Structure and Dynamics of Liquid Water from ab Initio Molecular Dynamics—Comparison of BLYP, PBE, and revPBE Density Functionals with and without van der Waals Corrections

Water-air interface revisited by means of path-integral ab initio molecular dynamics

Although nuclear quantum effects (NQEs) have been considered on bulk liquid water, the impact of these latter on the air-water interface has not yet been reported. Herein, by performing and comparing ab initio molecular dynamics (AIMD) and path integral AIMD (PI-AIMD) simulations, we reveal the impact of NQEs on structural, dynamical and electronic properties as well as IR spectra of the air-water interface at room temperature. NQEs, being able to describe a more accurate proton delocalization in H-bonded system than AIMD, reveal a different structural arrangement and dynamical behaviour of both bulk and interfacial water molecules in comparison to AIMD results. A more de-structured and de-bound water arrangement and coordination are identified when the quantum nature of nuclei are considered for both bulk and interfacial water molecules. Structural properties, such as inter-/intra-molecular bond lengths, coordination numbers and H-bonding angles of bulk and interfacial water molecules here calculated, are affected by NQEs mitigating the overstructured description given by AIMD. Further evidences of an AIMD overstructured description of bulk water are in the computed IR spectra, where an increased absorption peak intensity and an increased strength of the hydrogen-bond network are alleviated by NQEs. In addition, NQEs show a valuable impact on the electronic structure of the air-water interface, reducing the total valence bandwidth and the electronic energy band-gap when passing from bulk to interfacial water. This work proves how NQEs significantly affect properties and features of the air-water interface, that are essential to accurately describe H-bonded interfacial systems.

PyDFT-QMMM: A modular, extensible software framework for DFT-based QM/MM molecular dynamics

PyDFT-QMMM is a Python-based package for performing hybrid quantum mechanics/molecular mechanics (QM/MM) simulations at the density functional level of theory. The program is designed to treat short-range and long-range interactions through user-specified combinations of electrostatic and mechanical embedding procedures within periodic simulation domains, providing necessary interfaces to external quantum chemistry and molecular dynamics software. To enable direct embedding of long-range electrostatics in periodic systems, we have derived and implemented force terms for our previously described QM/MM/PME approach [Pederson and McDaniel, J. Chem. Phys. 156, 174105 (2022)]. Communication with external software packages Psi4 and OpenMM is facilitated through Python application programming interfaces (APIs). The core library contains basic utilities for running QM/MM molecular dynamics simulations, and plug-in entry-points are provided for users to implement custom energy/force calculation and integration routines, within an extensible architecture. The user interacts with PyDFT-QMMM primarily through its Python API, allowing for complex workflow development with Python scripting, for example, interfacing with PLUMED for free energy simulations. We provide benchmarks of forces and energy conservation for the QM/MM/PME and alternative QM/MM electrostatic embedding approaches. We further demonstrate a simple example use case for water solute in a water solvent system, for which radial distribution functions are computed from 100 ps QM/MM simulations; in this example, we highlight how the solvation structure is sensitive to different basis-set choices due to under- or over-polarization of the QM water molecule's electron density.

PW-SMD: A Plane-Wave Implicit Solvation Model Based on Electron Density for Surface Chemistry and Crystalline Systems in Aqueous Solution

Electron density-based implicit solvation models are a class of techniques for quantifying solvation effects and calculating free energies of solvation without an explicit representation of solvent molecules. Integral to the accuracy of solvation modeling is the proper definition of the solvation shell separating the solute molecule from the solvent environment, allowing for a physical partitioning of the free energies of solvation. Unlike state-of-the-art implicit solvation models for molecular quantum chemistry calculations, e.g., the solvation model based on solute electron density (SMD), solvation models for systems under periodic boundary conditions with plane-wave (PW) basis sets have been limited in their accuracy. Furthermore, a unified implicit solvation model with both homogeneous solution-phase and heterogeneous interfacial structures treated on equal footing is needed. In order to address this challenge, we developed a high-accuracy solvation model for periodic PW calculations that is applicable to molecular, ionic, interfacial, and bulk-phase chemistry. Our model, PW-SMD, is an extension of the SMD molecular solvation model to periodic systems in water. The free energy of solvation is partitioned into the electrostatic and cavity-dispersion-solvent structure (CDS) contributions. The electrostatic contributions of the solvation shell surrounding solute structures are parametrized based on their geometric and physical properties. In addition, the nonelectrostatic contribution to the solvation energy is accounted for by extending the CDS formalism of SMD to incorporate periodic boundary conditions. We validate the accuracy and robustness of our solvation model by comparing predicted solvation free energies against experimental data for molecular and ionic systems, carved-cluster composite energetic models of solvated reaction energies and barriers on surface systems, and deep-learning-accelerated ab initio molecular dynamics (AIMD). Our developed periodic implicit solvation model shows significantly improved accuracy compared to previous work (namely, solvation models in aqueous solution) and can be applied to simulate solvent effects in a wide range of surface and crystalline materials.

Modeling Vibrational Sum Frequency Generation Spectra of Interfacial Water on a Gold Surface: The Role of the Fermi Resonance

Studying the hydrogen bonding structure of H2O at the metal-water interface is a highly complex yet fascinating endeavor. The intricate interactions and diverse orientations of water molecules on metal surfaces with varying potentials pose a significant challenge in elucidating the coupling between O-H stretching and H-O-H bending modes. In this study, we employed DFT-MD simulation to explore how the orientation of interfacial water molecules changes with the applied potential on the Au(111) surface. Based on the surface-specific velocity-velocity correlation function (ssVVCF) formula, we calculated vibrational sum frequency generation (VSFG) spectra for the O-H stretches. We found that three assigned peaks (∼3300, ∼3450, and 3650 cm-1) shifted toward lower frequencies as the potential moved toward more negative values. Our results align remarkably well with experimental Raman spectroscopy data. Notably, our VSFG analysis revealed a significant change in the VSFG spectra of the hydrogen-bonded O-H groups (∼3300 cm-1), switching from a negative to a positive sign with decreasing potential. This alteration suggests a substantial change in the orientation of these low-frequency O-H groups owing to their increased interactions with the Au surface. In contrast, the orientations of both the high-frequency O-H groups (∼3450 cm-1) and the dangling O-H groups (∼3650 cm-1) remained unaffected by the applied potentials. Furthermore, our analysis of the decomposed vibrational density of states (VDOS) for the H-O-H bending mode uncovered the coupling between the H-O-H bending and O-H stretching vibrations, known as the Fermi resonance. Our work suggests that the H-O-H bending vibration becomes restricted when water molecules transition from the ″one-H-down″ to the ″two-H-down″ conformation, leading to a redshift in the O-H stretching vibration through the Fermi resonance. By constructing the VSFG and decomposed VDOS spectra, we gained valuable insights into the structural changes that Raman spectra alone cannot fully interpret. Specifically, our analysis revealed the critical role of the Fermi resonance effect in shaping the spectroscopic signature of interfacial water molecules on the Au(111) surface.

Superdiffusive Rotation of Interfacial Water on Noble Metal Surface

Interfacial water on a metal surface acts as an active layer through the reorientation of water, thereby facilitating the energy transfer and chemical reaction across the metal surface in various physicochemical and industrial processes. However, how this active interfacial water collectively behaves on flat noble metal substrates remains largely unknown due to the experimental limitation in capturing librational vibrational motion of interfacial water and prohibitive computational costs at the first-principles level. Herein, by implementing a machine-learning approach to train neural network potentials, we enable performing advanced molecular dynamics simulations with ab initio accuracy at a nanosecond scale to map the distinct rotational motion of water molecules on a metal surface at room temperature. The vibrational density of states of the interfacial water with two-layer profiles reveals that the rotation and vibration of water within the strong adsorption layer on the metal surface behave as if the water molecules in the bulk ice, wherein the O-H stretching frequency is well consistent with the experimental results. Unexpectedly, the water molecules within the adjacent weak adsorption layer exhibit superdiffusive rotation, contrary to the conventional diffusive rotation of bulk water, while the vibrational motion maintains the characteristic of bulk water. The mechanism underlying this abnormal superdiffusive rotation is attributed to the translation-rotation decoupling of water, in which the translation is restrained by the strong hydrogen bonding within the bilayer interfacial water, whereas the rotation is accelerated freely by the asymmetric water environment. This superdiffusive rotation dynamics may elucidate the experimentally observed large fluctuation of the potential of zero charge on Pt and thereby the conventional Helmholtz layer model revised by including the contribution of interfacial water orientation. The surprising superdiffusive rotation of vicinal water next to noble metals will shed new light on the physicochemical processes and the activity of water molecules near metal electrodes or catalysts.

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.

Electrofreezing of liquid water at ambient conditions

Water is routinely exposed to external electric fields. Whether, for example, at physiological conditions, in contact with biological systems, or at the interface of polar surfaces in countless technological settings, water responds to fields on the order of a few V Å-1 in a manner that is under intense investigation. Dating back to the 19th century, the possibility of solidifying water upon applying electric fields - a process known as electrofreezing - is an alluring promise that has canalized major efforts since, with uncertain outcomes. Here, we perform long (up to 500 ps per field strength) ab initio molecular dynamics simulations of water at ambient conditions under external electric fields. We show that fields of 0.10 - 0.15 V Å-1 induce electrofreezing to a ferroelectric amorphous phase which we term f-GW (ferroelectric glassy water). The transition occurs after ~ 150 ps for a field of 0.15 V Å-1 and after ~ 200 ps for a field of 0.10 V Å-1 and is signaled by a structural and dynamic arrest and the suppression of the fluctuations of the hydrogen bond network. Our work reports evidence of electrofreezing of bulk liquid water at ambient conditions and therefore impacts several fields, from fundamental chemical physics to biology and catalysis.

Balance between Physical Interpretability and Energetic Predictability in Widely Used Dispersion-Corrected Density Functionals

We assess the performance of different dispersion models for several popular density functionals across a diverse set of noncovalent systems, ranging from the benzene dimer to molecular crystals. By analyzing the interaction energies and their individual components, we demonstrate that there exists variability across different systems for empirical dispersion models, which are calibrated for reproducing the interaction energies of specific systems. Thus, parameter fitting may undermine the underlying physics, as dispersion models rely on error compensation among the different components of the interaction energy. Energy decomposition analyses reveal that, the accuracy of revPBE-D3 for some aqueous systems originates from significant compensation between dispersion and charge transfer energies. However, revPBE-D3 is less accurate in describing systems where error compensation is incomplete, such as the benzene dimer. Such cases highlight the propensity for unpredictable behavior in various dispersion-corrected density functionals across a wide range of molecular systems, akin to the behavior of force fields. On the other hand, we find that SCAN-rVV10, a targeted-dispersion approach, affords significant reductions in errors associated with the lattice energies of molecular crystals, while it has limited accuracy in reproducing structural properties. Given the ubiquitous nature of noncovalent interactions and the key role of density functional theory in computational sciences, the future development of dispersion models should prioritize the faithful description of the dispersion energy, a shift that promises greater accuracy in capturing the underlying physics across diverse molecular and extended systems.

Probing the dynamic behaviour and magnetic identification of seven coordinated Mn(II) complexes: a combined AIMD and multi-reference approach

We present an in-depth solution phase dynamics of rare seven coordinated pentagonal bipyramidal Mn(II) complexes, together with their binding affinity anticipated using ab initio molecular dynamics (AIMD) simulations and density functional theory (DFT). Moreover, the simulations at different temperatures (25 °C and 90 °C) interpret the rigidity and stability of the ligands with Mn(II) ions. An intuitive approach for modulating the easy plane magnetic anisotropy of the mononuclear Mn(II) complex has been revealed by this work. In this regard, we have performed an extensive theoretical study based on the ab initio CASSCF/NEVPT2 method, exhibiting the presence of an easy plane magnetic anisotropy with a positive value of axial zero-field splitting (ZFS) parameter D. The complex's magnetic properties and electronic relaxation reveal that the rhombic ZFS term (E) can be modulated as the symmetry around the Mn(II) ion varies. The magnitude of the D-value increased with a more symmetrical equatorial ligand as found in the order of [Mn(pydpa)(H2O)] > [Mn(cbda)(H2O)]- > [Mn(dpaaa)(H2O)]- > [Mn(dpasam)(H2O)]-. Furthermore, we found that substituting the equatorial oxygen atom with heavier S and Se-donor atoms switches the sign of magnetic anisotropy for the Mn(II) complexes. The magnitude of the D-value increased when the energy levels of the ground state (GS) and the first excited state (ES) decreased. The observed magneto-structural correlation reveals that shortening the distance of the axial water molecule (Mn-O(w)) increases the D-value by an order of magnitude for the symmetrical [Mn(pydpa)(H2O)] complex. Overall, the combined analysis of solution phase dynamics of Mn(II) complexes and their magnetic characterization opens up new avenues in coordination chemistry, molecular magnetism, spin-crossover materials, and catalysis.

Structure and dynamics of the Li+ ion in water, methanol and acetonitrile solvents: ab initio molecular dynamics simulations

Fundamental understanding of the structure and dynamics of the Li+ ion in solution is of utmost importance in different fields of science and technology, especially in the field of ion batteries. In view of this, ab initio molecular dynamics (AIMD) simulations of the LiCl salt in water, methanol and acetonitrile were performed to elucidate structural parameters such as radial distribution function and coordination number, and dynamical properties like diffusion coefficient, limiting ion conductivity and hydrogen bond correlation function. In the present AIMD simulation, one LiCl in water is equivalent to 0.8 M, which is close to the concentration of the lithium salt used in the Li-ion battery. The first sphere of coordination number of the Li+ ion was reaffirmed to be 4. The radial distribution function for different pairs of atoms is seen to be in good agreement with the experimental results. The calculated potential of mean force indicates the stronger interaction of the Li+ ion with methanol over water followed by acetonitrile. The dynamical parameters convey quite high diffusion and limiting ionic conductivity of the Li+ ion in acetonitrile compared to that in water and methanol which has been attributed to the transport of the Li-Cl ion pair in a non-dissociated form in acetonitrile. The AIMD results were found to be in accordance with the experimental findings, i.e. the limiting ion conductivity was found to follow the order acetonitrile > methanol > water. This study shows the importance of atomistic level simulations in evaluating the structural and dynamical parameters and in implementing the results for predicting and synthesizing better next generation solvents for lithium ion batteries (LIBs).

Simulating the isotropic Raman spectra of O-H stretching mode in liquid H2O based on a machine learning potential: the influence of vibrational couplings

In this study, we trained a deep potential (DP) for H2O, an accurate machine learning (ML) potential. We performed molecular dynamics (MD) simulations of liquid water using the DP model (or DeePMD simulations). Our results showed that the DP model exhibits DFT-level accuracy, and the DeePMD simulation is a promising approach for modeling the structural properties of liquid water. Based on the DeePMD simulation trajectories, we calculated the isotropic Raman spectra of the O-H stretching mode using the surface-specific velocity-velocity correlation function (ssVVCF), showing that the DeePMD/ssVVCF approach can correctly capture the bimodal characteristics of the experimental Raman spectra, with one peak located near 3400 cm-1 and the other near 3250 cm-1. The success of the DeePMD/ssVVCF approach should be credited to (1) the DFT-level accuracy of the DP model for H2O, (2) the ssVVCF formulation considering the coupling between vibrational modes, and (3) non-Condon effects. Furthermore, the DeePMD simulations revealed that the anharmonic interactions between the coupled water molecules in the first and second hydration shells should play an essential role in the strong mixing of the H-O-H bending mode and the O-H stretching mode, leading to the delocalization of the O-H stretching band. In particular, increasing the strength of hydrogen bonds would enhance the bend-stretch coupling, leading to the red-shifting of the O-H vibrational spectra and the increase in the intensity of the shoulder around 3250 cm-1.

On the Rich Chemistry of Pseudo-Protic Ionic Liquid Electrolytes

Mixing weak acids and bases can produce highly complicated binary mixtures, called pseudo-protic ionic liquids, in which a complex network of effects determines the physicochemical properties that are currently impossible to predict. In this joint computational-experimental study, we investigated 1-methylimidazole-acetic acid mixtures through the whole concentration range. Effects of the varying ionization and excess of either components on the properties, such as density, diffusion coefficients, and overall hydrogen bonding structure were uncovered. A special emphasis was put on understanding the multiple factors that govern the conductivity of the system. In the presence of an excess of acetic acid, the 1-methylimidazolium acetate ion pairs dissociate more efficiently, resulting in a higher concentration of independently moving, conducting ions. However, the conductivity measurements showed that higher concentrations of acetic acid improve the conductivity beyond this effect, suggesting in addition to standard dilution effects the occurrence of Grotthuss diffusion in high acid-to-base ratios. The results here will potentially help designing novel electrolytes and proton conducting systems, which can be exploited in a variety of applications.

Effects of intermetal distance on the electrochemistry-induced surface coverage of M-N-C dual-atom catalysts

The often-overlooked electrocatalytic bridge-site poisoning of the emerging dual-atom catalysts (DACs) has aroused broad concerns very recently. Herein, based on surface Pourbaix analysis, we identified a significant change in the electrochemistry-induced surface coverages of DACs upon changing the intermetal distance. We found a pronounced effect of the intermetal distance on the electrochemical potential window and the type of pre-covered adsorbate, suggesting an interesting avenue to tune the electrocatalytic function of DACs.

Nature and coordination geometry of geologically relevant aqueous Uranium(VI) complexes up to 400 ºC: A review and new data

The structure of the uranyl aqua ion (UO₂²⁺) and a number of its inorganic complexes (specifically, UO₂Cl⁺, UO₂Cl₂⁰, UO₂SO₄⁰, [Formula: see text] , [Formula: see text] and UO₂OH₄^2-) have been characterised using X-Ray absorption spectroscopy/extended X-Ray absorption fine structure (XAS/EXAFS) at temperatures ranging from 25 to 326 ºC. Results of ab initio molecular dynamics (MD) calculations are also reported for uranyl in chloride and sulfate-bearing fluids from 25 to 400 ºC and 600 bar to 20 kilobar (kb). These results are reported alongside a comprehensive review of prior structural characterisation work with particular focus given to EXAFS works to provide a consistent and up-to-date view of the structure of these complexes under conditions relevant to U mobility in ore-forming systems and around high-grade nuclear waste repositories. Regarding reported EXAFS results, average equatorial coordination was found to decrease in uranyl and its sulfate and chloride complexes as temperature rose - the extent of this decrease differed between species and solution compositions but typically resulted in an equatorial coordination number of ∼3-4 at temperatures above 200 ºC. The [Formula: see text] complex was observed at temperatures from 25 to 247 ºC and exhibited no major structural changes over this temperature range. UO₂OH₄^2- exhibited only minor structural changes over a temperature range from 88 to 326 ºC and was suggested to manifest fivefold coordination with four hydroxyl molecules and one water molecule around its equator. Average coordination values derived from fits of the reported EXAFS data were compared to average coordination values calculated using the experimentally derived thermodynamic data for chloride complexes reported by Dargent et al. (2013) and Migdisov et al. (2018b), and for sulfate complexes reported by Alcorn et al. (2019) and Kalintsev et al. (2019). Sulfate EXAFS data were well described by available thermodynamic data, and chloride EXAFS data were described well by the thermodynamic data of Migdisov et al. (2018b), but not by the data of Dargent et al. (2013). The ab initio molecular dynamics calculations confirmed the trends in equatorial coordination observed with EXAFS and were also able to provide an insight into the effect of pressure in equatorial water coordination - for a given temperature, higher pressures appear to lead to a greater number of equatorially bound waters counteracting the temperature effect.

Machine Learning Electron Density Prediction Using Weighted Smooth Overlap of Atomic Positions

Having access to accurate electron densities in chemical systems, especially for dynamical systems involving chemical reactions, ion transport, and other charge transfer processes, is crucial for numerous applications in materials chemistry. Traditional methods for computationally predicting electron density data for such systems include quantum mechanical (QM) techniques, such as density functional theory. However, poor scaling of these QM methods restricts their use to relatively small system sizes and short dynamic time scales. To overcome this limitation, we have developed a deep neural network machine learning formalism, which we call deep charge density prediction (DeepCDP), for predicting charge densities by only using atomic positions for molecules and condensed phase (periodic) systems. Our method uses the weighted smooth overlap of atomic positions to fingerprint environments on a grid-point basis and map it to electron density data generated from QM simulations. We trained models for bulk systems of copper, LiF, and silicon; for a molecular system, water; and for two-dimensional charged and uncharged systems, hydroxyl-functionalized graphane, with and without an added proton. We showed that DeepCDP achieves prediction R2 values greater than 0.99 and mean squared error values on the order of 10-5e2 Å-6 for most systems. DeepCDP scales linearly with system size, is highly parallelizable, and is capable of accurately predicting the excess charge in protonated hydroxyl-functionalized graphane. We demonstrate how DeepCDP can be used to accurately track the location of charges (protons) by computing electron densities at a few selected grid points in the materials, thus significantly reducing the computational cost. We also show that our models can be transferable, allowing prediction of electron densities for systems on which it has not been trained but that contain a subset of atomic species on which it has been trained. Our approach can be used to develop models that span different chemical systems and train them for the study of large-scale charge transport and chemical reactions.

Common Cations Are Not Polarizable: Effects of Dispersion Correction on Hydration Structures from Ab Initio Molecular Dynamics

We employed density functional theory-based ab initio molecular dynamics simulations to examine the hydration structure of several common alkali and alkali earth metal cations. We found that the commonly used atom pairwise dispersion correction scheme D3, which assigns dispersion coefficients based on the neutral form of the atom rather than its actual oxidation state, leads to inaccuracies in the hydration structures of these cations. We evaluated this effect for lithium, sodium, potassium, and calcium and found that the inaccuracies are particularly pronounced for sodium and potassium compared to the experiment. To remedy this issue, we propose disabling the D3 correction specifically for all cation-including pairs, which leads to a much better agreement with experimental data.

Molecular Dynamics and Structural Studies of Zinc Chloroquine Complexes

Chloroquine (CQ) is a first-choice drug against malaria and autoimmune diseases. It has been co-administered with zinc against SARS-CoV-2 and soon dismissed because of safety issues. The structural features of Zn-CQ complexes and the effect of CQ on zinc distribution in cells are poorly known. In this study, state-of-the-art computations combined with experiments were leveraged to solve the structural determinants of zinc-CQ interactions in solution and the solid state. NMR, ESI-MS, and X-ray absorption and diffraction methods were combined with ab initio molecular dynamics calculations to address the kinetic lability of this complex. Within the physiological pH range, CQ binds Zn²⁺ through the quinoline ring nitrogen, forming [Zn(CQH)Cl_x(H₂O)_3-x]^(3+)-x (x = 0, 1, 2, and 3) tetrahedral complexes. The Zn(CQH)Cl₃ species is stable at neutral pH and at high chloride concentrations typical of the extracellular medium, but metal coordination is lost at a moderately low pH as in the lysosomal lumen. The pentacoordinate complex [Zn(CQH)(H₂O)₄]³⁺ may exist in the absence of chloride. This in vitro/in silico approach can be extended to other metal-targeting drugs and bioinorganic systems.

Water Defect Stabilizes the Bi3+ Lone-Pair Electronic State Leading to an Unusual Aqueous Hydration Structure

The aqueous hydration structure of the Bi³⁺ ion is probed using a combination of extended X-ray absorption fine structure (EXAFS) spectroscopy and density functional theory (DFT) simulations of ion-water clusters and condensed-phase solutions. Anomalous features in the EXAFS spectra are found to be associated with a highly asymmetric first-solvent water shell. The aqueous chemistry and structure of the Bi³⁺ ion are dramatically controlled by the water stabilization of a lone-pair electronic state involving the mixed 6s and 6p orbitals. This leads to a distinct multimodal distribution of water molecules in the first shell that are separated by about 0.2 Å. The lone-pair structure is stabilized by a collective response of multiple waters that are localized near the lone-pair anti-bonding site. The findings indicate that the lone-pair stereochemistry of aqueous Bi³⁺ ions plays a major role in the binding of water and ligands in aqueous solutions.

Understanding the Underlying Field Evaporation Mechanism of Pure Water Tips in High Electrical Fields

We investigated the field evaporation process of frozen water in atom probe tomography (APT) by density functional simulations. In previous experiments, a strong tailing effect was observed for peaks caused by the molecular structure (H₂O)_nH⁺, in contrast to other peaks. In purely field-induced and thermally assisted evaporation simulations, we found that chains of protonated water molecules were pulled out of the dielectric surface by up to 6 Å, which are stable over a wide range of field strengths. Therefore, the resulting water clusters experience only part of the acceleration after evaporation compared to molecules evaporating directly from the surface and, thus, exhibit an energy deficit, which explains the tailing effect. Our simulations provide new insight into the complex evaporation behavior of water in high electrical fields and reveal possibilities for adapting the existing reconstruction algorithms.

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.

Simulating the solvation structure of low- and high-spin [Fe(bpy)3]2+: long-range dispersion and many-body effects

When characterizing transition metal complexes and their functionalities, the importance of including the solvent as an active participant is becoming more and more apparent. Whereas many studies have evaluated long-range dispersion effects inside organic molecules and organometallics, less is known about their role in solvation. Here, we have analysed the components within solute-solvent and solvent-solvent interactions of one of the most studied iron-based photoswitch model systems, in two spin states. We find that long-range dispersion effects modulate the coordination significantly, and that this is accurately captured by density functional theory models including dispersion corrections. We furthermore correlate gas-phase relaxed complex-water clusters to thermally averaged molecular densities. This shows how the gas-phase interactions translate to solution structure, quantified through 3D molecular densities, angular distributions, and radial distribution functions. We show that finite-size simulation cells can cause the radial distribution functions to have artificially enlarged amplitudes. Finally, we quantify the effects of many-body interactions within the solvent shells, and find that almost a fifth of the total interaction energy of the solute-shell system in the high-spin state comes from many-body contributions, which cannot be captured by by pair-wise additive force field methods.

Toward High-level Machine Learning Potential for Water Based on Quantum Fragmentation and Neural Networks

Accurate and efficient simulation of liquids, such as water and salt solutions, using high-level wave function theories is still a formidable task for computational chemists owing to the high computational costs. In this study, we develop a deep machine learning potential based on fragment-based second-order Møller-Plesset perturbation theory (DP-MP2) for water through neural networks. We show that the DP-MP2 potential predicts the structural, dynamical, and thermodynamic properties of liquid water in better agreement with the experimental data than previous studies based on density functional theory (DFT). The nuclear quantum effects (NQEs) on the properties of liquid water are also examined, which are noticeable in affecting the structural and dynamical properties of liquid water under ambient conditions. This work provides a general framework for quantitative predictions of the properties of condensed-phase systems with the accuracy of high-level wave function theory while achieving significant computational savings compared to ab initio simulations.

Assessing the Interplay between Functional-Driven and Density-Driven Errors in DFT Models of Water

We investigate the interplay between functional-driven and density-driven errors in different density functional approximations within density functional theory (DFT) and the implications of these errors for simulations of water with DFT-based data-driven potentials. Specifically, we quantify density-driven errors in two widely used dispersion-corrected functionals derived within the generalized gradient approximation (GGA), namely BLYP-D3 and revPBE-D3, and two modern meta-GGA functionals, namely strongly constrained and appropriately normed (SCAN) and B97M-rV. The effects of functional-driven and density-driven errors on the interaction energies are first assessed for the water clusters of the BEGDB dataset. Further insights into the nature of functional-driven errors are gained from applying the absolutely localized molecular orbital energy decomposition analysis (ALMO-EDA) to the interaction energies, which demonstrates that functional-driven errors are strongly correlated with the nature of the interactions. We discuss cases where density-corrected DFT (DC-DFT) models display higher accuracy than the original DFT models and cases where reducing the density-driven errors leads to larger deviations from the reference energies due to the presence of large functional-driven errors. Finally, molecular dynamics simulations are performed with data-driven many-body potentials derived from DFT and DC-DFT data to determine the effect that minimizing density-driven errors has on the description of liquid water. Besides rationalizing the performance of widely used DFT models of water, we believe that our findings unveil fundamental relations between the shortcomings of some common DFT approximations and the requirements for accurate descriptions of molecular interactions, which will aid the development of a consistent, DFT-based framework for the development of data-driven and machine-learned potentials for simulations of condensed-phase systems.

Density Functional Theory of Water with the Machine-Learned DM21 Functional

The delicate interplay between functional-driven and density-driven errors in density functional theory (DFT) has hindered traditional density functional approximations (DFAs) from providing an accurate description of water for over 30 years. Recently, the deep-learned DeepMind 21 (DM21) functional has been shown to overcome the limitations of traditional DFAs as it is free of delocalization error. To determine if DM21 can enable a molecular-level description of the physical properties of aqueous systems within Kohn-Sham DFT, we assess the accuracy of the DM21 functional for neutral, protonated, and deprotonated water clusters. We find that the ability of DM21 to accurately predict the energetics of aqueous clusters varies significantly with cluster size. Additionally, we introduce the many-body MB-DM21 potential derived from DM21 data within the many-body expansion of the energy and use it in simulations of liquid water as a function of temperature at ambient pressure. We find that size-dependent functional-driven errors identified in the analysis of the energetics of small clusters calculated with the DM21 functional result in the MB-DM21 potential systematically overestimating the hydrogen-bond strength and, consequently, predicting a more ice-like local structure of water at room temperature.

Electrocatalysis in Alkaline Media and Alkaline Membrane-Based Energy Technologies

Hydrogen energy-based electrochemical energy conversion technologies offer the promise of enabling a transition of the global energy landscape from fossil fuels to renewable energy. Here, we present a comprehensive review of the fundamentals of electrocatalysis in alkaline media and applications in alkaline-based energy technologies, particularly alkaline fuel cells and water electrolyzers. Anion exchange (alkaline) membrane fuel cells (AEMFCs) enable the use of nonprecious electrocatalysts for the sluggish oxygen reduction reaction (ORR), relative to proton exchange membrane fuel cells (PEMFCs), which require Pt-based electrocatalysts. However, the hydrogen oxidation reaction (HOR) kinetics is significantly slower in alkaline media than in acidic media. Understanding these phenomena requires applying theoretical and experimental methods to unravel molecular-level thermodynamics and kinetics of hydrogen and oxygen electrocatalysis and, particularly, the proton-coupled electron transfer (PCET) process that takes place in a proton-deficient alkaline media. Extensive electrochemical and spectroscopic studies, on single-crystal Pt and metal oxides, have contributed to the development of activity descriptors, as well as the identification of the nature of active sites, and the rate-determining steps of the HOR and ORR. Among these, the structure and reactivity of interfacial water serve as key potential and pH-dependent kinetic factors that are helping elucidate the origins of the HOR and ORR activity differences in acids and bases. Additionally, deliberately modulating and controlling catalyst-support interactions have provided valuable insights for enhancing catalyst accessibility and durability during operation. The design and synthesis of highly conductive and durable alkaline membranes/ionomers have enabled AEMFCs to reach initial performance metrics equal to or higher than those of PEMFCs. We emphasize the importance of using membrane electrode assemblies (MEAs) to integrate the often separately pursued/optimized electrocatalyst/support and membranes/ionomer components. Operando/in situ methods, at multiscales, and ab initio simulations provide a mechanistic understanding of electron, ion, and mass transport at catalyst/ionomer/membrane interfaces and the necessary guidance to achieve fuel cell operation in air over thousands of hours. We hope that this Review will serve as a roadmap for advancing the scientific understanding of the fundamental factors governing electrochemical energy conversion in alkaline media with the ultimate goal of achieving ultralow Pt or precious-metal-free high-performance and durable alkaline fuel cells and related technologies.

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.

Insights into lithium manganese oxide-water interfaces using machine learning potentials

Unraveling the atomistic and the electronic structure of solid-liquid interfaces is the key to the design of new materials for many important applications, from heterogeneous catalysis to battery technology. Density functional theory (DFT) calculations can, in principle, provide a reliable description of such interfaces, but the high computational costs severely restrict the accessible time and length scales. Here, we report machine learning-driven simulations of various interfaces between water and lithium manganese oxide (Li_xMn₂O₄), an important electrode material in lithium ion batteries and a catalyst for the oxygen evolution reaction. We employ a high-dimensional neural network potential to compute the energies and forces several orders of magnitude faster than DFT without loss in accuracy. In addition, a high-dimensional neural network for spin prediction is utilized to analyze the electronic structure of the manganese ions. Combining these methods, a series of interfaces is investigated by large-scale molecular dynamics. The simulations allow us to gain insights into a variety of properties, such as the dissociation of water molecules, proton transfer processes, and hydrogen bonds, as well as the geometric and electronic structure of the solid surfaces, including the manganese oxidation state distribution, Jahn-Teller distortions, and electron hopping.

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.

Molecular dissociation and proton transfer in aqueous methane solution under an electric field

Methane-water mixtures are ubiquitous in our solar system and they have been the subject of a wide variety of experimental, theoretical, and computational studies aimed at understanding their behaviour under disparate thermodynamic scenarios, up to extreme planetary ice conditions of pressures and temperatures [Lee and Scandolo, Nat. Commun., 2011, 2, 185]. Although it is well known that electric fields, by interacting with condensed matter, can produce a range of catalytic effects which can be similar to those observed when material systems are pressurised, to the best of our knowledge, no quantum-based computational investigations of methane-water mixtures under an electric field have been reported so far. Here we present a study relying upon state-of-the-art ab initio molecular dynamics simulations where a liquid aqueous methane solution is exposed to strong oriented static and homogeneous electric fields. It turns out that a series of field-induced effects on the dipoles, polarisation, and the electronic structure of both methane and water molecules are recorded. Moreover, upon increasing the field strength, increasing fractions of water molecules are not only re-oriented towards the field direction, but are also dissociated by the field, leading to the release of oxonium and hydroxyde ions in the mixture. However, in contrast to what is observed upon pressurisation (∼50 GPa), where the presence of the water counterions triggers methane ionisation and other reactions, methane molecules preserve their integrity up to the strongest field explored (i.e., 0.50 V Å^-1). Interestingly, neither the field-induced molecular dissociation of neat water (i.e., 0.30 V Å^-1) nor the proton conductivity typical of pure aqueous samples at these field regimes (i.e., 1.3 S cm^-1) are affected by the presence of hydrophobic interactions, at least in a methane-water mixture containing a molar fraction of 40% methane.

Solvation of anthraquinone and TEMPO redox-active species in acetonitrile using a polarizable force field

Redox-active molecules are of interest in many fields, such as medicine, catalysis, or energy storage. In particular, in supercapacitor applications, they can be grafted to ionic liquids to form so-called biredox ionic liquids. To completely understand the structural and transport properties of such systems, an insight at the molecular scale is often required, but few force fields are developed ad hoc for these molecules. Moreover, they do not include polarization effects, which can lead to inaccurate solvation and dynamical properties. In this work, we developed polarizable force fields for redox-active species anthraquinone (AQ) and 2,2,6,6-tetra-methylpiperidinyl-1-oxyl (TEMPO) in their oxidized and reduced states as well as for acetonitrile. We validate the structural properties of AQ, AQ^•-, AQ^2-, TEMPO^•, and TEMPO⁺ in acetonitrile against density functional theory-based molecular dynamics simulations and we study the solvation of these redox molecules in acetonitrile. This work is a first step toward the characterization of the role played by AQ and TEMPO in electrochemical and catalytic devices.

Computational Prediction of All Lanthanide Aqua Ion Acidity Constants

The protonation state of lanthanide-ligand complexes, or lanthanide-containing porous materials, with many Brønsted acid sites can change due to proton loss/gain reactions with water or other heteroatom-containing compounds. Consequently, variations in the protonation state of lanthanide-containing species affect their molecular structure and desired properties. Lanthanide(III) aqua ions undergo hydrolysis and form hydroxides; they are the best characterized lanthanide-containing species with multiple Brønsted acid sites. We employed constrained ab initio molecular dynamics simulations and electronic structure calculations to determine all acidity constants of the lanthanide(III) aqua ions solely from computation. The first, second, and third acidity constants of lanthanide(III) aqua ions were predicted, on average, within 1.2, 2.5, and 4.7 absolute pK_a units from experiment, respectively. A table includes our predicted pK_a values alongside most experimentally measured pK_a values known to date. The approach presented is particularly suitable to determine the Brønsted acidity of lanthanide-containing systems with multiple acidic sites, including those whose measured acidity constants cannot be linked to specific acid sites.

Nuclear Quantum Effect and Its Temperature Dependence in Liquid Water from Random Phase Approximation via Artificial Neural Network

We report structural and dynamical properties of liquid water described by the random phase approximation (RPA) correlation together with the exact exchange energy (EXX) within density functional theory. By utilizing thermostated ring polymer molecular dynamics, we examine the nuclear quantum effects and their temperature dependence. We circumvent the computational limitation of performing direct first-principles molecular dynamics simulation at this high level of electronic structure theory by adapting an artificial neural network model. We show that the EXX+RPA level of theory accurately describes liquid water in terms of both dynamical and structural properties.

Electric Field and Temperature Effects on the Ab Initio Spectroscopy of Liquid Methanol

Although many H-bonded systems have been extensively investigated by means of infrared (IR) spectroscopy, the vibrational response to externally applied electric fields of polar liquids remains poorly investigated. However, local electric fields along with quantum-mechanical interactions rule the behavior of H-bonded samples at the molecular level. Among the many H-bonded systems, liquid methanol holds a key place in that it exhibits a very simple H-bond network where, on average, each molecule acts as a single H-bond donor and, at the same time, as a single H-bond acceptor. Here we report on the IR spectra emerging from a series of state-of-the-art ab initio molecular dynamics simulations of bulk liquid methanol under the action of static and homogeneous electric fields. In addition, the same analysis is here conducted in the absence of the external field and for different temperatures. Although some electric-field-induced effects resemble the response of other polar liquids (such as the global contraction of the IR spectrum upon field exposure), it turns out that, distinctly from water, the “electrofreezing” phenomenon is unlikely to happen in liquid methanol. Finally, we provide atomistic analyses magnifying the completely different nature of electric-field- and temperature-induced effects on bulk liquid methanol and on its vibrational response.

First-Principles Simulations of CuCl in High-Temperature Water Vapor

Experimental data suggest that the solubility of copper in high-temperature water vapor is controlled by the formation of hydrated clusters of the form CuCl(H₂O)_n, where the average number of water molecules in the cluster generally increases with increasing density [Migdisov, A. A.; et al. Geochim. Cosmochim. Acta 2014, 129, 33-53]. However, the precise nature of these clusters is difficult to probe experimentally. Moreover, there are some discrepancies between experimental estimates of average cluster size and prior simulation work [Mei, Y. Geofluids 2018, 2018, 4279124]. We have performed first-principles Monte Carlo (MC) and molecular dynamics (MD) simulations to explore these clusters in finer detail. We find that molecular dynamics is not the most appropriate technique for studying aggregation in vapor phases, even at relatively high temperatures. Specifically, our MD simulations exhibit substantial problems in adequately sampling the equilibrium cluster size distribution. In contrast, MC simulations with specialized cluster moves are able to accurately sample the phase space of hydrogen-bonding vapors. At all densities, we find a stable, slightly distorted linear H₂O-Cu-Cl structure, which is in agreement with the earlier simulations, surrounded by a variable number of water molecules. The surrounding water molecules do not form a well-defined second solvation shell but rather a loose network of hydrogen-bonded water with molecular CuCl on the outside edge of the water cluster. We also find a broad distribution of hydration numbers, especially at higher densities. In contrast to previous simulation work but in agreement with experimental data, we find that the average hydration number substantially increases with increasing density. Moreover, the value of the hydration number depends on the choice of cluster definition.

OH- and H3O+ Diffusion in Model AEMs and PEMs at Low Hydration: Insights from Ab Initio Molecular Dynamics

Fuel cell-based anion-exchange membranes (AEMs) and proton exchange membranes (PEMs) are considered to have great potential as cost-effective, clean energy conversion devices. However, a fundamental atomistic understanding of the hydroxide and hydronium diffusion mechanisms in the AEM and PEM environment is an ongoing challenge. In this work, we aim to identify the fundamental atomistic steps governing hydroxide and hydronium transport phenomena. The motivation of this work lies in the fact that elucidating the key design differences between the hydroxide and hydronium diffusion mechanisms will play an important role in the discovery and determination of key design principles for the synthesis of new membrane materials with high ion conductivity for use in emerging fuel cell technologies. To this end, ab initio molecular dynamics simulations are presented to explore hydroxide and hydronium ion solvation complexes and diffusion mechanisms in the model AEM and PEM systems at low hydration in confined environments. We find that hydroxide diffusion in AEMs is mostly vehicular, while hydronium diffusion in model PEMs is structural. Furthermore, we find that the region between each pair of cations in AEMs creates a bottleneck for hydroxide diffusion, leading to a suppression of diffusivity, while the anions in PEMs become active participants in the hydronium diffusion, suggesting that the presence of the anions in model PEMs could potentially promote hydronium diffusion.

Phase Equilibrium of Water with Hexagonal and Cubic Ice Using the SCAN Functional

Machine learning models are rapidly becoming widely used to simulate complex physicochemical phenomena with ab initio accuracy. Here, we use one such model as well as direct density functional theory (DFT) calculations to investigate the phase equilibrium of water, hexagonal ice (Ih), and cubic ice (Ic), with an eye toward studying ice nucleation. The machine learning model is based on deep neural networks and has been trained on DFT data obtained using the SCAN exchange and correlation functional. We use this model to drive enhanced sampling simulations aimed at calculating a number of complex properties that are out of reach of DFT-driven simulations and then employ an appropriate reweighting procedure to compute the corresponding properties for the SCAN functional. This approach allows us to calculate the melting temperature of both ice polymorphs, the driving force for nucleation, the heat of fusion, the densities at the melting temperature, the relative stability of ices Ih and Ic, and other properties. We find a correct qualitative prediction of all properties of interest. In some cases, quantitative agreement with experiment is better than for state-of-the-art semiempirical potentials for water. Our results also show that SCAN correctly predicts that ice Ih is more stable than ice Ic.

Intrinsically Polar Piezoelectric Self-Assembled Oligopeptide Monolayers

Flexible, biocompatible piezoelectric materials are of considerable research interest for a variety of applications, but many suffer from low response or high cost to manufacture. Herein, novel piezoelectric force and touch sensors based on self-assembled monolayers of oligopeptides are presented, which produce large piezoelectric voltage response and are easily manufactured without the need for electrical poling. While the devices generate modest piezoelectric charge constants (d33 ) of up to 9.8 pC N-1 , they exhibit immense piezoelectric voltage constants (g33 ) up to 2 V m N-1 . Furthermore, a flexible device prototype is demonstrated that produces open-circuit voltages of nearly 6 V under gentle bending motion. Improvements in peptide selection and device construction promise to further improve the already outstanding voltage response and open the door to numerous practical applications.

Predicting lanthanide coordination structures in solution with molecular simulation

The chemical and physical properties of lanthanide coordination complexes can significantly change with small variations in their molecular structure. Further, in solution, coordination structures (e.g., lanthanide-ligand complexes) are dynamic. Resolving solution structures, computationally or experimentally, is challenging because structures in solution have limited spatial restrictions and are responsive to chemical or physical changes in their surroundings. To determine structures of lanthanide-ligand complexes in solution, a molecular simulation approach is presented in this chapter, which concurrently considers chemical reactions and molecular dynamics. Lanthanide ion, ligand, solvent, and anion molecules are explicitly included to identify, in atomic resolution, lanthanide coordination structures in solution. The computational protocol described is applicable to determining the molecular structure of lanthanide-ligand complexes, particularly with ligands known to bind lanthanides but whose structures have not been resolved, as well as with ligands not previously known to bind lanthanide ions. The approach in this chapter is also relevant to elucidating lanthanide coordination in more intricate structures, such as in the active site of enzymes.

Supercooled liquid-like dynamics in water near a fully hydrated titania surface: Decoupling of rotational and translational diffusion

We report an ab initio molecular dynamics (MD) simulation investigating the effect of a fully hydrated surface of TiO₂ on the water dynamics. It is found that the universal relation between the rotational and translational diffusion characteristics of bulk water is broken in the water layers near the surface with the rotational diffusion demonstrating progressive retardation relative to the translational diffusion when approaching the surface. This kind of rotation-translation decoupling has so far only been observed in the supercooled liquids approaching glass transition, and its observation in water at a normal liquid temperature is of conceptual interest. This finding is also of interest for the application-significant studies of the water interaction with fully hydrated nanoparticles. We note that this is the first observation of rotation-translation decoupling in an ab initio MD simulation of water.

Coordination Sphere of Lanthanide Aqua Ions Resolved with Ab Initio Molecular Dynamics and X-ray Absorption Spectroscopy

To resolve the fleeting structures of lanthanide Ln3+ aqua ions in solution, we (i) performed the first ab initio molecular dynamics (AIMD) simulations of the entire series of Ln3+ aqua ions in explicit water solvent using pseudopotentials and basis sets recently optimized for lanthanides and (ii) measured the symmetry of the hydrating waters about Ln3+ ions (Nd3+, Dy3+, Er3+, Lu3+) for the first time with extended X-ray absorption fine structure (EXAFS). EXAFS spectra were measured experimentally and generated from AIMD trajectories to directly compare simulation, which concurrently considers the electronic structure and the atomic dynamics in solution, with experiment. We performed a comprehensive evaluation of EXAFS multiple-scattering analysis (up to 6.5 Å) to measure Ln-O distances and angular correlations (i.e., symmetry) and elucidate the molecular geometry of the first hydration shell. This evaluation, in combination with symmetry-dependent L3- and L1-edge spectral analysis, shows that the AIMD simulations remarkably reproduces the experimental EXAFS data. The error in the predicted Ln-O distances is less than 0.07 Å for the later lanthanides, while we observed excellent agreement with predicted distances within experimental uncertainty for the early lanthanides. Our analysis revealed a dynamic, symmetrically disordered first coordination shell, which does not conform to a single molecular geometry for most lanthanides. This work sheds critical light on the highly elusive coordination geometry of the Ln3+ aqua ions.

Determining Partial Atomic Charges for Liquid Water: Assessing Electronic Structure and Charge Models

Partial atomic charges provide an intuitive and efficient way to describe the charge distribution and the resulting intermolecular electrostatic interactions in liquid water. Many charge models exist and it is unclear which model provides the best assignment of partial atomic charges in response to the local molecular environment. In this work, we systematically scrutinize various electronic structure methods and charge models (Mulliken, natural population analysis, CHelpG, RESP, Hirshfeld, Iterative Hirshfeld, and Bader) by evaluating their performance in predicting the dipole moments of isolated water, water clusters, and liquid water as well as charge transfer in the water dimer and liquid water. Although none of the seven charge models is capable of fully capturing the dipole moment increase from isolated water (1.85 D) to liquid water (about 2.9 D), the Iterative Hirshfeld method performs best for liquid water, reproducing its experimental average molecular dipole moment, yielding a reasonable amount of intermolecular charge transfer, and showing modest sensitivity to the local water environment. The performance of the charge model is dependent on the choice of the density functional and the quantum treatment of the environment. The computed molecular dipole moment of water generally increases with the percentage of the exact Hartree-Fock exchange in the functional, whereas the amount of charge transfer between molecules decreases. For liquid water, including two full solvation shells of surrounding water molecules (within about 5.5 Å of the central water) in the quantum chemical calculation converges the charges of the central water molecule. Our final pragmatic quantum chemical charge-assigning protocol for liquid water is the Iterative Hirshfeld method with M06-HF/aug-cc-pVDZ and a quantum region cutoff radius of 5.5 Å.

Solution structure of a europium–nicotianamine complex supports that phytosiderophores bind lanthanides

The structures of europium–EDTA (known lanthanide chelator) and europium–nicotianamine (biochemical precursor of phytosiderophores) complexes are resolved, in solution, with ab initio molecular dynamics as well as excitation and emission spectroscopy.

Unravelling phosphate adsorption on hydrous ferric oxide surfaces at the molecular level

The thorough understanding of the adsorption mechanism of phosphate on hydrous ferric oxides is necessary to deal with the environmental issues related to high phosphate concentrations in soils and open water. In this work, we consider three different adsorption geometries (monodentate and bidentate chemisorption and physisorption) and calculate the adsorption geometries and related adsorption energies at optPBE-vdW level. Using the Maxwell-Boltzmann distribution, it is estimated that about 83% of the phosphate molecules is in a monodentate chemisorption configuration, while 17% is physisorbed. Furthermore, theoretical infra-red spectra are obtained and compared to equivalent experimental spectra, supporting the conclusion that mainly monodentate chemisorption and physisorption occur. Most interestingly, a weighed infra-red spectrum is then calculated, using the weights from the Maxwell-Boltzmann distribution, showing a very good comparison with the experimental spectra.