First-Principles Calculation of Water pKa Using the Newly Developed SCAN Functional

Learning a reactive potential for silica-water through uncertainty attribution

The reactivity of silicates in aqueous solution is relevant to various chemistries ranging from silicate minerals in geology, to the C-S-H phase in cement, nanoporous zeolite catalysts, or highly porous precipitated silica. While simulations of chemical reactions can provide insight at the molecular level, balancing accuracy and scale in reactive simulations in the condensed phase is a challenge. Here, we demonstrate how a machine-learning reactive interatomic potential trained on PaiNN architecture can accurately capture silicate-water reactivity. The model was trained on a dataset comprising 400,000 energies and forces of molecular clusters at the ωB97X-D3/def2-TZVP level. To ensure the robustness of the model, we introduce a general active learning strategy based on the attribution of the model uncertainty, that automatically isolates uncertain regions of bulk simulations to be calculated as small-sized clusters. The potential reproduces static and dynamic properties of liquid water and solid crystalline silicates, despite having been trained exclusively on cluster data. Furthermore, we utilize enhanced sampling simulations to recover the self-ionization reactivity of water accurately, and the acidity of silicate oligomers, and lastly study the silicate dimerization reaction in a water solution at neutral conditions and find that the reaction occurs through a flanking mechanism.

The Determination of Free Energy of Hydration of Water Ions from First Principles

We model the autoionization of water by determining the free energy of hydration of the major intermediate species of water ions. We represent the smallest ions─the hydroxide ion OH-, the hydronium ion H3O+, and the Zundel ion H5O2+─by bonded models and the more extended ionic structures by strong nonbonded interactions (e.g., the Eigen H9O4+ = H3O+ + 3(H2O) and the Stoyanov H13O6+ = H5O2+ + 4(H2O)). Our models are faithful to the precise QM energies and their components to within 1% or less. Using the calculated free energies and atomization energies, we compute the pKa of pure water from first principles as a consistency check and arrive at a value within 1.3 log units of the experimental one. From these calculations, we conclude that the hydronium ion, and its hydrated state, the Eigen cation, are the dominant species in the water autoionization process.

Probing the self-ionization of liquid water with ab initio deep potential molecular dynamics

The chemical equilibrium between self-ionized and molecular water dictates the acid-base chemistry in aqueous solutions, yet understanding the microscopic mechanisms of water self-ionization remains experimentally and computationally challenging. Herein, Density Functional Theory (DFT)-based deep neural network (DNN) potentials are combined with enhanced sampling techniques and a global acid-base collective variable to perform extensive atomistic simulations of water self-ionization for model systems of increasing size. The explicit inclusion of long-range electrostatic interactions in the DNN potential is found to be crucial to accurately reproduce the DFT free energy profile of solvated water ion pairs in small (64 and 128 H2O) cells. The reversible work to separate the hydroxide and hydronium to a distance [Formula: see text] is found to converge for simulation cells containing more than 500 H2O, and a distance of [Formula: see text] 8 Å is the threshold beyond which the work to further separate the two ions becomes approximately zero. The slow convergence of the potential of mean force with system size is related to a restructuring of water and an increase of the local order around the water ions. Calculation of the dissociation equilibrium constant illustrates the key role of long-range electrostatics and entropic effects in the water autoionization process.

Accurate Computation of Aqueous pKas of Biologically Relevant Organic Acids: Overcoming the Challenges Posed by Multiple Conformers, Tautomeric Equilibria, and Disparate Functional Groups with the Fully Black-Box pK-Yay Method

The use of static electronic structure calculations to compute solution-phase pKas offers a great advantage in that a macroscopic bulk property could be computed via microscopic computations involving very few molecules. There are various sources of errors in the quantum chemical calculations though. Overcoming these errors to accurately compute pKas of a plethora of acids is an active area of research in physical chemistry pursued by both computational as well as experimental chemists. We recently developed the pK-Yay method in our attempt to accurately compute aqueous pKas of strong and weak acids. The method is fully black-box, computationally inexpensive, and is very easy for even a nonexpert to use. However, the method was thus far tested on very few molecules (only 16 in all). Herein, in order to assess the future applicability of pK-Yay, we study the effect of multiple conformers, the presence of tautomers under equilibrium, and the impact of a wide variety of functional groups (derivatives of acetic acid with substituents at various positions, dicarboxylic acids, aromatic carboxylic acids, amines and amides, phenols and thiols, and fluorine bearing organic acids). Starting with more than 1000 conformers and tautomers, this study establishes that overall errors of ∼ 1.0 pKa units are routinely obtained for a majority of the molecules. Larger errors are noted in cases where multiple charges, intramolecular hydrogen bonding, and several ionizable functional groups are simultaneously present. An important conclusion to emerge from this work is that, the computed pKas are insensitive (difference <0.5) to whether we consider multiple conformers/tautomers or only choose the most stable conformer/tautomer. Further, pK-Yay captures the stereoelectronic effects arising due to differing axial vs equatorial pattern, and is useful to predict the dominant acid-base equilibrium in a system featuring several equilibria. Overall, pK-Yay may be employed in several chemical applications featuring organic molecules and biomonomers.

Microscopic Mechanism of Proton Transfer in Pure Water under Ambient Conditions

Water molecules and the associated proton transfer (PT) are prevalent in chemical and biological systems and have been a hot research topic. Spectroscopic characterization and ab initio molecular dynamics (AIMD) simulations have previously revealed insights into acidic and basic liquids. Presumably, the situation in the acidic/basic solution is not necessarily the same as in pure water; in addition, the autoionization constant for water is only 10^-14 under ambient conditions, making the study of PT in pure water challenging. To overcome this issue, we modeled periodic water box systems containing 1000 molecules for tens of nanoseconds based on a neural network potential (NNP) with quantum mechanical accuracy. The NNP was generated by training a dataset containing the energies and atomic forces of 17 075 configurations of periodic water box systems, and these data points were calculated at the MP2 level that considers electron correlation effects. We found that the size of the system and the duration of the simulation have a significant impact on the convergence of the results. With these factors considered, our simulations showed that hydronium (H₃O⁺) and hydroxide (OH^-) ions in water have distinct hydration structures, thermodynamic and kinetic properties, e.g., the longer-lasting and more stable hydrated structure of OH^- ions than that of H₃O⁺, as well as a significantly higher free energy barrier for the OH^--associated PT than that of H₃O⁺, leading the two to exhibit completely different PT behaviors. Given these characteristics, we further found that PT via OH^- ions tends not to occur multiple times or between many molecules. In contrast, PT via H₃O⁺ can synergistically occur among multiple molecules and prefers to adopt a cyclic pattern among three water molecules, while it occurs mostly in a chain pattern when more water molecules are involved. Therefore, our studies provide a detailed and solid microscopic explanation for the PT process in pure water.

Subpicosecond Molecular Rearrangements Affect Local Electric Fields and Auto-Dissociation in Water

Molecular simulations of auto-dissociation of water molecules in an 81,000 atom bulk water system show that the electric field variations caused by local bond length and angle variations enhance proton transfer within ∼600 fs prior to auto-dissociation. In this paper, auto-dissociation relates to the initial separation of a proton from a water molecule to another, forming the H33O+ and OH- ions. Only transfers for which a proton's initial nearest covalently bonded oxygen remained the same for at least 1 ps prior to the transfer and for which that proton's new nearest acceptor oxygen remained the same for at least 1 ps after the transfer were evaluated. Electric fields from solvent atoms within 6 Å of a transferring proton (H*) are dominant, with little contribution from farther molecules. However, exclusion of the accepting oxygen in such electric field calculations shows that the field on H* from the other solvent atoms weakens as the time to transfer becomes less than 600 fs, indicating the primary importance of the accepting oxygen on enabling auto-dissociation. All resultant OH- and H3O+ ion pairs recombined at times greater than 1 ps after auto-dissociation. A concentration of 8.01 × 1017 cm-3 for these ion pairs was observed. The simulations indicate that transient auto-dissociation in water is more common than that inferred from dc-conductivity experiments (10-5 vs 10-7) and is consistent with the results of calculations that include nuclear quantum effects. The conductivity experiments require the rearrangement of farther water molecules to form hydrogen-bonded "water wires" that afford long-range and measurable proton transport away from the reaction site. Nonetheless, the relatively large number of picosecond-lived auto-dissociation products might be engineered within 2D layers and oriented external fields to offer new energy-related systems.

Molecular determinants of acrylamide neurotoxicity through covalent docking

Acrylamide (ACR) is formed during food processing by Maillard reaction between sugars and proteins at high temperatures. It is also used in many industries, from water waste treatment to manufacture of paper, fabrics, dyes and cosmetics. Unfortunately, cumulative exposure to acrylamide, either from diet or at the workplace, may result in neurotoxicity. Such adverse effects arise from covalent adducts formed between acrylamide and cysteine residues of several neuronal proteins via a Michael addition reaction. The molecular determinants of acrylamide reactivity and its impact on protein function are not completely understood. Here we have compiled a list of acrylamide protein targets reported so far in the literature in connection with neurotoxicity and performed a systematic covalent docking study. Our results indicate that acrylamide binding to cysteine is favored in the presence of nearby positively charged amino acids, such as lysines and arginines. For proteins with more than one reactive Cys, docking scores were able to discriminate between the primary ACR modification site and secondary sites modified only at high ACR concentrations. Therefore, docking scores emerge as a potential filter to predict Cys reactivity against acrylamide. Inspection of the ACR-protein complex structures provides insights into the putative functional consequences of ACR modification, especially for non-enzyme proteins. Based on our study, covalent docking is a promising computational tool to predict other potential protein targets mediating acrylamide neurotoxicity.

Superhydrophilicity of α-alumina surfaces results from tight binding of interfacial waters to specific aluminols

HYPOTHESIS

Understanding the microscopic driving force of water wetting is challenging and important for design of materials. The relations between structure, dynamics and hydrogen bonds of interfacial water can be investigated using molecular dynamics simulations.

EXPERIMENTS AND SIMULATIONS

Contact angles at the alumina (0001) and (112‾0) surfaces are studied using both classical molecular dynamics simulations and experiments. To test the superhydrophilicity, the free energy cost of removing waters near the interfaces are calculated using the density fluctuations method. The strength of hydrogen bonds is determined by their lifetime and geometry.

FINDINGS

Both surfaces are superhydrophilic and the (0001) surface is more hydrophilic. Interactions between surfaces and interfacial waters promote a templating effect whereby the latter are aligned in a pattern that follows the underlying lattice of the surfaces. Translational and rotational dynamics of interfacial water molecules are slower than in bulk water. Hydrogen bonds between water and both surfaces are asymmetric, water-to-aluminol ones are stronger than aluminol-to-water ones. Molecular dynamics simulations eliminate the impacts of surface contamination when measuring contact angles and the results reveal the microscopic origin of the macroscopic superhydrophilicity of alumina surfaces: strong water-to-aluminol hydrogen bonds.

Molecular Mechanism of Autodissociation in Liquid Water: Ab Initio Molecular Dynamics Simulations

Autodissociation in liquid water is one of the most important processes in various topics of physical chemistry, such as acid-base chemistry. Molecular simulations have elucidated most of the molecular mechanisms at the atomic level, yet quantitative analysis to compare with experiments using the potential of mean force (PMF) remains a hurdle, including the definition of reaction coordinates and the accuracy of liquid structures by ab initio molecular dynamics (AIMD) simulations with density functional theory (DFT) methods. Here, we perform AIMD simulations with the revPBE-D3 exchange-correlation functional to compute the PMF profiles of autoionization, or proton transfer (PT), in liquid water. For the quantitative analysis with physically meaningful reaction coordinates, we employ a PT coordinate, donor-acceptor (OH^--H₃O⁺) distance, and hydrogen (H)-bond number. The one-dimensional (1D) PMF profile along the PT coordinate shows no local minimum in the product state of PT (OH^- and H₃O⁺), which is necessary to accurately compute the acid dissociation constant (or pK_a). On the other hand, the 2D PMF profiles along the PT coordinate and donor-acceptor distance show local minima in the product state and reaction barriers, and the computed pK_w is comparable to the experiment. In addition, the 2D PMF profiles along the PT coordinate and the H-bond number reveal the molecular mechanism of the H-bond rearrangement concomitant with PT, in which the H-bond breaking before PT is slightly preferable. These findings indicate that an accurate evaluation of pK_a by MD simulations requires the donor-acceptor distance in addition to the conventional PT coordinate.

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.

Nuclear quantum effects on autoionization of water isotopologs studied by ab initio path integral molecular dynamics

In this study, we investigate the nuclear quantum effects (NQEs) on the acidity constant (pK_A) of liquid water isotopologs under the ambient condition by path integral molecular dynamics (PIMD) simulations. We compared simulations using a fully explicit solvent model with a classical polarizable force field, density functional tight binding, and ab initio density functional theory, which correspond to empirical, semiempirical, and ab initio PIMD simulations, respectively. The centroid variable with respect to the proton coordination number of a water molecule was restrained to compute the gradient of the free energy, which measures the reversible work of the proton abstraction for the quantum mechanical system. The free energy curve obtained by thermodynamic integration was used to compute the pK_A value based on probabilistic determination. This technique not only reproduces the pK_A value of liquid D₂O experimentally measured (14.86) but also allows for a theoretical prediction of the pK_A values of liquid T₂O and aqueous HDO and HTO, which are unknown due to their scarcity. It is also shown that the NQEs on the free energy curve can result in a downshift of 4.5 ± 0.9 pK_A units in the case of liquid water, which indicates that the NQEs plays an indispensable role in the absolute determination of pK_A. The results of this study can help inform further extensions into the calculation of the acidity constants of isotope substituted species with high accuracy.

Assessment of the SCAN Functional for Spin-State Energies in Spin-Crossover Systems

The strongly constrained and appropriately normed (SCAN) functional has been tested toward the calculation of spin-state energy differences in a data set of 20 spin-crossover (SCO) systems, ranging from d⁴ to d⁷. Results show that the SCAN functional is able to correctly predict the low-spin state as the ground state for all systems, and the energy window provided by the calculations falls in the approximate range of energies that will allow for SCO to occur. Moreover, the SCAN functional can be used in periodic boundary condition calculations, accounting for the effect of collective crystal vibrations and counterions in the thermochemistry of the spin transition. Our results validate this functional as a potential method for in silico screening of new SCO systems at both, molecular and crystal-packed levels.

Self-interaction error overbinds water clusters but cancels in structural energy differences

We gauge the importance of self-interaction errors in density functional approximations (DFAs) for the case of water clusters. To this end, we used the Fermi-Löwdin orbital self-interaction correction method (FLOSIC) to calculate the binding energy of clusters of up to eight water molecules. Three representative DFAs of the local, generalized gradient, and metageneralized gradient families [i.e., local density approximation (LDA), Perdew-Burke-Ernzerhof (PBE), and strongly constrained and appropriately normed (SCAN)] were used. We find that the overbinding of the water clusters in these approximations is not a density-driven error. We show that, while removing self-interaction error does not alter the energetic ordering of the different water isomers with respect to the uncorrected DFAs, the resulting binding energies are corrected toward accurate reference values from higher-level calculations. In particular, self-interaction-corrected SCAN not only retains the correct energetic ordering for water hexamers but also reduces the mean error in the hexamer binding energies to less than 14 meV/[Formula: see text] from about 42 meV/[Formula: see text] for SCAN. By decomposing the total binding energy into many-body components, we find that large errors in the two-body interaction in SCAN are significantly reduced by self-interaction corrections. Higher-order many-body errors are small in both SCAN and self-interaction-corrected SCAN. These results indicate that orbital-by-orbital removal of self-interaction combined with a proper DFA can lead to improved descriptions of water complexes.

Molecular Structure and Modeling of Water-Air and Ice-Air Interfaces Monitored by Sum-Frequency Generation

From a glass of water to glaciers in Antarctica, water-air and ice-air interfaces are abundant on Earth. Molecular-level structure and dynamics at these interfaces are key for understanding many chemical/physical/atmospheric processes including the slipperiness of ice surfaces, the surface tension of water, and evaporation/sublimation of water. Sum-frequency generation (SFG) spectroscopy is a powerful tool to probe the molecular-level structure of these interfaces because SFG can specifically probe the topmost interfacial water molecules separately from the bulk and is sensitive to molecular conformation. Nevertheless, experimental SFG has several limitations. For example, SFG cannot provide information on the depth of the interface and how the orientation of the molecules varies with distance from the surface. By combining the SFG spectroscopy with simulation techniques, one can directly compare the experimental data with the simulated SFG spectra, allowing us to unveil the molecular-level structure of water-air and ice-air interfaces. Here, we present an overview of the different simulation protocols available for SFG spectra calculations. We systematically compare the SFG spectra computed with different approaches, revealing the advantages and disadvantages of the different methods. Furthermore, we account for the findings through combined SFG experiments and simulations and provide future challenges for SFG experiments and simulations at different aqueous interfaces.