forces. This approach provides key insight into the timescale activation energies through a rigorous decomposition into contributions from the different interactions, including polarization and charge transfer. The results show that charge transfer effects have a negligible effect on the activation energies. Furthermore, the same tension between electrostatic and van der Waals interactions that is found in fixed-charge water models also governs the behavior of polarizable models. The models are found to involve significant energy–entropy compensation, pointing to the importance of developing water models that accurately describe the temperature dependence of water structure and dynamics. [ABSTRACT FROM AUTHOR]

The rigorous quantum mechanical description of the collective interaction of many molecules with the radiation field is usually considered numerically intractable, and approximation schemes must be employed. Standard spectroscopy usually contains some levels of perturbation theory, but under strong coupling conditions, other approximations are used. A common approximation is the 1-exciton model in which processes involving weak excitations are described using a basis comprising the ground state and singly excited states of the molecule cavity-mode system. In another frequently used approximation in numerical investigations, the electromagnetic field is described classically, and the quantum molecular subsystem is treated in the mean-field Hartree approximation with its wavefunction assumed to be a product of single molecules' wavefunctions. The former disregards states that take long time to populate and is, therefore, essentially a short time approximation. The latter is not limited in this way, but by its nature, disregards some intermolecular and molecule-field correlations. In this work, we directly compare results obtained from these approximations when applied to several prototype problems involving the optical response of molecules-in-optical cavities systems. In particular, we show that our recent model investigation [J. Chem. Phys. 157, 114108 (2022)] of the interplay between the electronic strong coupling and molecular nuclear dynamics using the truncated 1-exciton approximation agrees very well with the semiclassical mean-field calculation. [ABSTRACT FROM AUTHOR]

Strategies for multiple-level parallelizations of quantum-mechanical calculations are discussed, with an emphasis on using groups of workers for performing parallel tasks. These parallel programming models can be used for a variety ab initio quantum chemistry approaches, including the fragment molecular orbital method and replica-exchange molecular dynamics. Strategies for efficient load balancing on problems of increasing granularity are introduced and discussed. A four-level parallelization is developed based on a multi-level hierarchical grouping, and a high parallel efficiency is achieved on the Theta supercomputer using 131 072 OpenMP threads. [ABSTRACT FROM AUTHOR]

A large-scale quantum chemical calculation program, Dcdftbmd, was integrated with a Python-based advanced atomistic simulation program, i-PI. The implementation of a client–server model enabled hierarchical parallelization with respect to replicas and force evaluations. The established framework demonstrated that quantum path integral molecular dynamics simulations can be executed with high efficiency for systems consisting of a few tens of replicas and containing thousands of atoms. The application of the framework to bulk water systems, with and without an excess proton, demonstrated that nuclear quantum effects are significant for intra- and inter-molecular structural properties, including oxygen–hydrogen bond distance and radial distribution function around the hydrated excess proton. [ABSTRACT FROM AUTHOR]

The interaction of 2-propanol with Co3O4(001) was studied by vibrational sum frequency spectroscopy and ab initio molecular dynamics simulations of 2-propanol dissolved in a water film to gain an insight, at the molecular level, into the pathways of catalytic oxidation. The experimental study has been performed under near ambient conditions, where the presence of water vapor is unavoidable, resulting in a water film on the sample and, thereby, allowing us to mimic the solution–water interface. Both experiment and theory conclude that 2-propanol adsorbs molecularly. The lack of dissociation is attributed to the adsorption geometry of 2-propanol in which the O–H bond does not point toward the surface. Furthermore, the copresent water not only competitively adsorbs on the surface but also inhibits 2-propanol deprotonation. The calculations reveal that the presence of water deactivates the lattice oxygen, thereby reducing the surface activity. This finding sheds light on the multifaceted role of water at the interface for the electrochemical oxidation of 2-propanol in aqueous solution as recently reported [Falk et al., ChemCatChem 13, 2942–2951 (2021)]. At higher temperatures, 2-propanol remains molecularly adsorbed on Co3O4(001) until it desorbs with increasing surface temperature. [ABSTRACT FROM AUTHOR]

Transference number is a key design parameter for electrolyte materials used in electrochemical energy storage systems. However, the determination of the true transference number from experiments is rather demanding. On the other hand, the Bruce–Vincent method is widely used in the lab to approximately measure transference numbers of polymer electrolytes, which becomes exact in the limit of infinite dilution. Therefore, theoretical formulations to treat the Bruce–Vincent transference number and the true transference number on an equal footing are clearly needed. Here, we show how the Bruce–Vincent transference number for concentrated electrolyte solutions can be derived in terms of the Onsager coefficients, without involving any extrathermodynamic assumptions. By demonstrating it for the case of poly(ethylene oxide)–lithium bis(trifluoromethane)sulfonimide system, this work opens the door to calibrating molecular dynamics (MD) simulations via reproducing the Bruce–Vincent transference number and using MD simulations as a predictive tool for determining the true transference number. [ABSTRACT FROM AUTHOR]

The physical mechanisms governing molecular mobility in liquids remain unresolved. Whether distinct mechanisms govern mobility in the Arrhenian and super-cooled regions, and whether the mobility in these regions can be unified remain open questions. Here, molecular dynamics simulations were used to search for a structural property with a temperature dependence related by a simple functional form to the temperature dependent translational diffusion coefficient, Dtrans. The logarithm of Dtrans was found to be a two-parameter function of F 2 , where F 2 is the mean squared-force per molecule. The relationship is demonstrated for all systems investigated: a three-bead model of ortho-terphenyl, an 80:20 binary mixture of Lennard-Jones spheres, and a system of Lennard-Jones dumbbells. For each system, the relationship holds for the entire range of temperatures under both constant pressure and constant density conditions. The same F 2 -based expression describes the translational diffusion coefficient in the Arrhenian, crossover, and super-Arrhenian regions. [ABSTRACT FROM AUTHOR]

We present a hydrodynamic theory describing pair diffusion in systems with periodic boundary conditions, thereby generalizing earlier work on self-diffusion [B. Dünweg and K. Kremer, J. Chem. Phys. 99, 6983–6997 (1993) and I.-C. Yeh and G. Hummer, J. Phys. Chem. B 108, 15873–15879 (2004)]. Its predictions are compared with Molecular Dynamics simulations for a liquid carbonate electrolyte and two ionic liquids, for which we characterize the correlated motion between distinct ions. Overall, we observe good agreement between theory and simulation data, highlighting that hydrodynamic interactions universally dictate ion correlations. However, when summing over all ion pairs in the system to obtain the cross-contributions to the total cationic or anionic conductivity, the hydrodynamic interactions between ions with like and unlike charges largely cancel. Consequently, significant conductivity contributions only arise from deviations from a hydrodynamic flow field of an ideal fluid, which is from the local electrolyte structure as well as the relaxation processes in the subdiffusive regime. In the case of ionic liquids, the momentum-conservation constraint additionally is vital, which we study by employing different ionic masses in the simulations. Our formalism will likely also be helpful to estimate finite-size effects of the conductivity or of Maxwell-Stefan diffusivities in simulations. [ABSTRACT FROM AUTHOR]

Simulation datasets of proteins (e.g., those generated by molecular dynamics simulations) are filled with information about how a non-covalent interaction network within a protein regulates the conformation and, thus, function of the said protein. Most proteins contain thousands of non-covalent interactions, with most of these being largely irrelevant to any single conformational change. The ability to automatically process any protein simulation dataset to identify non-covalent interactions that are strongly associated with a single, defined conformational change would be a highly valuable tool for the community. Furthermore, the insights generated from this tool could be applied to basic research, in order to improve understanding of a mechanism of action, or for protein engineering, to identify candidate mutations to improve/alter the functionality of any given protein. The open-source Python package Key Interactions Finder (KIF) enables users to identify those non-covalent interactions that are strongly associated with any conformational change of interest for any protein simulated. KIF gives the user full control to define the conformational change of interest as either a continuous variable or categorical variable, and methods from statistics or machine learning can be applied to identify and rank the interactions and residues distributed throughout the protein, which are relevant to the conformational change. Finally, KIF has been applied to three diverse model systems (protein tyrosine phosphatase 1B, the PDZ3 domain, and the KE07 series of Kemp eliminases) in order to illustrate its power to identify key features that regulate functionally important conformational dynamics. [ABSTRACT FROM AUTHOR]

A vast array of phenomena, ranging from chemical reactions to phase transformations, are analyzed in terms of a free energy surface defined with respect to a single or multiple order parameters. Enhanced sampling methods are typically used, especially in the presence of large free energy barriers, to estimate free energies using biasing protocols and sampling of transition paths. Kinetic reconstructions of free energy barriers of intermediate height have been performed, with respect to a single order parameter, employing the steady state properties of unconstrained simulation trajectories when barrier crossing is achievable with reasonable computational effort. Considering such cases, we describe a method to estimate free energy surfaces with respect to multiple order parameters from a steady state ensemble of trajectories. The approach applies to cases where the transition rates between pairs of order parameter values considered is not affected by the presence of an absorbing boundary, whereas the macroscopic fluxes and sampling probabilities are. We demonstrate the applicability of our prescription on different test cases of random walkers executing Brownian motion in order parameter space with an underlying (free) energy landscape and discuss strategies to improve numerical estimates of the fluxes and sampling. We next use this approach to reconstruct the free energy surface for supercooled liquid silicon with respect to the degree of crystallinity and density, from unconstrained molecular dynamics simulations, and obtain results quantitatively consistent with earlier results from umbrella sampling. [ABSTRACT FROM AUTHOR]

Reactive force fields for molecular dynamics have enabled a wide range of studies in numerous material classes. These force fields are computationally inexpensive compared with electronic structure calculations and allow for simulations of millions of atoms. However, the accuracy of traditional force fields is limited by their functional forms, preventing continual refinement and improvement. Therefore, we develop a neural network-based reactive interatomic potential for the prediction of the mechanical, thermal, and chemical responses of energetic materials at extreme conditions. The training set is expanded in an automatic iterative approach and consists of various CHNO materials and their reactions under ambient and shock-loading conditions. This new potential shows improved accuracy over the current state-of-the-art force fields for a wide range of properties such as detonation performance, decomposition product formation, and vibrational spectra under ambient and shock-loading conditions. [ABSTRACT FROM AUTHOR]

We present an unsupervised data processing workflow that is specifically designed to obtain a fast conformational clustering of long molecular dynamics simulation trajectories. In this approach, we combine two dimensionality reduction algorithms (cc_analysis and encodermap) with a density-based spatial clustering algorithm (hierarchical density-based spatial clustering of applications with noise). The proposed scheme benefits from the strengths of the three algorithms while avoiding most of the drawbacks of the individual methods. Here, the cc_analysis algorithm is applied for the first time to molecular simulation data. The encodermap algorithm complements cc_analysis by providing an efficient way to process and assign large amounts of data to clusters. The main goal of the procedure is to maximize the number of assigned frames of a given trajectory while keeping a clear conformational identity of the clusters that are found. In practice, we achieve this by using an iterative clustering approach and a tunable root-mean-square-deviation-based criterion in the final cluster assignment. This allows us to find clusters of different densities and different degrees of structural identity. With the help of four protein systems, we illustrate the capability and performance of this clustering workflow: wild-type and thermostable mutant of the Trp-cage protein (TC5b and TC10b), NTL9, and Protein B. Each of these test systems poses their individual challenges to the scheme, which, in total, give a nice overview of the advantages and potential difficulties that can arise when using the proposed method. [ABSTRACT FROM AUTHOR]

Starting from the orthogonal dynamics of any given set of variables with respect to the projection variable used to derive the Mori–Zwanzig equation, a set of coupled Volterra equations is obtained that relate the projected time correlation functions between all the variables of interest. This set of equations can be solved using standard numerical inversion methods for Volterra equations, leading to a very convenient yet efficient strategy to obtain any projected time correlation function or contribution to the memory kernel entering a generalized Langevin equation. Using this strategy, the memory kernel related to the diffusion of tagged particles in a bulk Lennard–Jones fluid is investigated up to the long-term regime to show that the repulsive–attractive cross-contribution to memory effects represents a small but non-zero contribution to the self-diffusion coefficient. [ABSTRACT FROM AUTHOR]

Topological data analysis based on persistent homology has been applied to the molecular dynamics simulation for the fast ion-conducting phase (α-phase) of AgI to show its effectiveness on the ion migration mechanism analysis. Time-averaged persistence diagrams of α-AgI, which quantitatively record the shape and size of the ring structures in the given atomic configurations, clearly showed the emergence of the four-membered rings formed by two Ag and two I ions at high temperatures. They were identified as common structures during the Ag ion migration. The averaged potential energy change due to the deformation of the four-membered ring during Ag migration agrees well with the activation energy calculated from the conductivity Arrhenius plot. The concerted motion of two Ag ions via the four-membered ring was also successfully extracted from molecular dynamics simulations by our approach, providing new insight into the specific mechanism of the concerted motion. [ABSTRACT FROM AUTHOR]

SchNetPack is a versatile neural network toolbox that addresses both the requirements of method development and the application of atomistic machine learning. Version 2.0 comes with an improved data pipeline, modules for equivariant neural networks, and a PyTorch implementation of molecular dynamics. An optional integration with PyTorch Lightning and the Hydra configuration framework powers a flexible command-line interface. This makes SchNetPack 2.0 easily extendable with a custom code and ready for complex training tasks, such as the generation of 3D molecular structures. [ABSTRACT FROM AUTHOR]

In this work, we perform molecular dynamics simulations to study a spherical polyelectrolyte brush. We explore the effects of surface polarization and electrostatic coupling on brush size and distribution of counterions. The method of image charges is considered to take into account surface polarization, considering a metallic, an unpolarizable, and a dielectric nano-core. It is observed that, for all cases, a moderate shrinking–swelling effect appears with an increase in the electrostatic coupling parameter. This effect occurs under high Manning ratios. The curves relating the average size of polyelectrolyte brush as a function of coupling show a minimum. The results show that the grafting density of polyelectrolytes on the nano-core surface plays an important role in the polarization effect. We consider a modified Poisson–Boltzmann theory to describe the counterion profiles around the brush in the case of unpolarizable nano-cores and weak electrostatic coupling. [ABSTRACT FROM AUTHOR]

The transition between the gas-, supercritical-, and liquid-phase behavior is a fascinating topic, which still lacks molecular-level understanding. Recent ultrafast two-dimensional infrared spectroscopy experiments suggested that the vibrational spectroscopy of N2O embedded in xenon and SF6 as solvents provides an avenue to characterize the transitions between different phases as the concentration (or density) of the solvent increases. The present work demonstrates that classical molecular dynamics (MD) simulations together with accurate interaction potentials allows us to (semi-)quantitatively describe the transition in rotational vibrational infrared spectra from the P-/R-branch line shape for the stretch vibrations of N2O at low solvent densities to the Q-branch-like line shapes at high densities. The results are interpreted within the classical theory of rigid-body rotation in more/less constraining environments at high/low solvent densities or based on phenomenological models for the orientational relaxation of rotational motion. It is concluded that classical MD simulations provide a powerful approach to characterize and interpret the ultrafast motion of solutes in low to high density solvents at a molecular level. [ABSTRACT FROM AUTHOR]

The most accepted origin for the water anomalous behavior is the phase transition between two liquids (LLPT) in the supercooled regime connected to the glassy first order phase transition at lower temperatures. Two length scale potentials are an effective approach that has long been employed to understand the properties of fluids with waterlike anomalies and, more recently, the behavior of colloids and nanoparticles. These potentials can be parameterized to have distinct shapes, as a pure repulsive ramp, such as the model proposed by de Oliveira et al. [J. Chem. Phys. 124, 64901 (2006)]. This model has waterlike anomalies despite the absence of LLPT. To unravel how the waterlike anomalies are connected to the solid phases, we employ molecular dynamics simulations. We have analyzed the fluid–solid transition under cooling, with two solid crystalline phases, BCC and HCP, and two amorphous regions being observed. We show how the competition between the scales creates an amorphous cluster in the BCC crystal that leads to amorphization at low temperatures. A similar mechanism is found in the fluid phase, with the system changing from a BCC-like to an amorphous-like structure in the point where a maxima in kT is observed. With this, we can relate the competition between two fluid structures with the amorphous clusterization in the BCC phase. These findings help to understand the origins of waterlike behavior in systems without the liquid–liquid critical point. [ABSTRACT FROM AUTHOR]

The origin of β-relaxation in metallic glasses is still not fully understood, and the guidance of slow atoms for caged dynamics and β-relaxation is rarely mentioned. Using molecular dynamics simulations, we reveal the bridging role of slow atoms on unusual caged dynamics and β-relaxation. In the stage of unusual caged dynamics, slow atoms are bounded by neighboring atoms. It is difficult for the slow atoms to break the cage, producing more high-frequency vibration, which causes more atoms to jump out of the cage randomly in the next stage. Precisely, the movement of the slow atoms changes from individual atoms vibrating inside the cage and gradually breaking out of the cage into a string-like pattern. The string-like collective atomic jumps cause decay of the cages, inducing β-relaxation. This situation generally exists in binary systems with the large atomic mass difference. This work offers valuable insights for understanding the role of slow atoms in unusual caged dynamics and β-relaxation, complementing studies on the origin of β-relaxation in metallic glasses and their glass-forming liquids. [ABSTRACT FROM AUTHOR]

Computationally inspired design of organic electronic materials requires robust models of not only the ground and excited electronic states but also of transitions between these states. In this work, we introduce a strategy for obtaining electronic transition dipole moments for the lowest-lying singlet–singlet transition in organic chromophores from time-independent excited-state density-functional tight-binding (ΔDFTB) calculations. Through small-molecule benchmarks and applications to larger chromophores, we explore the accuracy, potential, and limitations of this semiempirical strategy. While more accurate methods are recommended for small systems, we find some evidence for the method's potential in high-throughput molecular screening applications and in the analysis of molecular dynamics simulations. [ABSTRACT FROM AUTHOR]

The vibrational dynamics of the NO stretching mode of [RuCl5(NO)]2− in D2O were investigated by nonlinear infrared (IR) spectroscopy. We performed IR pump–probe measurements to obtain the vibrational lifetime of this molecule. The lifetime is 31 ps, which is sufficiently long enough to study the vibrational frequency fluctuation on a slower time scale with high precision. By two-dimensional IR spectroscopy, the frequency–frequency time correlation function (FFTCF) of the NO stretching mode was characterized with a delta function plus a double-exponential function. The time constant of the slower component was ∼10 ps. We also found that the time constant does not strongly depend on temperature. In order to investigate the microscopic origin of this component, we performed classical molecular dynamics simulations. It was found that the hydration structure around the NO group was influenced by the negatively charged Cl ligands. To calculate the FFTCF decay, we employed an approximate theoretical model based on the vibrational solvatochromism theory. It was demonstrated that water fluctuations around the Cl ligands projected on the NO group correspond to the 10 ps decay component in the FFTCF. The fluctuation is related to the orientational dynamics of the water molecules attracted by the Cl ligands. By comparing the FFTCF parameters of the present solute with those of previously reported metal complexes and SCN− in D2O, we conclude that the presence of different electrostatic environments around the vibrational probe and the other interaction sites of the solute is important for understanding the slow decay component in the FFTCFs. [ABSTRACT FROM AUTHOR]

Allostery in proteins involves, broadly speaking, ligand-induced conformational transitions that modulate function at active sites distal to where the ligand binds. In contrast, the concept of cooperativity (in the sense used in phase transition theory) is often invoked to understand protein folding and, therefore, function. The modern view on allostery is one based on dynamics and hinges on the time-dependent interactions between key residues in a complex network, interactions that determine the free-energy profile for the reaction at the distal site. Here, we merge allostery and cooperativity, and we discuss a joint model with features of both. In our model, the active-site reaction is replaced by the reaction pathway that leads to protein folding, and the presence or absence of the effector is replaced by mutant-vs-wild type changes in key residues. To this end, we employ our recently introduced time-lagged independent component analysis (tICA) correlation approach [Ray et al. Proc. Natl. Acad. Sci. 118(43) (2021), e2100943118] to identify the allosteric role of distant residues in the folded-state dynamics of a large protein. In this work, we apply the technique to identify key residues that have a significant role in the folding of a small, fast folding-protein, chignolin. Using extensive enhanced sampling simulations, we critically evaluate the accuracy of the predictions by mutating each residue one at a time and studying how the mutations change the underlying free energy landscape of the folding process. We observe that mutations in those residues whose associated backbone torsion angles have a high correlation score can indeed lead to loss of stability of the folded configuration. We also provide a rationale based on interaction energies between individual residues with the rest of the protein to explain this effect. From these observations, we conclude that the tICA correlation score metric is a useful tool for predicting the role of individual residues in the correlated dynamics of proteins and can find application to the problem of identifying regions of protein that are either most vulnerable to mutations or—mutatis mutandis—to binding events that affect their functionality. [ABSTRACT FROM AUTHOR]

We computed the IR, Raman, and sum frequency generation spectra of water in the OH-stretch region by employing the quantum/classical mixed approach that consists of a vibrational spectroscopic map and molecular dynamics (MD) simulation. We carried out the MD simulation with the TIP4P, TIP4P/2005, and TIP4P/Ice models and applied the map designed for TIP4P by Skinner et al. to each MD trajectory. Although the map is not tuned for TIP4P-like models, TIP4P/2005 and TIP4P/Ice provide the best reproduction of the experimental vibrational spectra of liquid water and crystalline ice, respectively. This result demonstrates the transferability of the map from TIP4P to TIP4P/2005 and TIP4P/Ice, meaning that one can choose an appropriate TIP4P-like model to calculate the vibrational spectra of an aqueous system without rebuilding the map. [ABSTRACT FROM AUTHOR]

Proteolysis is essential for the control of metabolic pathways and the cell cycle. Bacterial caseinolytic proteases (Clp) use peptidase components, such as ClpP, to degrade defective substrate proteins and to regulate cellular levels of stress-response proteins. To ensure selective degradation, access to the proteolytic chamber of the double–ring ClpP tetradecamer is controlled by a critical gating mechanism of the two axial pores. The binding of conserved loops of the Clp ATPase component of the protease or small molecules, such as acyldepsipeptide (ADEP), at peripheral ClpP ring sites, triggers axial pore opening through dramatic conformational transitions of flexible N-terminal loops between disordered conformations in the "closed" pore state and ordered hairpins in the "open" pore state. In this study, we probe the allosteric communication underlying these conformational changes by comparing residue–residue couplings in molecular dynamics simulations of each configuration. Both principal component and normal mode analyses highlight large-scale conformational changes in the N-terminal loop regions and smaller amplitude motions of the peptidase core. Community network analysis reveals a switch between intra- and inter-protomer coupling in the open–closed pore transition. Allosteric pathways that connect the ADEP binding sites to N-terminal loops are rewired in this transition, with shorter network paths in the open pore configuration supporting stronger intra- and inter-ring coupling. Structural perturbations, either through the removal of ADEP molecules or point mutations, alter the allosteric network to weaken the coupling. [ABSTRACT FROM AUTHOR]

Deep eutectic solvent is a mixture of two or more components, mixed in a certain molar ratio, such that the mixture melts at a temperature lower than individual substances. In this work, we have used a combination of ultrafast vibrational spectroscopy and molecular dynamics simulations to investigate the microscopic structure and dynamics of a deep eutectic solvent (1:2 choline chloride: ethylene glycol) at and around the eutectic composition. In particular, we have compared the spectral diffusion and orientational relaxation dynamics of these systems with varying compositions. Our results show that although the time-averaged solvent structures around a dissolved solute are comparable across compositions, both the solvent fluctuations and solute reorientation dynamics show distinct differences. We show that these subtle changes in solute and solvent dynamics with changing compositions arise from the variations in the fluctuations of the different intercomponent hydrogen bonds. [ABSTRACT FROM AUTHOR]

Surfactants are commonly used as disinfection agents in personal care products against bacteria and viruses, including SARS-CoV-2. However, there is a lack of understanding of the molecular mechanisms of the inactivation of viruses by surfactants. Here, we employ coarse grain (CG) and all-atom (AA) molecular dynamics simulations to investigate the interaction between general families of surfactants and the SARS-CoV-2 virus. To this end, we considered a CG model of a full virion. Overall, we found that surfactants have only a small impact on the virus envelope, being inserted into the envelope without dissolving it or generating pores, at the conditions considered here. However, we found that surfactants may induce a deep impact on the spike protein of the virus (responsible for its infectivity), easily covering it and inducing its collapse over the envelope surface of the virus. AA simulations confirmed that both negatively and positively charged surfactants are able to extensively adsorb over the spike protein and get inserted into the virus envelope. Our results suggest that the best strategy for the design of surfactants as virucidal agents will be to focus on those strongly interacting with the spike protein. [ABSTRACT FROM AUTHOR]

Extensive coarse-grained molecular dynamics simulations are performed to investigate the conformational phase diagram of a neutral polymer in the presence of attractive crowders. We show that, for low crowder densities, the polymer predominantly shows three phases as a function of both intra-polymer and polymer–crowder interactions: (1) weak intra-polymer and weak polymer–crowder attractive interactions induce extended or coil polymer conformations (phase E), (2) strong intra-polymer and relatively weak polymer–crowder attractive interactions induce collapsed or globular conformations (phase CI), and (3) strong polymer–crowder attractive interactions, regardless of intra-polymer interactions, induce a second collapsed or globular conformation that encloses bridging crowders (phase CB). The detailed phase diagram is obtained by determining the phase boundaries delineating the different phases based on an analysis of the radius of gyration as well as bridging crowders. The dependence of the phase diagram on strength of crowder–crowder attractive interactions and crowder density is clarified. We also show that when the crowder density is increased, a third collapsed phase of the polymer emerges for weak intra-polymer attractive interactions. This crowder density-induced compaction is shown to be enhanced by stronger crowder–crowder attraction and is different from the depletion-induced collapse mechanism, which is primarily driven by repulsive interactions. We also provide a unified explanation of the observed re-entrant swollen/extended conformations of the earlier simulations of weak and strongly self-interacting polymers in terms of crowder–crowder attractive interactions. [ABSTRACT FROM AUTHOR]

We investigate the structures of hydrated electrons (e−aq) in one of water's solid phases, namely, clathrate hydrates (CHs). Using density functional theory (DFT) calculations, DFT-based ab initio molecular dynamics (AIMD), and path-integral AIMD simulations with periodic boundary conditions, we find that the structure of the e−aq@node model is in good agreement with the experiment, suggesting that an e−aq could form a node in CHs. The node is a H2O defect in CHs that is supposed to be composed of four unsaturated hydrogen bonds. Since CHs are porous crystals that possess cavities that can accommodate small guest molecules, we expect that these guest molecules can be used to tailor the electronic structure of the e−aq@node, and it leads to experimentally observed optical absorption spectra of CHs. Our findings have a general interest and extend the knowledge of e−aq into porous aqueous systems. [ABSTRACT FROM AUTHOR]

The slow relaxation of interface water (IW) across three primary phases of membranes is relevant to understand the influence of IW on membrane functions at supercooled conditions. To this objective, a total of ∼ 16.26 μ s all-atom molecular dynamics simulations of 1,2-dimyristoyl-sn-glycerol-3-phosphocholine lipid membranes are carried out. A supercooling-driven drastic slow-down in heterogeneity time scales of the IW is found at the fluid to the ripple to the gel phase transitions of the membranes. At both fluid-to-ripple-to-gel phase transitions, the IW undergoes two dynamic crossovers in Arrhenius behavior with the highest activation energy at the gel phase due to the highest number of hydrogen bonds. Interestingly, the Stokes–Einstein (SE) relation is conserved for the IW near all three phases of the membranes for the time scales derived from the diffusion exponents and the non-Gaussian parameters. However, the SE relation breaks for the time scale obtained from the self-intermediate scattering functions. The behavioral difference in different time scales is universal and found to be an intrinsic property of glass. The first dynamical transition in the α relaxation time of the IW is associated with an increase in the Gibbs energy of activation of hydrogen bond breaking with locally distorted tetrahedral structures, unlike the bulk water. Thus, our analyses unveil the nature of the relaxation time scales of the IW across membrane phase transitions in comparison with the bulk water. The results will be useful to understand the activities and survival of complex biomembranes under supercooled conditions in the future. [ABSTRACT FROM AUTHOR]

We report a molecular dynamics study of the heterogeneous crystallization of high-pressure glassy water using (plastic) ice VII as a substrate. We focus on the thermodynamic conditions P ∈ [6–8] GPa and T ∈ [100–500] K, at which (plastic) ice VII and glassy water are supposed to coexist in several (exo)planets and icy moons. We find that (plastic) ice VII undergoes a martensitic phase transition to a (plastic) fcc crystal. Depending on the molecular rotational lifetime τ, we identify three rotational regimes: for τ > 20 ps, crystallization does not occur; for τ ∼ 15 ps, we observe a very sluggish crystallization and the formation of a considerable amount of icosahedral environments trapped in a highly defective crystal or in the residual glassy matrix; and for τ < 10 ps, crystallization takes place smoothly, resulting in an almost defect-free plastic fcc solid. The presence of icosahedral environments at intermediate τ is of particular interest as it shows that such a geometry, otherwise ephemeral at lower pressures, is, indeed, present in water. We justify the presence of icosahedral structures based on geometrical arguments. Our results represent the first study of heterogeneous crystallization occurring at thermodynamic conditions of relevance for planetary science and unveil the role of molecular rotations in achieving it. Our findings (i) show that the stability of plastic ice VII, widely reported in the literature, should be reconsidered in favor of plastic fcc, (ii) provide a rationale for the role of molecular rotations in achieving heterogeneous crystallization, and (iii) represent the first evidence of long-living icosahedral structures in water. Therefore, our work pushes forward our understanding of the properties of water. [ABSTRACT FROM AUTHOR]