Sensitivity Analysis for ReaxFF Reparametrization Using the Hilbert-Schmidt Independence Criterion.

We apply a global sensitivity method, the Hilbert-Schmidt independence criterion (HSIC), to the reparametrization of a Zn/S/H ReaxFF force field to identify the most appropriate parameters for reparametrization. Parameter selection remains a challenge in this context, as high-dimensional optimizations are prone to overfitting and take a long time but selecting too few parameters leads to poor-quality force fields. We show that the HSIC correctly and quickly identifies the most sensitive parameters and that optimizations done using a small number of sensitive parameters outperform those done using a higher-dimensional reasonable-user parameter selection. Optimizations using only sensitive parameters (1) converge faster, (2) have loss values comparable to those found with the naive selection, (3) have similar accuracy in validation tests, and (4) do not suffer from problems of overfitting. We demonstrate that an HSIC global sensitivity is a cheap optimization preprocessing step that has both qualitative and quantitative benefits which can substantially simplify and speed up ReaxFF reparametrizations.

Importance of Nuclear Quantum Effects on Aqueous Electrolyte Transport under Confinement in Ti3C2 MXenes.

Protons display a high chemical activity and strongly affect the charge storage capability in confined interlayer spaces of two-dimensional (2D) materials. As such, an accurate representation of proton dynamics under confinement is important for understanding and predicting charge storage dynamics in these materials. While often ignored in atomistic-scale simulations, nuclear quantum effects (NQEs), e.g., tunneling, can be significant under confinement even at room temperature. Using the thermostatted ring polymer molecular dynamics implementation of path integral molecular dynamics (PIMD) in conjunction with the ReaxFF force field, density functional tight binding (DFTB), and NequIP neural network potential simulations, we investigate the role of NQEs on proton and water transport in bulk water and aqueous electrolytes under confinement in Ti3C2 MXenes. Although overall NQEs are relatively small, especially in bulk, we find that they can alter both quantitative values and qualitative trends on both proton transport and water self-diffusion under confinement relative to classical MD predictions. Therefore, our results suggest the need for NQEs to be considered to simulate aqueous systems under confinement for both qualitative and quantitative accuracy.

Super-ions of sodium cations with hydrated hydroxide anions: inorganic structure-directing agents in zeolite synthesis.

In inorganic zeolite formation, a direct correspondence between liquid state species in the synthesis and the supramolecular decoration of the pores in the as-made final zeolite has never been reported. In this paper, a direct link between the sodium speciation in the synthesis mixture and the pore structure and content of the final zeolite is demonstrated in the example of hydroxysodalite. Super-ions with 4 sodium cations bound by mono- and bihydrated hydroxide are identified as structure-directing agents for the formation of this zeolite. This documentation of inorganic solution species acting as a templating agent in zeolite formation opens new horizons for zeolite synthesis by design.

ParAMS: Parameter Optimization for Atomistic and Molecular Simulations.

This work introduces ParAMS-a versatile Python package that aims to make parametrization workflows in computational chemistry and physics more accessible, transparent, and reproducible. We demonstrate how ParAMS facilitates the parameter optimization for potential energy surface (PES) models, which can otherwise be a tedious specialist task. Because of the package's modular structure, various functionality can be easily combined to implement a diversity of parameter optimization protocols. For example, the choice of PES model and the parameter optimization algorithm can be selected independently. An illustration of ParAMS' strengths is provided in two case studies: (i) a density functional-based tight binding (DFTB) repulsive potential for the inorganic ionic crystal ZnO and (ii) a ReaxFF force field for the simulation of organic disulfides.

PiNN: A Python Library for Building Atomic Neural Networks of Molecules and Materials.

Atomic neural networks (ANNs) constitute a class of machine learning methods for predicting potential energy surfaces and physicochemical properties of molecules and materials. Despite many successes, developing interpretable ANN architectures and implementing existing ones efficiently are still challenging. This calls for reliable, general-purpose, and open-source codes. Here, we present a python library named PiNN as a solution toward this goal. In PiNN, we designed a new interpretable and high-performing graph convolutional neural network variant, PiNet, as well as implemented the established Behler-Parrinello neural network. These implementations were tested using datasets of isolated small molecules, crystalline materials, liquid water, and an aqueous alkaline electrolyte. PiNN comes with a visualizer called PiNNBoard to extract chemical insight "learned" by ANNs. It provides analytical stress tensor calculations and interfaces to both the atomic simulation environment and a development version of the Amsterdam Modeling Suite. Moreover, PiNN is highly modularized, which makes it useful not only as a standalone package but also as a chain of tools to develop and to implement novel ANNs. The code is distributed under a permissive BSD license and is freely accessible at https://github.com/Teoroo-CMC/PiNN/ with full documentation and tutorials.

Temperature effects on the ionic conductivity in concentrated alkaline electrolyte solutions.

Alkaline electrolyte solutions are important components in rechargeable batteries and alkaline fuel cells. As the ionic conductivity is thought to be a limiting factor in the performance of these devices, which are often operated at elevated temperatures, its temperature dependence is of significant interest. Here we use NaOH as a prototypical example of alkaline electrolytes, and for this system we have carried out reactive molecular dynamics simulations with an experimentally verified high-dimensional neural network potential derived from density-functional theory calculations. It is found that in concentrated NaOH solutions elevated temperatures enhance both the contributions of proton transfer to the ionic conductivity and deviations from the Nernst-Einstein relation. These findings are expected to be of practical relevance for electrochemical devices based on alkaline electrolyte solutions.

New Insights into the Catalytic Activity of Cobalt Orthophosphate Co3 (PO4 )2 from Charge Density Analysis.

An extensive characterization of Co3 (PO4 )2 was performed by topological analysis according to Bader's Quantum Theory of Atoms in Molecules from the experimentally and theoretically determined electron density. This study sheds light on the reactivity of cobalt orthophosphate as a solid-state heterogeneous oxidative-dehydration and -dehydrogenation catalyst. Various faces of the bulk catalyst were identified as possible reactive sites given their topological properties. The charge accumulations and depletions around the two independent five- and sixfold-coordinated cobalt atoms, found in the topological analysis, are correlated to the orientation and population of the d-orbitals. It is shown that the (011) face has the best structural features for catalysis. Fivefold-coordinated ions in close proximity to advantageously oriented vacant coordination sites and electron depletions suit the oxygen lone pairs of the reactant, mainly for chemisorption. This is confirmed both from the multipole refinement as well as from density functional theory calculations. Nearby basic phosphate ions are readily available for C-H activation.

One-dimensional vs. two-dimensional proton transport processes at solid-liquid zinc-oxide-water interfaces.

Long-range charge transport is important for many applications like batteries, fuel cells, sensors, and catalysis. Obtaining microscopic insights into the atomistic mechanism is challenging, in particular if the underlying processes involve protons as the charge carriers. Here, large-scale reactive molecular dynamics simulations employing an efficient density-functional-theory-based neural network potential are used to unravel long-range proton transport mechanisms at solid-liquid interfaces, using the zinc oxide-water interface as a prototypical case. We find that the two most frequently occurring ZnO surface facets, (101[combining macron]0) and (112[combining macron]0), that typically dominate the morphologies of zinc oxide nanowires and nanoparticles, show markedly different proton conduction behaviors along the surface with respect to the number of possible proton transfer mechanisms, the role of the solvent for long-range proton migration, as well as the proton transport dimensionality. Understanding such surface-facet-specific mechanisms is crucial for an informed bottom-up approach for the functionalization and application of advanced oxide materials.

Nuclear Quantum Effects in Sodium Hydroxide Solutions from Neural Network Molecular Dynamics Simulations.

Nuclear quantum effects (NQEs) cause the nuclei of light elements like hydrogen to delocalize, affecting numerous properties of water and aqueous solutions, such as hydrogen-bonding and proton transfer barriers. Here, we address the prototypical case of aqueous NaOH solutions by investigating the effects of quantum nuclear fluctuations on radial distribution functions, hydrogen-bonding geometries, power spectra, proton transfer barriers, proton transfer rates, water self-exchange rates around the Na+ cations, and diffusion coefficients, for the full room-temperature solubility range. These properties were calculated from classical and ring-polymer molecular dynamics simulations employing a reactive high-dimensional neural network potential based on dispersion-corrected density functional theory reference calculations. We find that NQEs have a very small impact on the solvation structure around Na+, slightly strengthen the water-water and water-hydroxide hydrogen bonds, and lower the peak positions in the power spectra for the HOH bending and OH stretching modes by about 50 and 100 cm-1, respectively. Moreover, NQEs significantly lower the proton transfer barriers, thus increasing the proton transfer rates, resulting in an increase of the diffusion coefficient in particular of OH-, as well as a decrease of the mean residence time of molecules in the first hydration shell around Na+ at high NaOH concentrations.

Maximally resolved anharmonic OH vibrational spectrum of the water/ZnO(101¯0) interface from a high-dimensional neural network potential.

Unraveling the atomistic details of solid/liquid interfaces, e.g., by means of vibrational spectroscopy, is of vital importance in numerous applications, from electrochemistry to heterogeneous catalysis. Water-oxide interfaces represent a formidable challenge because a large variety of molecular and dissociated water species are present at the surface. Here, we present a comprehensive theoretical analysis of the anharmonic OH stretching vibrations at the water/ZnO(101¯0) interface as a prototypical case. Molecular dynamics simulations employing a reactive high-dimensional neural network potential based on density functional theory calculations have been used to sample the interfacial structures. In the second step, one-dimensional potential energy curves have been generated for a large number of configurations to solve the nuclear Schrödinger equation. We find that (i) the ZnO surface gives rise to OH frequency shifts up to a distance of about 4 Å from the surface; (ii) the spectrum contains a number of overlapping signals arising from different chemical species, with the frequencies decreasing in the order ν(adsorbed hydroxide) > ν(non-adsorbed water) > ν(surface hydroxide) > ν(adsorbed water); (iii) stretching frequencies are strongly influenced by the hydrogen bond pattern of these interfacial species. Finally, we have been able to identify substantial correlations between the stretching frequencies and hydrogen bond lengths for all species.

Surface phase diagram prediction from a minimal number of DFT calculations: redox-active adsorbates on zinc oxide.

Density functional theory (DFT) is routinely used to calculate the adsorption energies of molecules on solid surfaces, which can be employed to derive surface phase diagrams. Such calculations become computationally expensive if the number of substrate atoms is large, which happens whenever the adsorbate coverage is small. Here, we propose an efficient method for calculating surface phase diagrams for redox-active adsorbates on semiconductors, that we apply to the important example of proton (H+) and hydride (H-) adsorbates on a ZnO surface. We identify the leading cause for the coverage dependence of the adsorption energies to be the filling and depletion of the disperse substrate conduction band. From only four DFT calculations, coupled with an analysis of the substrate electronic band structure and changes in the electrostatic potential within the substrate upon adsorption, we derive a phenomenological model that well describes the coverage-dependent adsorption energies. Moreover, our model allows us to extrapolate to the "infinite" supercell limit, where additional H adsorption leads to an arbitrarily small increase of the surface coverage. With this tool we are able to derive a surface phase diagram containing structures with extremely small H coverages (<0.002 ML), that have so far been unattainable. We expect that such models can be applied to a wide range of semiconductor substrates and redox-active adsorbates.

Proton-Transfer-Driven Water Exchange Mechanism in the Na+ Solvation Shell.

Ligand exchange plays an important role for organic and inorganic chemical reactions. We demonstrate the existence of a novel water exchange mechanism, the "proton transfer pathway" (PTP), around Na+(aq) in basic (high pH) solution, using reactive molecular dynamics simulations employing a high-dimensional neural network potential. An aqua ligand in the first solvation (hydration) shell around a sodium ion is only very weakly acidic, but if a hydroxide ion is present in the second solvation shell, thermal fluctuations can cause the aqua ligand to transfer a proton to the neighboring OH-, resulting in a transient direct-contact ion pair, Na+-OH-, which is only weakly bound and easily dissociates. The extent to which water exchange events follow the PTP is pH-dependent: in dilute NaOH(aq) solutions, only very few exchanges occur, whereas in saturated NaOH(aq) solutions up to a third of water self-exchange events are induced by proton transfer. The principles and results outlined here are expected to be relevant for chemical synthesis involving bases and alkali metal cations.

Proton-Transfer Mechanisms at the Water-ZnO Interface: The Role of Presolvation.

The dissociation of water is an important step in many chemical processes at solid surfaces. In particular, water often spontaneously dissociates near metal oxide surfaces, resulting in a mixture of H2O, H+, and OH- at the interface. Ubiquitous proton-transfer (PT) reactions cause these species to dynamically interconvert, but the underlying mechanisms are poorly understood. Here, we develop and use a reactive high-dimensional neural-network potential based on density functional theory data to elucidate the structural and dynamical properties of the interfacial species at the liquid-water-metal-oxide interface, using the nonpolar ZnO(101̅0) surface as a prototypical case. Molecular dynamics simulations reveal that water dissociation and recombination proceed via two types of PT reactions: (i) to and from surface oxide and hydroxide anions ("surface-PT") and (ii) to and from neighboring adsorbed hydroxide ions and water molecules ("adlayer-PT"). We find that the adlayer-PT rate is significantly higher than the surface-PT rate. Water dissociation is, for both types of PT, governed by a predominant presolvation mechanism, i.e., thermal fluctuations that cause the adsorbed water molecules to occasionally accept a hydrogen bond, resulting in a decreased PT barrier and an increased dissociation rate as compared to when no hydrogen bond is present. Consequently, we are able to show that hydrogen bond fluctuations govern PT events at the water-metal-oxide interface in a way similar to that in acidic and basic aqueous bulk solutions.

Structure of aqueous NaOH solutions: insights from neural-network-based molecular dynamics simulations.

Sodium hydroxide, NaOH, is one of the most widely-used chemical reagents, but the structural properties of its aqueous solutions have only sparingly been characterized. Here, we automatically classify the cation coordination polyhedra obtained from molecular dynamics simulations. We find that, for example, with increasing concentration, octahedral coordination geometries become less favored, while the opposite is true for the trigonal prism. At high concentrations, the coordination polyhedra frequently deviate considerably from "ideal" polyhedra, because of an increased extent of interligand hydrogen-bonding, in which hydrogen bonds between two ligands, either OH2 or OH-, around the same Na+ are formed. In saturated solutions, with concentrations of about 19 mol L-1, ligands are frequently shared between multiple Na+ ions as a result of the deficiency of solvent molecules. This results in more complex structural patterns involving certain "characteristic" polyhedron connectivities, such as octahedra sharing ligands with capped trigonal prisms, and tetrahedra sharing ligands with trigonal bipyramids. The simulations were performed using a density-functional-theory-based reactive high-dimensional neural network potential, that was extensively validated against available neutron and X-ray diffraction data from the literature.

Concentration-Dependent Proton Transfer Mechanisms in Aqueous NaOH Solutions: From Acceptor-Driven to Donor-Driven and Back.

Proton transfer processes play an important role in many fields of chemistry. In dilute basic aqueous solutions, proton transfer from water molecules to hydroxide ions is aided by "presolvation", i.e., thermal fluctuations that modify the hydrogen-bonding environment around the proton-receiving OH(-) ion to become more similar to that of a neutral H2O molecule. In particular at high concentrations, however, the underlying mechanisms and especially the role of the counterions are little understood. As a prototypical case, we investigate aqueous NaOH solutions using molecular dynamics simulations employing a reactive high-dimensional neural-network potential constructed from density functional theory reference data. We find that with increasing concentration the predominant proton transfer mechanism changes from being "acceptor-driven", i.e., governed by the presolvation of OH(-), to "donor-driven", i.e., governed by the presolvation of H2O, and back to acceptor-driven near the room-temperature solubility limit of 19 mol/L, which corresponds to an extremely solvent-deficient system containing only about one H2O molecule per ion. Specifically, we identify concentration ranges where the proton transfer rate is mostly affected by OH(-) losing an accepted hydrogen bond, OH(-) forming a donated hydrogen bond, H2O forming an accepted hydrogen bond, or H2O losing a coordinated Na(+). Presolvation also manifests itself in the shortening of the Na(+)-OH2 distances, in that the Na(+) "pushes" one of the H2O protons away.

Enhanced wetting of Cu on ZnO by migration of subsurface oxygen vacancies.

Metal adhesion on metal oxides is strongly controlled by the oxide surface structure and composition, but lack of control over the surface conditions often limits the possibilities to exploit this in opto- and micro-electronics applications and heterogeneous catalysis where nanostructural control is of utmost importance. The Cu/ZnO system is among the most investigated of such systems in model studies, but the presence of subsurface ZnO defects and their important role for adhesion on ZnO have been unappreciated so far. Here we reveal that the surface-directed migration of subsurface defects affects the Cu adhesion on polar ZnO(0001) in the technologically interesting temperature range up to 550 K. This leads to enhanced adhesion and ultimately complete wetting of ZnO(0001) by a Cu overlayer. On the basis of our experimental and computational results we demonstrate a mechanism which implies that defect concentrations in the bulk are an important, and possibly controllable, parameter for the metal-on-oxide growth.

Treatment of delocalized electron transfer in periodic and embedded cluster DFT calculations: The case of Cu on ZnO (10(1)0).

We assess the consequences of the interface model-embedded-cluster or periodic-slab model-on the ability of DFT calculations to describe charge transfer (CT) in a particularly challenging case where periodic-slab calculations indicate a delocalized charge-transfer state. Our example is Cu atom adsorption on ZnO(10(1)0), and in fact the periodic slab calculations indicate three types of CT depending on the adsorption site: full CT, partial CT, and no CT. Interestingly, when full CT occurs in the periodic calculations, the calculated Cu atom adsorption energy depends on the underlying ZnO substrate supercell size, since when the electron enters the ZnO it delocalizes over as many atoms as possible. In the embedded-cluster calculations, the electron transferred to the ZnO delocalizes over the entire cluster region, and as a result the calculated Cu atom adsorption energy does not agree with the value obtained using a large periodic supercell, but instead to the adsorption energy obtained for a periodic supercell of roughly the same size as the embedded cluster. Different density functionals (of GGA and hybrid types) and basis sets (local atom-centered and plane-waves) were assessed, and we show that embedded clusters can be used to model Cu adsorption on ZnO(10(1)0), as long as care is taken to account for the effects of CT.

An SCC-DFTB Repulsive Potential for Various ZnO Polymorphs and the ZnO-Water System.

We have developed an efficient scheme for the generation of accurate repulsive potentials for self-consistent charge density-functional-based tight-binding calculations, which involves energy-volume scans of bulk polymorphs with different coordination numbers. The scheme was used to generate an optimized parameter set for various ZnO polymorphs. The new potential was subsequently tested for ZnO bulk, surface, and nanowire systems as well as for water adsorption on the low-index wurtzite (101̅0) and (112̅0) surfaces. By comparison to results obtained at the density functional level of theory, we show that the newly generated repulsive potential is highly transferable and capable of capturing most of the relevant chemistry of ZnO and the ZnO/water interface.

Band-Filling Correction Method for Accurate Adsorption Energy Calculations: A Cu/ZnO Case Study.

We present a simple method, the "band-filling correction", to calculate accurate adsorption energies (Eads) in the low coverage limit from finite-size supercell slab calculations using DFT. We show that it is necessary to use such a correction if charge transfer takes place between the adsorbate and the substrate, resulting in the substrate bands either filling up or becoming depleted. With this correction scheme, we calculate Eads of an isolated Cu atom adsorbed on the ZnO(101̅0) surface. Without the correction, the calculated Eads is highly coverage-dependent, even for surface supercells that would typically be considered very large (in the range from 1 nm × 1 nm to 2.5 nm × 2.5 nm). The correction scheme works very well for semilocal functionals, where the corrected Eads is converged within 0.01 eV for all coverages. The correction scheme also works well for hybrid functionals if a large supercell is used and the exact exchange interaction is screened.