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

Modeling separation of lanthanides via heterogeneous ligand binding

Individual lanthanide elements have physical/electronic/magnetic properties that make each useful for specific applications. Several of the lanthanides cations (Ln3+) naturally occur together in the same ores. They are notoriously difficult to separate from each other due to their chemical similarity. Predicting the Ln3+ differential binding energies (ΔΔE) or free energies (ΔΔG) at different binding sites, which are key figures of merit for separation applications, will help design of materials with lanthanide selectivity. We apply ab initio molecular dynamics (AIMD) simulations and density functional theory (DFT) to calculate ΔΔG for Ln3+ coordinated to ligands in water and embedded in metal-organic frameworks (MOFs), and ΔΔE for Ln3+ bonded to functionalized silica surfaces, thus circumventing the need for the computational costly absolute binding (free) energies ΔG and ΔE. Perturbative AIMD simulations of water-inundated simulation cells are applied to examine the selectivity of ligands towards adjacent Ln3+ in the periodic table. Static DFT calculations with a full Ln3+ first coordination shell, while less rigorous, show that all ligands examined with net negative charges are more selective towards the heavier lanthanides than a charge-neutral coordination shell made up of water molecules. Amine groups are predicted to be poor ligands for lanthanide-binding. We also address cooperative ion binding, i.e., using different ligands in concert to enhance lanthanide selectivity.

To Pair or not to Pair? Machine-Learned Explicitly-Correlated Electronic Structure for NaCl in Water

The extent of ion pairing in solution is an important phenomenon to rationalize transport and thermodynamic properties of electrolytes. A fundamental measure of this pairing is the potential of mean force (PMF) between solvated ions. The relative stabilities of the paired and solvent shared states in the PMF and the barrier between them are highly sensitive to the underlying potential energy surface. However, direct application of accurate electronic structure methods is challenging, since long simulations are required. We develop wave function based machine learning potentials with the random phase approximation (RPA) and second order Møller-Plesset (MP2) perturbation theory for the prototypical system of Na and Cl ions in water. We show both methods in agreement, predicting the paired and solvent shared states to have similar energies (within 0.2 kcal/mol). We also provide the same benchmarks for different DFT functionals as well as insight into the PMF based on simple analyses of the interactions in the system.

Hydration numbers of biologically relevant divalent metal cations from ab initio molecular dynamics and continuum solvation methods

Hydration and, in particular, the coordination number of a metal ion is of paramount importance as it defines many of its (bio)physicochemical properties. It is not only essential for understanding its behavior in aqueous solutions but also determines the metal ion reference state and its binding energy to (bio)molecules. In this paper, for divalent metal cations Ca2+, Cd2+, Cu2+, Fe2+, Hg2+, Mg2+, Ni2+, Pb2+, and Zn2+, we compare two approaches for predicting hydration numbers: (1) a mixed explicit/continuum DFT-D3//COSMO-RS solvation model and (2) density functional theory based ab initio molecular dynamics. The former approach is employed to calculate the Gibbs free energy change for the sequential hydration reactions, starting from [M(H2O)2]2+ aqua complexes to [M(H2O)9]2+, allowing explicit water molecules to bind in the first or second coordination sphere and determining the most stable [M(H2O)n]2+ structure. In the latter approach, the hydration number is obtained by integrating the ion-water radial distribution function. With a couple of exceptions, the metal ion hydration numbers predicted by the two approaches are in mutual agreement, as well as in agreement with the experimental data.

Hydration of biologically relevant tetramethylammonium cation by neutron scattering and molecular dynamics

Neutron scattering and molecular dynamics studies were performed on a concentrated aqueous tetramethylammonium (TMA) chloride solution to gain insight into the hydration shell structure of TMA, which is relevant for understanding its behavior in biological contexts of, e.g., properties of phospholipid membrane headgroups or interactions between DNA and histones. Specifically, neutron diffraction with isotopic substitution experiments were performed on TMA and water hydrogens to extract the specific correlation between hydrogens in TMA (HTMA) and hydrogens in water (HW). Classical molecular dynamics simulations were performed to help interpret the experimental neutron scattering data. Comparison of the hydration structure and simulated neutron signals obtained with various force field flavors (e.g. overall charge, charge distribution, polarity of the CH bonds and geometry) allowed us to gain insight into how sensitive the TMA hydration structure is to such changes and how much the neutron signal can capture them. We show that certain aspects of the hydration, such as the correlation of the hydrogen on TMA to hydrogen on water, showed little dependence on the force field. In contrast, other correlations, such as the ion-ion interactions, showed more marked changes. Strikingly, the neutron scattering signal cannot discriminate between different hydration patterns. Finally, ab initio molecular dynamics was used to examine the three-dimensional hydration structure and thus to benchmark force field simulations. Overall, while neutron scattering has been previously successfully used to improve force fields, in the particular case of TMA we show that it has only limited value to fully determine the hydration structure, with other techniques such as ab initio MD being of a significant help.

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.

Understanding the Anomalous Diffusion of Water in Aqueous Electrolytes Using Machine Learned Potentials

The diffusivity of water in aqueous cesium iodide solutions is larger than that in neat liquid water and vice versa for sodium chloride solutions. Such peculiar ion-specific behavior, called anomalous diffusion, is not reproduced in typical force field based molecular dynamics (MD) simulations due to inadequate treatment of ion-water interactions. Herein, this hurdle is tackled by using machine learned atomic potentials (MLPs) trained on data from density functional theory calculations. MLP based atomistic MD simulations of aqueous salt solutions reproduce experimentally determined thermodynamic, structural, dynamical, and transport properties, including their varied trends in water diffusivities across salt concentration. This enables an examination of their intermolecular structure to unravel the microscopic underpinnings of the differences in their transport properties. While both ions in CsI solutions contribute to the faster diffusion of water molecules, the competition between the heavy retardation by Na ions and the slight acceleration by Cl ions in NaCl solutions reduces their water diffusivity.

Nonaqueous Ion Pairing Exemplifies the Case for Including Electronic Polarization in Molecular Dynamics Simulations

The inclusion of electronic polarization is of crucial importance in molecular simulations of systems containing charged moieties. When neglected, as often done in force field simulations, charge-charge interactions in solution may become severely overestimated, leading to unrealistically strong bindings of ions to biomolecules. The electronic continuum correction introduces electronic polarization in a mean-field way via scaling of charges by the reciprocal of the square root of the high-frequency dielectric constant of the solvent environment. Here, we use ab initio molecular dynamics simulations to quantify the effect of electronic polarization on pairs of like-charged ions in a model nonaqueous environment where electronic polarization is the only dielectric response. Our findings confirm the conceptual validity of this approach, underlining its applicability to complex aqueous biomolecular systems. Simultaneously, the results presented here justify the potential employment of weaker charge scaling factors in force field development.