How Thick is the Air-Water Interface?─A Direct Experimental Measurement of the Decay Length of the Interfacial Structural Anisotropy

The air-water interface is a highly prevalent phase boundary impacting many natural and artificial processes. The significance of this interface arises from the unique properties of water molecules within the interfacial region, with a crucial parameter being the thickness of its structural anisotropy, or "healing depth". This quantity has been extensively assessed by various simulations which have converged to a prediction of a remarkably short length of ∼6 Å. Despite the absence of any direct experimental measurement of this quantity, this predicted value has surprisingly become widely accepted as fact. Using an advancement in nonlinear vibrational spectroscopy, we provide the first measurement of this thickness and, indeed, find it to be ∼6-8 Å, finally confirming the prior predictions. Lastly, by combining the experimental results with depth-dependent second-order spectra calculated from ab initio parametrized molecular dynamics simulations, which are also in excellent agreement with this experimental result, we shed light on this surprisingly short correlation length of molecular orientations at the interface.

Ab Initio Simulation of Liquid Water without Artificial High Temperature

Comprehending the structure and dynamics of water is crucial in various fields, such as water desalination, ion separation, electrocatalysis, and biochemical processes. While reported works show that the ab initio molecular dynamics (AIMD) can accurately portray water's structure, the artificial high temperature (AHT) from 120 to 30 K is needed to mimic the quantum nature of hydrogen-bond network from GGA, metaGGA to hybrid functionals. The AHT proves to be an inadequate approach for systems involving aqueous multiphase mixtures, such as water-solid interfaces and aqueous solutions. This is due to the activation of additional phonons in other phases, which can lead to an overestimation of the dynamics of nearby water molecules. In this work, we find that the regularized SCAN (rSCAN) functional effectively captures both the structure and dynamics of liquid water at ambient conditions without AHT. Moreover, rSCAN closely matches experimental results for the hydration structures of alkali, alkali earth, and halide ions. We anticipate that the versatile and accurate rSCAN functional will emerge as a key tool based on ab initio simulation for investigating chemical processes in aqueous environments.

Accuracy limit of non-polarizable four-point water models: TIP4P/2005 vs OPC. Should water models reproduce the experimental dielectric constant?

The last generation of four center non-polarizable models of water can be divided into two groups: those reproducing the dielectric constant of water, as OPC, and those significantly underestimating its value, as TIP4P/2005. To evaluate the global performance of OPC and TIP4P/2005, we shall follow the test proposed by Vega and Abascal in 2011 evaluating about 40 properties to fairly address this comparison. The liquid-vapor and liquid-solid equilibria are computed, as well as the heat capacities, isothermal compressibilities, surface tensions, densities of different ice polymorphs, the density maximum, equations of state at high pressures, and transport properties. General aspects of the phase diagram are considered by comparing the ratios of different temperatures (namely, the temperature of maximum density, the melting temperature of hexagonal ice, and the critical temperature). The final scores are 7.2 for TIP4P/2005 and 6.3 for OPC. The results of this work strongly suggest that we have reached the limit of what can be achieved with non-polarizable models of water and that the attempt to reproduce the experimental dielectric constant deteriorates the global performance of the water force field. The reason is that the dielectric constant depends on two surfaces (potential energy and dipole moment surfaces), whereas in the absence of an electric field, all properties can be determined simply from just one surface (the potential energy surface). The consequences of the choice of the water model in the modeling of electrolytes in water are also discussed.

Born-Oppenheimer Molecular Dynamics with a Linear Combination of Atomic Orbitals and Hybrid Functionals for Condensed Matter Simulations Made Possible. Theory and Performance for the Microcanonical and Canonical Ensembles

The implementation of an original Born-Oppenheimer molecular dynamics module is presented, which is able to perform simulations of large and complex condensed phase systems for sufficiently long time scales at the level of density functional theory with hybrid functionals, in the microcanonical (NVE) and canonical (NVT) ensembles. The algorithm is fully integrated in the Crystal code, a program for quantum mechanical simulations of materials, whose peculiarity stems from the use of atom-centered basis functions within a linear combination of atomic orbitals to describe the wave function. The corresponding efficiency in the evaluation of the exact Fock exchange series has led to the implementation of a rich variety of hybrid density functionals at a low computational cost. In addition, the molecular dynamics implementation benefits also from the effective MPI parallelization of the code, suited to exploit high-performance computing resources available on current generation supercomputer architectures. Furthermore, the information contained in the trajectory of the dynamics is extracted through a series of postprocessing algorithms that provide the radial distribution function, the diffusion coefficient and the vibrational density of states. In this work, we present a detailed description of the theoretical framework and the algorithmic implementation, followed by a critical evaluation of the accuracy and parallel performance (e.g., strong and weak scaling) of this approach, when ice and liquid water simulations are performed in the microcanonical and canonical ensembles.

Comparing machine learning potentials for water: Kernel-based regression and Behler-Parrinello neural networks

In this paper, we investigate the performance of different machine learning potentials (MLPs) in predicting key thermodynamic properties of water using RPBE + D3. Specifically, we scrutinize kernel-based regression and high-dimensional neural networks trained on a highly accurate dataset consisting of about 1500 structures, as well as a smaller dataset, about half the size, obtained using only on-the-fly learning. This study reveals that despite minor differences between the MLPs, their agreement on observables such as the diffusion constant and pair-correlation functions is excellent, especially for the large training dataset. Variations in the predicted density isobars, albeit somewhat larger, are also acceptable, particularly given the errors inherent to approximate density functional theory. Overall, this study emphasizes the relevance of the database over the fitting method. Finally, this study underscores the limitations of root mean square errors and the need for comprehensive testing, advocating the use of multiple MLPs for enhanced certainty, particularly when simulating complex thermodynamic properties that may not be fully captured by simpler tests.

Structure and dynamics of liquid water from ab initio simulations: adding Minnesota density functionals to Jacob's ladder

The accurate representation of the structural and dynamical properties of water is essential for simulating the unique behavior of this ubiquitous solvent. Here we assess the current status of describing liquid water using ab initio molecular dynamics, with a special focus on the performance of all the later generation Minnesota functionals. Findings are contextualized within the current knowledge on DFT for describing bulk water under ambient conditions and compared to experimental data. We find that, contrary to the prevalent idea that local and semilocal functionals overstructure water and underestimate dynamical properties, M06-L, revM06-L, and M11-L understructure water, while MN12-L and MN15-L overdistance water molecules due to weak cohesive effects. This can be attributed to a weakening of the hydrogen bond network, which leads to dynamical fingerprints that are over fast. While most of the hybrid Minnesota functionals (M06, M08-HX, M08-SO, M11, MN12-SX, and MN15) also yield understructured water, their dynamical properties generally improve over their semilocal counterparts. It emerges that exact exchange is a crucial component for accurately describing hydrogen bonds, which ultimately leads to corrections in both the dynamical and structural properties. However, an excessive amount of exact exchange strengthens hydrogen bonds and causes overstructuring and slow dynamics (M06-HF). As a compromise, M06-2X is the best performing Minnesota functional for water, and its D3 corrected variant shows very good structural agreement. From previous studies considering nuclear quantum effects (NQEs), the hybrid revPBE0-D3, and the rung-5 RPA (RPA@PBE) have been identified as the only two approximations that closely agree with experiments. Our results suggest that the M06-2X(-D3) functionals have the potential to further improve the reproduction of experimental properties when incorporating NQEs through path integral approaches. This work provides further proof that accurate modeling of water interactions requires the inclusion of both exact exchange and balanced (non-local) correlation, highlighting the need for higher rungs on Jacob's ladder to achieve predictive simulations of complex biological systems in aqueous environments.

The structure of water: A historical perspective

Attempts to understand the molecular structure of water were first made well over a century ago. Looking back at the various attempts, it is illuminating to see how these were conditioned by the state of knowledge of chemistry and physics at the time and the experimental and theoretical tools then available. Progress in the intervening years has been facilitated by not only conceptual and theoretical advances in physics and chemistry but also the development of experimental techniques and instrumentation. Exploitation of powerful computational methods in interpreting what at first sight may seem impenetrable experimental data has led us to the consistent and detailed picture we have today of not only the structure of liquid water itself and how it changes with temperature and pressure but also its interactions with other molecules, in particular those relevant to water's role in important chemical and biological processes. Much remains to be done in the latter areas, but the experimental and computational techniques that now enable us to do what might reasonably be termed "liquid state crystallography" have opened the door to make possible further advances. Consequently, we now have the tools to explore further the role of water in those processes that underpin life itself-the very prospect that inspired Bernal to develop his ideas on the structure of liquids in general and of water in particular.

Hydrophobic hydration of the hydrocarbon adamantane in amorphous ice

Hydrophobic molecules are by definition difficult to hydrate. Previous studies in the area of hydrophobic hydration have therefore often relied on using amphiphilic molecules where the hydrophilic part of a molecule enabled the solubility in liquid water. Here, we show that the hydrophobic adamantane (C10H16) molecule can be fully hydrated through vapour codeposition with water onto a cryogenic substrate at 80 K resulting in the matrix isolation of adamantane in amorphous ice. Using neutron diffraction in combination with the isotopic substitution method and the empirical potential structure refinement technique, we find that the first hydration shell of adamantane is well structured consisting of a hydrogen-bonded cage of 28 water molecules that is also found in cubic structure II clathrate hydrates. The four hexagonal faces of the 51264 cage are situated above the four methine (CH) groups of adamantane whereas the methylene (CH2) groups are positioned below the edges of two adjoining pentagonal faces. The oxygen atoms of the 28 water molecules can be categorised on the basis of symmetry equivalences as twelve A, twelve B and four C oxygens. The water molecules of the first hydration shell display orientations consistent with those expected for a clathrate-hydrate-type cage, but also unfavourable ones with respect to the hydrogen bonding between the water molecules. Annealing the samples at 140 K, which is just below the crystallisation temperature of the matrix, removes the unfavourable orientations and leads to a slight increase in the structural order of the first hydration shell. The very closest water molecules display a tendency for their dipole moments to point towards the adamantane which is attributed to steric effects. Other than this, no significant polarisation effects are observed which is consistent with weak interactions between adamantane and the amorphous ice matrix. FT-IR spectroscopy shows that the incorporation of adamantane into amorphous ice leads to a weakening of the hydrogen bonds. In summary, the matrix-isolation of the highly symmetric adamantane in amorphous ice provides an interesting test case for hydrophobic hydration. Studying the structure and spectroscopic properties of water at the interface with hydrophobic hydrocarbons is also relevant for astrophysical environments, such as comets or the interstellar medium, where amorphous ice and hydrocarbons have been shown to coexist in large quantities.

Machine Learning Potentials with the Iterative Boltzmann Inversion: Training to Experiment

Methodologies for training machine learning potentials (MLPs) with quantum-mechanical simulation data have recently seen tremendous progress. Experimental data have a very different character than simulated data, and most MLP training procedures cannot be easily adapted to incorporate both types of data into the training process. We investigate a training procedure based on iterative Boltzmann inversion that produces a pair potential correction to an existing MLP using equilibrium radial distribution function data. By applying these corrections to an MLP for pure aluminum based on density functional theory, we observe that the resulting model largely addresses previous overstructuring in the melt phase. Interestingly, the corrected MLP also exhibits improved performance in predicting experimental diffusion constants, which are not included in the training procedure. The presented method does not require autodifferentiating through a molecular dynamics solver and does not make assumptions about the MLP architecture. Our results suggest a practical framework for incorporating experimental data into machine learning models to improve the accuracy of molecular dynamics simulations.

Accuracy of TIP4P/2005 and SPC/Fw Water Models

Water is used as the main solvent in model systems containing bioorganic molecules. Choosing the right water model is an important step in the study of the biophysical and biochemical processes that occur in cells. In the present work, we perform molecular dynamics simulations using two distinct force fields for water: the rigid model TIP4P/2005, where only intermolecular interactions are considered, and the flexible model SPC/Fw, where intramolecular interactions are also taken into account. The simulations aim to determine the effect of the inclusion of intramolecular interactions on the accuracy of calculated properties of bulk water (density and thermal expansion coefficient, self-diffusion coefficients, shear viscosity, radial distribution functions, and dielectric constant), as compared to experimental results, over a temperature range between 250 and 370 K. We find that the results of the rigid model present the smallest deviations relative to experiments for most of the calculated quantities, except for the shear viscosity of supercooled water and the water dielectric constant, where the flexible model presents better agreement with experiments.

The role of urea in formation of the sodium acetate trihydrate (SAT)-urea eutectic liquid: a neutron diffraction and isotopic substitution study

Neutron diffraction with isotopic substitution has been used to investigate the structure of the liquid sodium acetate trihydrate-urea eutectic (mole fraction (χurea) of 0.60) at 50 °C. Urea competes with acetate anions and water molecules in the solvation of sodium ions, displacing water and, simultaneously, stabilising the liberated 'excess' water through hydrogen bonding between water and urea molecules in the eutectic liquid. This provides a direct insight into the role of urea as both denaturant and hydrogen-bond network former in generating eutectic liquids.

Machine Learning Density Functionals from the Random-Phase Approximation

Kohn-Sham density functional theory (DFT) is the standard method for first-principles calculations in computational chemistry and materials science. More accurate theories such as the random-phase approximation (RPA) are limited in application due to their large computational cost. Here, we use machine learning to map the RPA to a pure Kohn-Sham density functional. The machine learned RPA model (ML-RPA) is a nonlocal extension of the standard gradient approximation. The density descriptors used as ingredients for the enhancement factor are nonlocal counterparts of the local density and its gradient. Rather than fitting only RPA exchange-correlation energies, we also include derivative information in the form of RPA optimized effective potentials. We train a single ML-RPA functional for diamond, its surfaces, and liquid water. The accuracy of ML-RPA for the formation energies of 28 diamond surfaces reaches that of state-of-the-art van der Waals functionals. For liquid water, however, ML-RPA cannot yet improve upon the standard gradient approximation. Overall, our work demonstrates how machine learning can extend the applicability of the RPA to larger system sizes, time scales, and chemical spaces.

Accurate SCC-DFTB Parametrization of Liquid Water with Improved Atomic Charges and Iterative Boltzmann Inversion

This work presents improvements of the description of liquid water within the self-consistent-charge density-functional based tight-binding scheme combining the use of Weighted Mulliken (WMull) charges and optimized O-H repulsive potential through the iterative Boltzmann inversion (IBI) process. The quality of the newly developed models is validated considering pair radial distribution functions (RDFs), as well as other structural, energetic, thermodynamic, and dynamic properties. The use of WMull charges certainly improves the agreement with experimental data, however leading to over-structured RDFs at short distance, that can be further improved by considering an optimized O-H repulsive potential obtained by the IBI process. Three different schemes were used to optimize this potential: (i) optimization including short O-H distances. This led to accurate RDFs as well as improved self-diffusion coefficient and heat of vaporization, while the proton transfer energy barrier is severely deteriorated; (ii) optimization starting at long distance. The proton transfer energy barrier is recovered while the heat of vaporization is deteriorated and the O-H RDF is less accurate at short distance; (iii) optimization within the path-integral molecular dynamics scheme which allows us to exclude nuclear quantum effects from the repulsive potential. The latter potential, in conjunction with the WMull improved atomic charges, provides similar results as (i) for structural, dynamic, and thermodynamic properties while recovering a large part of the proton transfer energy barrier. It therefore offers a good compromise to study both dynamic properties and chemistry within liquid water at a quantum chemical level.

Routine Molecular Dynamics Simulations Including Nuclear Quantum Effects: From Force Fields to Machine Learning Potentials

We report the implementation of a multi-CPU and multi-GPU massively parallel platform dedicated to the explicit inclusion of nuclear quantum effects (NQEs) in the Tinker-HP molecular dynamics (MD) package. The platform, denoted Quantum-HP, exploits two simulation strategies: the Ring-Polymer Molecular Dynamics (RPMD) that provides exact structural properties at the cost of a MD simulation in an extended space of multiple replicas and the adaptive Quantum Thermal Bath (adQTB) that imposes the quantum distribution of energy on a classical system via a generalized Langevin thermostat and provides computationally affordable and accurate (though approximate) NQEs. We discuss some implementation details, efficient numerical schemes, and parallelization strategies and quickly review the GPU acceleration of our code. Our implementation allows an efficient inclusion of NQEs in MD simulations for very large systems, as demonstrated by scaling tests on water boxes with more than 200,000 atoms (simulated using the AMOEBA polarizable force field). We test the compatibility of the approach with Tinker-HP's recently introduced Deep-HP machine learning potentials module by computing water properties using the DeePMD potential with adQTB thermostatting. Finally, we show that the platform is also compatible with the alchemical free energy estimation capabilities of Tinker-HP and fast enough to perform simulations. Therefore, we study how NQEs affect the hydration free energy of small molecules solvated with the recently developed Q-AMOEBA water force field. Overall, the Quantum-HP platform allows users to perform routine quantum MD simulations of large condensed-phase systems and will help to shed new light on the quantum nature of important interactions in biological matter.

Capturing the Polarization Response of Solvated Proteins under Constant Electric Fields in Molecular Dynamics Simulations

We capture and compare the polarization response of a solvated globular protein ubiquitin to static electric (E-fields) using atomistic molecular dynamics simulations. We collectively follow E-field induced changes, electrical and structural, occurring across multiple trajectories using the magnitude of the protein dipole vector (P_p ). E-fields antiparallel to P_p induce faster structural changes and more facile protein unfolding relative to parallel fields of the same strength. While weak E-fields (0.1-0.5 V/nm) do not unfold ubiquitin and produce a reversible polarization, strong E-fields (1-2 V/nm) unfold the protein through a pathway wherein the helix:β-strand interactions rupture before those for the β1-β5 clamp. Independent of E-field direction, high E-field induced structural changes are also reversible if the field is switched off before P_p exceeds 2 times its equilibrium value. We critically examine the dependence of water properties, protein rotational diffusion and E-field induced protein unfolding pathways on the thermostat/barostat parameters used in our simulations.

In situ diffraction monitoring of nanocrystals structure evolving during catalytic reaction at their surface

With decreasing size of crystals the number of their surface atoms becomes comparable to the number of bulk atoms and their powder diffraction pattern becomes sensitive to a changing surface structure. On the example of nanocrystalline gold supported on also nanocrystalline [Formula: see text] we show evolution of (a) the background pattern due to chemisorption phenomena, (b) peak positions due to adsorption on nonstoichiometric [Formula: see text] particles, (c) Au peaks intensity. The results of the measurements, complemented with mass spectrometry gas analysis, point to (1) a multiply twinned structure of gold, (2) high mobility of Au atoms enabling transport phenomena of Au atoms to the surface of ceria while varying the amount of Au in the crystalline form, and (3) reversible [Formula: see text] peaks position shifts on exposure to He-X-He where X is O₂, H₂, CO or CO oxidation reaction mixture, suggesting solely internal alternations of the [Formula: see text] crystal structure. We found no evidence of ceria lattice oxygen being consumed/supplied at any stage of the process. The work shows possibility of structurally interpreting different contributions to the multi-phase powder diffraction pattern during a complex physico-chemical process, including effects of physi-, chemisorption and surface evolution. It shows a way to structurally interpret heterogeneous catalytic reactions even if no bulk phase transition is involved.

The structure of protic ionic liquids based on sulfuric acid, doped with excess of sulfuric acid or with water

Neutron scattering with isotopic substitution was used to study the structure of concentrated sulfuric acid, and two protic ionic liquids (PILs): a Brønsted-acidic PIL, synthesised using pyridine and excess of sulfuric acid, [Hpy][HSO₄]·H₂SO₄, and a hydrated PIL, in which an equimolar mixture of sulfuric acid and pyridine has been doped with water, [Hpy][HSO₄]·2H₂O. Brønsted acidic PILs are excellent solvents/catalysts for esterifications, driving reaction to completion by phase-separating water and ester products. Water-doped PILs are efficient solvents/antisolvents in biomass fractionation. This study was carried out to provide an insight into the relationship between the performance of PILs in the two respective processes and their liquid structure. It was found that a persistent sulfate/sulfuric acid/water network structure was retained through the transition from sulfuric acid to PILs, even in the presence of 2 moles (∼17 wt%) of water. Hydrogen sulfate PILs have the propensity to incorporate water into hydrogen-bonded anionic chains, with strong and directional hydrogen bonds, which essentially form a new water-in-salt solvent system, with its own distinct structure and physico-chemical properties. It is the properties of this hydrated PIL that can be credited both for the good performance in esterification and beneficial solvent/antisolvent behaviour in biomass fractionation.

The ability of trimethylamine N-oxide to resist pressure induced perturbations to water structure

Trimethylamine N-oxide (TMAO) protects organisms from the damaging effects of high pressure. At the molecular level both TMAO and pressure perturb water structure but it is not understood how they act in combination. Here, we use neutron scattering coupled with computational modelling to provide atomistic insight into the structure of water under pressure at 4 kbar in the presence and absence of TMAO. The data reveal that TMAO resists pressure-induced perturbation to water structure, particularly in retaining a clear second solvation shell, enhanced hydrogen bonding between water molecules and strong TMAO - water hydrogen bonds. We calculate an 'osmolyte protection' ratio at which pressure and TMAO-induced energy changes effectively cancel out. Remarkably this ratio translates across scales to the organism level, matching the observed concentration dependence of TMAO in the muscle tissue of organisms as a function of depth. Osmolyte protection may therefore offer a molecular mechanism for the macroscale survival of life in extreme environments.

Neutron Diffraction Study of Indole Solvation in Deep Eutectic Systems of Choline Chloride, Malic Acid, and Water

Deep eutectic systems are currently under intense investigation to replace traditional organic solvents in a range of syntheses. Here, indole in choline chloride‐malic acid deep eutectic solvent (DES) was studied as a function of water content, to identify solute interactions with the DES which affect heterocycle reactivity and selectivity, and as a proxy for biomolecule solvation. Empirical Potential Structure Refinement models of neutron diffraction data showed [Cholinium]⁺ cations associate strongly with the indole π‐system due to electrostatics, whereas malic acid is only weakly associated. Trace water is sequestered into the DES and does not interact strongly with indole. When water is added to the DES, it does not interact with the indole π‐system but is exclusively in‐plane with the heterocyclic rings, forming strong H‐bonds with the ‐NH group, and also weak H‐bonds and thus prominent hydrophobic hydration of the indole aromatic region, which could direct selectivity in reactions.

Accurate diffusion coefficients of the excess proton and hydroxide in water via extensive ab initio simulations with different schemes

Despite its simple molecular formula, obtaining an accurate in silico description of water is far from straightforward. Many of its very peculiar properties are quite elusive, and in particular, obtaining good estimations of the diffusion coefficients of the solvated proton and hydroxide at a reasonable computational cost has been an unsolved challenge until now. Here, I present extensive results of several unusually long ab initio molecular dynamics (MD) simulations employing different combinations of the Born-Oppenheimer and second-generation Car-Parrinello MD propagation methods with different ensembles (NVE and NVT) and thermostats, which show that these methods together with the RPBE-D3 functional provide a very accurate estimation of the diffusion coefficients of the solvated H₃O⁺ and OH^- ions, together with an extremely accurate description of several properties of neutral water (such as the structure of the liquid and its diffusion and shear viscosity coefficients). In addition, I show that the estimations of D_H3O⁺ and D_OH^- depend dramatically on the simulation length, being necessary to reach timescales in the order of hundreds of picoseconds to obtain reliable results.

Cuts through the manifold of molecular H2O potential energy surfaces in liquid water at ambient conditions

Liquid water at ambient conditions is ubiquitous in chemistry and biology as well as in technology, energy, and atmospheric processes. Since parts of the phase diagram of water are unsettled—most notably the supercooled liquid homogeneous nucleation region—repercussions thereof on our molecular-level understanding for even the common ambient conditions remain. Breathtaking advances in X-ray–based approaches over the last decade give us now the tools to derive molecular potential energy surfaces as a quantitative view on the molecular manifold within the fluctuating hydrogen bonding network. With selective cuts along the local asymmetric O–H bond coordinate and the symmetric normal mode excitations an experimental foundation to benchmark competing molecular-level models of water has been achieved.

The fluctuating hydrogen bridge bonded network of liquid water at ambient conditions entails a varied ensemble of the underlying constituting H₂O molecular moieties. This is mirrored in a manifold of the H₂O molecular potentials. Subnatural line width resonant inelastic X-ray scattering allowed us to quantify the manifold of molecular potential energy surfaces along the H₂O symmetric normal mode and the local asymmetric O–H bond coordinate up to 1 and 1.5 Å, respectively. The comparison of the single H₂O molecular potentials and spectroscopic signatures with the ambient conditions liquid phase H₂O molecular potentials is done on various levels. In the gas phase, first principles, Morse potentials, and stepwise harmonic potential reconstruction have been employed and benchmarked. In the liquid phase the determination of the potential energy manifold along the local asymmetric O–H bond coordinate from resonant inelastic X-ray scattering via the bound state oxygen 1s to 4a1 resonance is treated within these frameworks. The potential energy surface manifold along the symmetric stretch from resonant inelastic X-ray scattering via the oxygen 1s to 2b2 resonance is based on stepwise harmonic reconstruction. We find in liquid water at ambient conditions H₂O molecular potentials ranging from the weak interaction limit to strongly distorted potentials which are put into perspective to established parameters, i.e., intermolecular O–H, H–H, and O–O correlation lengths from neutron scattering.

Structures of liquid and aqueous water isotopologues at ambient temperature from ab initio path integral simulations

The heavy hydrogen isotopes D and T are found in trace amounts in water, and when their concentration increases they can play an intricate role in modulating the physical properties of the liquid. We present an analysis of the microscopic structures of ambient light water (H₂O(l)), heavy water (D₂O(l)), T₂O(l), HDO(aq) and HTO(aq) studied by ab initio path integral molecular dynamics (PIMD). Unlike previous ab initio PIMD investigations of H₂O(l) and D₂O(l) [Chen et al., Phys. Rev. Lett., 2003, 91, 215503] [Machida et al., J. Chem. Phys., 2017, 148, 102324] we find that D₂O(l) is more structured than H₂O(l), as is predicted by the experiment. The agreement between the experiment and our simulation for H₂O(l) and D₂O(l) allows us to accurately predict the intra- and intermolecular structures of T₂O(l) HDO(aq) and HTO(aq). T₂O(l) is found to have a similar intermolecular structure to that of D₂O(l), while the intramolecular structure is more compact, giving rise to a smaller dipole moment than those of H₂O(l) and D₂O(l). For the mixed isotope species, HDO(aq) and HTO(aq), we find smaller dipole moments and fewer hydrogen bonds when compared with the pure species H₂O and D₂O. We can attribute this effect to the relative compactness of the mixed isotope species, which results in a lower dipole moment than that of the pure species.

The nano- and meso-scale structure of amorphous calcium carbonate

Understanding the underlying processes of biomineralization is crucial to a range of disciplines allowing us to quantify the effects of climate change on marine organisms, decipher the details of paleoclimate records and advance the development of biomimetic materials. Many biological minerals form via intermediate amorphous phases, which are hard to characterize due to their transient nature and a lack of long-range order. Here, using Monte Carlo simulations constrained by X-ray and neutron scattering data together with model building, we demonstrate a method for determining the structure of these intermediates with a study of amorphous calcium carbonate (ACC) which is a precursor in the bio-formation of crystalline calcium carbonates. We find that ACC consists of highly ordered anhydrous nano-domains of approx. 2 nm that can be described as nanocrystalline. These nano-domains are held together by an interstitial net-like matrix of water molecules which generate, on the mesoscale, a heterogeneous and gel-like structure of ACC. We probed the structural stability and dynamics of our model on the nanosecond timescale by molecular dynamics simulations. These simulations revealed a gel-like and glassy nature of ACC due to the water molecules and carbonate ions in the interstitial matrix featuring pronounced orientational and translational flexibility. This allows for viscous mobility with diffusion constants four to five orders of magnitude lower than those observed in solutions. Small and ultra-small angle neutron scattering indicates a hierarchically-ordered organization of ACC across length scales that allow us, based on our nano-domain model, to build a comprehensive picture of ACC formation by cluster assembly from solution. This contribution provides a new atomic-scale understanding of ACC and provides a framework for the general exploration of biomineralization and biomimetic processes.

Structural Effects of pH Variation and Calcium Amount on the Microencapsulation of Glutathione in Alginate Polymers

Reduced glutathione (GSH) has a high antioxidant capacity and is present in nearly every cell in the body, playing important roles in nutrient metabolism, antioxidant defense, and regulation of cellular events. Conversely, alginate is a macromolecule that has been widely used in the food, pharmaceutical, biomedical, and textile industries due to its biocompatibility, biodegradability, nontoxicity, and nonimmunogenicity as well as for its capabilities of retaining water and stabilizing emulsions. The primary goal of this study was to characterize and optimize the formation of a molecular complex of calcium alginate with GSH using a computational approach. As methods, we evaluated the influence of varying the amount of calcium cations at two different pHs on the structural stability of Ca²⁺-alginate complexes and thus on GSH liberation from these types of nanostructures. The results showed that complex stabilization depends on pH, with the system having a lower Ca²⁺ amount that produces the major GSH release. The systems at pH 2.5 retain more molecules within the calcium-alginate complex, which release GSH more slowly when embedded in more acidic media. In conclusions, this study demonstrates the dependence of the amount of calcium and the stabilizing effect of pH on the formation and subsequent maintenance of an alginate nanostructure. The results presented in this study can help to develop better methodological frameworks in industries where the release or capture of compounds, such as GSH in this case, depends on the conditions of the alginate nanoparticle.

Predicting properties of periodic systems from cluster data: A case study of liquid water

The accuracy of the training data limits the accuracy of bulk properties from machine-learned potentials. For example, hybrid functionals or wave-function-based quantum chemical methods are readily available for cluster data but effectively out of scope for periodic structures. We show that local, atom-centered descriptors for machine-learned potentials enable the prediction of bulk properties from cluster model training data, agreeing reasonably well with predictions from bulk training data. We demonstrate such transferability by studying structural and dynamical properties of bulk liquid water with density functional theory and have found an excellent agreement with experimental and theoretical counterparts.

Ab Initio Simulations of Water/Metal Interfaces

Structures and processes at water/metal interfaces play an important technological role in electrochemical energy conversion and storage, photoconversion, sensors, and corrosion, just to name a few. However, they are also of fundamental significance as a model system for the study of solid-liquid interfaces, which requires combining concepts from the chemistry and physics of crystalline materials and liquids. Particularly interesting is the fact that the water-water and water-metal interactions are of similar strength so that the structures at water/metal interfaces result from a competition between these comparable interactions. Because water is a polar molecule and water and metal surfaces are both polarizable, explicit consideration of the electronic degrees of freedom at water/metal interfaces is mandatory. In principle, ab initio molecular dynamics simulations are thus the method of choice to model water/metal interfaces, but they are computationally still rather demanding. Here, ab initio simulations of water/metal interfaces will be reviewed, starting from static systems such as the adsorption of single water molecules, water clusters, and icelike layers, followed by the properties of liquid water layers at metal surfaces. Technical issues such as the appropriate first-principles description of the water-water and water-metal interactions will be discussed, and electrochemical aspects will be addressed. Finally, more approximate but numerically less demanding approaches to treat water at metal surfaces from first-principles will be briefly discussed.

Structural Analysis of Molecular Materials Using the Pair Distribution Function

This is a review of atomic pair distribution function (PDF) analysis as applied to the study of molecular materials. The PDF method is a powerful approach to study short- and intermediate-range order in materials on the nanoscale. It may be obtained from total scattering measurements using X-rays, neutrons, or electrons, and it provides structural details when defects, disorder, or structural ambiguities obscure their elucidation directly in reciprocal space. While its uses in the study of inorganic crystals, glasses, and nanomaterials have been recently highlighted, significant progress has also been made in its application to molecular materials such as carbons, pharmaceuticals, polymers, liquids, coordination compounds, composites, and more. Here, an overview of applications toward a wide variety of molecular compounds (organic and inorganic) and systems with molecular components is presented. We then present pedagogical descriptions and tips for further implementation. Successful utilization of the method requires an interdisciplinary consolidation of material preparation, high quality scattering experimentation, data processing, model formulation, and attentive scrutiny of the results. It is hoped that this article will provide a useful reference to practitioners for PDF applications in a wide realm of molecular sciences, and help new practitioners to get started with this technique.

Comparison of molecular dynamics simulations of water with neutron and X-ray scattering experiments

The atomistic structure and dynamics obtained from molecular dynamics (MD) simulations with the example of TIP3P (rigid and flexible) and TIP4P/2005 (rigid) water is compared to neutron and X-ray scattering data at ambient conditions. Neutron and X-ray diffractograms are calculated from the simulations for four isotopic substitutions as well as the incoherent intermediate scattering function for neutrons. The resulting curves are compared to each other and to published experimental data. Differences between simulated and measured intermediate scattering functions are quantified by fitting an analytic model to the computed values. The sensitivity of the scattering curves to the parameters of the MD simulations is demonstrated on the example of two parameters, bond length and angle.

Wavefunction-Based Electrostatic-Embedding QM/MM Using CFOUR through MiMiC

We present an interface of the wavefunction-based quantum chemical software CFOUR to the multiscale modeling framework MiMiC. Electrostatic embedding of the quantum mechanical (QM) part is achieved by analytic evaluation of one-electron integrals in CFOUR, while the rest of the QM/molecular mechanical (MM) operations are treated according to the previous MiMiC-based QM/MM implementation. Long-range electrostatic interactions are treated by a multipole expansion of the potential from the QM electron density to reduce the computational cost without loss of accuracy. Testing on model water/water systems, we verified that the CFOUR interface to MiMiC is robust, guaranteeing fast convergence of the self-consistent field cycles and optimal conservation of the energy during the integration of the equations of motion. Finally, we verified that the CFOUR interface to MiMiC is compatible with the use of a QM/QM multiple time-step algorithm, which effectively reduces the cost of ab initio MD (AIMD) or QM/MM-MD simulations using higher level wavefunction-based approaches compared to cheaper density functional theory-based ones. The new wavefunction-based AIMD and QM/MM-MD implementations were tested and validated for a large number of wavefunction approaches, including Hartree-Fock and post-Hartree-Fock methods like Møller-Plesset, coupled-cluster, and complete active space self-consistent field.

Anomalous temperature dependence of the experimental x-ray structure factor of supercooled water

The structural changes of water upon deep supercooling were studied through wide-angle x-ray scattering at SwissFEL. The experimental setup had a momentum transfer range of 4.5 Å^-1, which covered the principal doublet of the x-ray structure factor of water. The oxygen-oxygen structure factor was obtained for temperatures down to 228.5 ± 0.6 K. Similar to previous studies, the second diffraction peak increased strongly in amplitude as the structural change accelerated toward a local tetrahedral structure upon deep supercooling. We also observed an anomalous trend for the second peak position of the oxygen-oxygen structure factor (q₂). We found that q₂ exhibits an unprecedented positive partial derivative with respect to temperature for temperatures below 236 K. Based on Fourier inversion of our experimental data combined with reference data, we propose that the anomalous q₂ shift originates from that a repeat spacing in the tetrahedral network, associated with all peaks in the oxygen-oxygen pair-correlation function, gives rise to a less dense local ordering that resembles that of low-density amorphous ice. The findings are consistent with that liquid water consists of a pentamer-based hydrogen-bonded network with low density upon deep supercooling.

Bridging Structure, Dynamics, and Thermodynamics: An Example Study on Aqueous Potassium Halides

Aqueous salt systems are ubiquitous in all areas of life. The ions in these solutions impose important structural and dynamic perturbations to water. In this study, we employ a combined neutron scattering, nuclear magnetic resonance, and computational modeling approach to deconstruct ion-specific perturbations to water structure and dynamics and shed light on the molecular origins of bulk thermodynamic properties of the solutions. Our approach uses the atomistic scale resolution offered to us by neutron scattering and computational modeling to investigate how the properties of particular short-ranged microenvironments within aqueous systems can be related to bulk properties of the system. We find that by considering only the water molecules in the first hydration shell of the ions that the enthalpy of hydration can be determined. We also quantify the range over which ions perturb water structure by calculating the average enthalpic interaction between a central halide anion and the surrounding water molecules as a function of distance and find that the favorable anion-water enthalpic interactions only extend to ∼4 Å. We further validate this by showing that ions induce structure in their solvating water molecules by examining the distribution of dipole angles in the first hydration shell of the ions but that this perturbation does not extend into the bulk water. We then use these structural findings to justify mathematical models that allow us to examine perturbations to rotational and diffusive dynamics in the first hydration shell around the potassium halide ions from NMR measurements. This shows that as one moves down the halide series from fluorine to iodine, and ionic charge density is therefore reduced, that the enthalpy of hydration becomes less negative. The first hydration shell also becomes less well structured, and rotational and diffusive motions of the hydrating water molecules are increased. This reduction in structure and increase in dynamics are likely the origin of the previously observed increased entropy of hydration as one moves down the halide series. These results also suggest that simple monovalent potassium halide ions induce mostly local perturbations to water structure and dynamics.

Ab initio study of nuclear quantum effects on sub- and supercritical water

The structures of water in the ambient, subcritical, and supercritical conditions at various densities were studied systematically by ab initio path integral molecular dynamics simulations. It was found that the nuclear quantum effects (NQEs) have a significant impact on the structure of hydrogen bonds in close contact, not only in the ambient condition but also in the sub- and supercritical conditions. The NQEs on the structure beyond the hydrogen bond contact are important in ambient water, but not much for water in the sub- and supercritical conditions. The NQEs are furthermore important for determining the number of hydrogen bonds in the ambient conditions, and this role is, however, diminished in the sub- and supercritical conditions. The NQEs do, nevertheless, show their importance in determining the intramolecular structure of water and the close contact structures of the hydrogen bonds, even at sub- and supercritical conditions. Using the RPBE-D3 functional, the computed radial distribution functions for ambient water are in excellent agreement with experimental data, upgrading our previous results using the BLYP-D2 functional [Machida et al., J. Chem. Phys. 148, 102324 (2018)]. The computed radial distribution functions for water in the sub- and supercritical conditions were carefully compared with experiment. In particular, we found that the first peak in hydrogen pair distribution functions matches only when the NQEs are taken into account.

Polarizable Water Potential Derived from a Model Electron Density

A new empirical potential for efficient, large scale molecular dynamics simulation of water is presented. The HIPPO (Hydrogen-like Intermolecular Polarizable POtential) force field is based upon the model electron density of a hydrogen-like atom. This framework is used to derive and parametrize individual terms describing charge penetration damped permanent electrostatics, damped polarization, charge transfer, anisotropic Pauli repulsion, and damped dispersion interactions. Initial parameter values were fit to Symmetry Adapted Perturbation Theory (SAPT) energy components for ten water dimer configurations, as well as the radial and angular dependence of the canonical dimer. The SAPT-based parameters were then systematically refined to extend the treatment to water bulk phases. The final HIPPO water model provides a balanced representation of a wide variety of properties of gas phase clusters, liquid water, and ice polymorphs, across a range of temperatures and pressures. This water potential yields a rationalization of water structure, dynamics, and thermodynamics explicitly correlated with an ab initio energy decomposition, while providing a level of accuracy comparable or superior to previous polarizable atomic multipole force fields. The HIPPO water model serves as a cornerstone around which similarly detailed physics-based models can be developed for additional molecular species.

Investigating the Accuracy of Water Models through the Van Hove Correlation Function

We present molecular-simulation-based calculations of the Van Hove correlation function (VHF) of water using multiple modeling approaches: classical molecular dynamics with simple three-site nonpolarizable models, with a polarizable model, and with a reactive force field; density functional tight-binding molecular dynamics; and ab initio molecular dynamics. Due to the many orders of magnitude difference in the computational cost of these approaches, we investigate how small and short the simulations can be while still yielding sufficiently accurate and interpretable results for the VHF. We investigate the accuracy of the different models by comparing them to recently published inelastic X-ray scattering measurements of the VHF. We find that all of the models exhibit qualitative agreement with the experiments, and in some models and for some properties, the agreement is quantitative. This work lays the foundation for future simulation approaches to calculating the VHF for aqueous solutions in bulk and under nanoconfinement.

Using Neural Network Force Fields to Ascertain the Quality of Ab Initio Simulations of Liquid Water

Accurately simulating the properties of bulk water, despite the apparent simplicity of the molecule, is still a challenge. In order to fully understand and reproduce its complex phase diagram, it is necessary to perform simulations at the ab initio level, including quantum mechanical effects both for electrons and nuclei. This comes at a high computational cost, given that the structural and dynamical properties tend to require long timescales and large simulation cells. In this work, we evaluate the errors that density functional theory (DFT)-based simulations routinely incur into due time- and size-scale limitations. These errors are evaluated using neural-network-trained force fields that are accurate at the level of DFT methods. We compare different exchange and correlation potentials for properties of bulk water that require large timescales. We show that structural properties are less dependent on the system size and that dynamical properties such as the diffusion coefficient have a strong dependence on the simulation size and timescale. Our results facilitate comparisons of DFT-based simulation results with experiments and offer a path to discriminate between model and convergence errors in these simulations.

On Structural Rearrangements Near the Glass Transition Temperature in Amorphous Silica

The formation of clusters was analyzed in a topologically disordered network of bonds of amorphous silica (SiO₂) based on the Angell model of broken bonds termed configurons. It was shown that a fractal-dimensional configuron phase was formed in the amorphous silica above the glass transition temperature T_g. The glass transition was described in terms of the concepts of configuron percolation theory (CPT) using the Kantor-Webman theorem, which states that the rigidity threshold of an elastic percolating network is identical to the percolation threshold. The account of configuron phase formation above T_g showed that (i) the glass transition was similar in nature to the second-order phase transformations within the Ehrenfest classification and that (ii) although being reversible, it occurred differently when heating through the glass–liquid transition to that when cooling down in the liquid phase via vitrification. In contrast to typical second-order transformations, such as the formation of ferromagnetic or superconducting phases when the more ordered phase is located below the transition threshold, the configuron phase was located above it.

Properties of the Pt(111)/electrolyte electrochemical interface studied with a hybrid DFT-solvation approach

Self-consistent modeling of the interface between solid metal electrode and liquid electrolyte is a crucial challenge in computational electrochemistry. In this contribution, we adopt the effective screening medium reference interaction site method (ESM-RISM) to study the charged interface between a Pt(111) surface that is partially covered with chemisorbed oxygen and an aqueous acidic electrolyte. This method proves to be well suited to describe the chemisorption and charging state of the interface at controlled electrode potential. We present an in-depth assessment of the ESM-RISM parameterization and of the importance of computing near-surface water molecules explicitly at the quantum mechanical level. We found that ESM-RISM is able to reproduce some key interface properties, including the peculiar, non-monotonic charging relation of the Pt(111)/electrolyte interface. The comparison with independent theoretical models and explicit simulations of the interface reveals strengths and limitations of ESM-RISM for modeling electrochemical interfaces.

Intermediate Range Order in Metal-Ammonia Solutions: Pure and Na-Doped Ca-NH3

The local and intermediate range ordering in Ca-NH₃ solutions in their metallic phase is determined through H/D isotopically differenced neutron diffraction in combination with empirical potential structure refinements. For both low and high relative Ca concentrations, the Ca ions are found to be octahedrally coordinated by the NH₃ solvent, and these hexammine units are spatially correlated out to lengthscales of ∼7.4-10.3 Å depending on the concentration, leading to pronounced ordering in the bulk liquid. We further demonstrate that this liquid order can be progressively disrupted by the substitution of Ca for Na, whereby a distortion of the average ion primary solvation occurs and the intermediate range ion-ion correlations are disrupted.

Mutually Beneficial Combination of Molecular Dynamics Computer Simulations and Scattering Experiments

We showcase the combination of experimental neutron scattering data and molecular dynamics (MD) simulations for exemplary phospholipid membrane systems. Neutron and X-ray reflectometry and small-angle scattering measurements are determined by the scattering length density profile in real space, but it is not usually possible to retrieve this profile unambiguously from the data alone. MD simulations predict these density profiles, but they require experimental control. Both issues can be addressed simultaneously by cross-validating scattering data and MD results. The strengths and weaknesses of each technique are discussed in detail with the aim of optimizing the opportunities provided by this combination.

Liquid structure and dynamics in the choline acetate:urea 1:2 deep eutectic solvent

We report on the thermodynamic, structural, and dynamic properties of a recently proposed deep eutectic solvent, formed by choline acetate (ChAc) and urea (U) at the stoichiometric ratio 1:2, hereinafter indicated as ChAc:U. Although the crystalline phase melts at 36-38 °C depending on the heating rate, ChAc:U can be easily supercooled at sub-ambient conditions, thus maintaining at the liquid state, with a glass-liquid transition at about -50 °C. Synchrotron high energy x-ray scattering experiments provide the experimental data for supporting a reverse Monte Carlo analysis to extract structural information at the atomistic level. This exploration of the liquid structure of ChAc:U reveals the major role played by hydrogen bonding in determining interspecies correlations: both acetate and urea are strong hydrogen bond acceptor sites, while both choline hydroxyl and urea act as HB donors. All ChAc:U moieties are involved in mutual interactions, with acetate and urea strongly interacting through hydrogen bonding, while choline being mostly involved in van der Waals mediated interactions. Such a structural situation is mirrored by the dynamic evidences obtained by means of ¹H nuclear magnetic resonance techniques, which show how urea and acetate species experience higher translational activation energy than choline, fingerprinting their stronger commitments into the extended hydrogen bonding network established in ChAc:U.

Tuning the solvation of indigo in aqueous deep eutectics

The solubility of synthetic indigo dye was measured at room temperature in three deep eutectic solvents (DESs)-1:3 choline chloride:1,4-butanediol, 1:3 tetrabutylammonium bromide:1,4-butanediol, and 1:2 choline chloride:p-cresol-to test the hypothesis that the structure of DESs can be systematically altered, to induce specific DES-solute interactions, and, thus, tune solubility. DESs were designed starting from the well-known cholinium chloride salt mixed with the partially amphiphilic 1,4-butanediol hydrogen bond donor (HBD), and then, the effect of increasing salt hydrophobicity (tetrabutylammonium bromide) and HBD hydrophobicity (p-cresol) was explored. Measurements were made between 2.5 and 25 wt. % H₂O, as a reasonable range representing atmospherically absorbed water, and molecular dynamics simulations were used for structural analysis. The choline chloride:1,4-butanediol DES had the lowest indigo solubility, with only the hydrophobic character of the alcohol alkyl spacers. Solubility was highest for indigo in the tetrabutylammonium bromide:1,4-butanediol DES with 2.5 wt. % H₂O due to interactions of indigo with the hydrophobic cation, but further addition of water caused this to reduce in line with the added water mole fraction, as water solvated the cation and reduced the extent of the hydrophobic region. The ChCl:p-cresol DES did not have the highest solubility at 2.5 wt. % H₂O, but did at 25 wt. % H₂O. Radial distribution functions, coordination numbers, and spatial distribution functions demonstrate that this is due to strong indigo-HBD interactions, which allow this system to resist the higher mole fraction of water molecules and retain its solubility. The DES is, therefore, a host to local-composition effects in solvation, where its hydrophobic moieties concentrate around the hydrophobic solute, illustrating the versatility of DES as solvents.

Aqueous choline amino acid deep eutectic solvents

We have investigated the structure and phase behavior of biocompatible, aqueous deep eutectic solvents by combining choline acetate, hydrogen aspartate, and aspartate amino acid salts with water as the sole molecular hydrogen bond donor. Using contrast-variation neutron diffraction, interpreted via computational modeling, we show how the interplay between anion structure and water content affects the hydrogen bond network structure in the liquid, which, in turn, influences the eutectic composition and temperature. These mixtures expand the current range choline amino acid ionic liquids under investigation for biomass processing applications to include higher melting point salts and also explain how the ionic liquids retain their desirable properties in aqueous solution.

Role of water model on ion dissociation at ambient conditions

We study ion pair dissociation in water at ambient conditions using a combination of classical and ab initio approaches. The goal of this study is to disentangle the sources of discrepancy observed in computed potentials of mean force. In particular, we aim to understand why some models favor the stability of solvent-separated ion pairs vs contact ion pairs. We found that some observed differences can be explained by non-converged simulation parameters. However, we also unveil that for some models, small changes in the solution density can have significant effects on modifying the equilibrium balance between the two configurations. We conclude that the thermodynamic stability of contact and solvent-separated ion pairs is very sensitive to the dielectric properties of the underlying simulation model. In general, classical models are very robust in providing a similar estimation of the contact ion pair stability, while this is much more variable in density functional theory-based models. The barrier to transition from the solvent-separated to contact ion pair is fundamentally dependent on the balance between electrostatic potential energy and entropy. This reflects the importance of water intra- and inter-molecular polarizability in obtaining an accurate description of the screened ion-ion interactions.

Adsorption of simple gases into the porous glass MCM-41

The porous glass MCM-41 is an important adsorbent to study the process of adsorption of gases onto a cylindrical surface. In this work, we study the adsorption of oxygen, nitrogen, deuterium, and deuteriated methane gases into MCM-41 using a combination of neutron diffraction analysis and atomistic computer modeling to interpret the measured data. Adsorption is achieved by immersing a sample of MCM-41 in a bath of the relevant gas, keeping the gas pressure constant (0.1 MPa), and lowering the temperature in steps toward the corresponding bulk liquid boiling point. All four gases have closely analogous behaviors, with an initial layering of liquid on the inside surface of the pores, followed by a relatively sharp capillary condensation (CC) when the pore becomes filled with dense fluid, signaled by a sharp decrease in the intensity of (100) Bragg diffraction reflection. At the temperature of CC, there is a marked distortion of the hexagonal lattice of pores, as others have seen, which relaxes close to the original structure after CC, and this appears to be accompanied by notable excess heterogeneity along the pore compared to when CC is complete. In none of the four gases studied does the final density of fluid in the pore fully attain the value of the bulk liquid at its boiling point at this pressure, although it does approach that limit closely near the center of the pore, and in all cases, the pronounced layering near the silica interface seen in previous studies is observed here as well.

Proton transfer in bulk water using the full adaptive QM/MM method: integration of solute- and solvent-adaptive approaches

The quantum mechanical/molecular mechanical (QM/MM) method is a hybrid molecular simulation technique that increases the accessibility of local electronic structures of large systems. The technique combines the benefit of accuracy found in the QM method and that of cost efficiency found in the MM method. However, it is difficult to directly apply the QM/MM method to the dynamics of solution systems, particularly for proton transfer. As explained in the Grotthuss mechanism, proton transfer is a structural interconversion between hydronium ions and solvent water molecules. Hence, when the QM/MM method is applied, an adaptive treatment, namely on-the-fly revisions on molecular definitions, is required for both the solute and solvent. Although several solvent-adaptive methods have been proposed, a full adaptive framework, which is an approach that also considers adaptation for solutes, remains untapped. In this paper, we propose a new numerical expression for the coordinates of the excess proton and its control algorithm. Furthermore, we confirm that this method can stably and accurately simulate proton transfer dynamics in bulk water.

Advantages of a curved image plate for rapid laboratory-based x-ray total scattering measurements: Application to pair distribution function analysis

The analysis and interpretation of the pair distribution function (PDF), as derived from total scattering measurements, is still seen by many as a technique confined to central synchrotron and neutron facilities. This situation has begun to change with a rising visibility of total scattering experiments reported in mainstream scientific journals and the modification of an increasing number of laboratory diffractometers. However, the rigor required during data reduction and the complexities of data interpretation mean the technique is still very far from being routine. Herein, we report the first application of a large area curved image plate system based on a Rigaku SPIDER (R-AXIS RAPID II) equipped with an Ag tube for collecting data amenable to high quality PDF refinement/modeling of crystalline, amorphous, and liquid samples. The advantages of such a system are the large Q range available without scanning (routinely in excess of 20 Å^-1) and the inherent properties of an image plate detector (single photon sensitivity, large dynamic range [1.05 × 10⁶], and effectively zero noise). Data are collected and structural models refined for a number of standard materials including NIST 640f silicon for which a R_wp ≤ 0.12 value was obtained with data collected in 60 min (excluding background measurements). These and other data are discussed and compared to similar examples in the literature.