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The electrical double layer (EDL) at aqueous solution-metal oxide interfaces critically affects many fundamental processes in electrochemistry, geology and biology, yet understanding its microscopic structure is challenging for both theory and experiments. Here we employ ab initio-based machine learning potentials including long-range electrostatics in large-scale atomistic simulations of the EDL at the TiO2-electrolyte interface. Our simulations provide a molecular-scale picture of the EDL that demonstrates the limitations of standard mean-field models. We further develop a method to accurately calculate the electrostatic potential drop at the interface. The computed capacitance originating from the adsorbed charges and the potential drop agrees with experiments, supporting the reliability of our description of the EDL. The larger interfacial capacitance of basic relative to acidic solutions originates from the higher affinity of the cations for the oxide surface and gives rise to distinct charging mechanisms on negative and positive surfaces.

The formation of ice in the atmosphere affects precipitation and cloud properties, and plays a key role in the climate of our planet. Although ice can form directly from liquid water at deeply supercooled conditions, the presence of foreign particles can aid ice formation at much warmer temperatures. Over the past decade, experiments have highlighted the remarkable efficiency of feldspar minerals as ice nuclei compared to other particles present in the atmosphere. However, the exact mechanism of ice formation on feldspar surfaces has yet to be fully understood. Here, we develop a first-principles machine-learning model for the potential energy surface aimed at studying ice nucleation at microcline feldspar surfaces. The model is able to reproduce with high fidelity the energies and forces derived from density-functional theory (DFT) based on the SCAN exchange and correlation functional. We apply the machine-learning force field to study different fully-hydroxylated terminations of the (100), (010), and (001) surfaces of microcline exposed to vacuum. Our calculations suggest that terminations that do not minimize the number of broken bonds are preferred in vacuum. We also study the structure of supercooled liquid water in contact with microcline surfaces, and find that water density correlations extend up to around 1 nm from the surfaces. Finally, we show that the force field maintains a high accuracy during the simulation of ice formation at microcline surfaces, even for large systems of around 30,000 atoms. Future work will be directed towards the calculation of nucleation free energy barriers and rates using the force field developed herein, and understanding the role of different microcline surfaces on ice nucleation., Comment: 12 pages, 6 figures

Two-dimensional (2D) metallic states induced by oxygen vacancies at oxide surfaces and interfaces provide new opportunities for the development of advanced applications, but the ability to control the behavior of these states is still limited. We used Angle Resolved Photoelectron Spectroscopy combined with density functional theory to study the reactivity of states induced by the oxygen vacancies at the (001)-(1x4) surface of anatase TiO2, where both 2D metallic and deeper lying in-gap states (IGs) are observed. Remarkably, the two states exhibit very different evolution when the surface is exposed to molecular O2: while IGs are almost completely quenched, the metallic states are only weakly affected. The energy scale analysis for the vacancy migration and recombination resulting from the DFT calculations confirms indeed that only the IGs originate from and remain localized at the surface, whereas the metallic states originate from subsurface vacancies, whose migration and recombination at the surface is energetically less favorable rendering them therefore insensitive to oxygen dosing.

Doping is one of the most common strategies for improving the photocatalytic and solar energy conversion properties of TiO$_2$, hence an accurate theoretical description of the electronic and optical properties of doped TiO$_2$ is of both scientific and practical interest. In this work we use many-body perturbation theory techniques to investigate two typical n-type dopants, Niobium and Hydrogen, in TiO$_2$ rutile. Using the GW approximation to determine band edges and defect energy levels, and the Bethe Salpeter equation for the calculation of the absorption spectra, we find that the defect energy levels form non-dispersive bands %associated with localized states lying $\simeq 2.2 eV$ above the top of the corresponding valence bands ($\simeq 0.9 eV$ below the conduction bands of the {\it pristine} material). The defect states are also responsible for the appearance of low energy absorption peaks that enhance the solar spectrum absorption of rutile. The spatial distributions of the excitonic wavefunctions associated with these low energy excitations are very different for the two dopants, suggesting a larger mobility of photoexcited electrons in Nb-TiO$_2$., Comment: 8 pages, 6 figures

Oxygen (O2) adsorbed on metal oxides is important in catalytic oxidation reactions, chemical sensing, and photocatalysis. Strong adsorption requires transfer of negative charge from oxygen vacancies (VOs) or dopants, for example. With scanning tunneling microscopy, we observed, transformed, and, in conjunction with theory, identified the nature of O2 molecules on the (101) surface of anatase (titanium oxide, TiO2) doped with niobium. VOs reside exclusively in the bulk, but we pull them to the surface with a strongly negatively charged scanning tunneling microscope tip. O2 adsorbed as superoxo (O2)- at fivefold-coordinated Ti sites was transformed to peroxo (O2)2- and, via reaction with a VO, placed into an anion surface lattice site as an (O2)O species. This so-called bridging dimer also formed when O2 directly reacted with VOs at or below the surface.

Anatase is a metastable polymorph of TiO$_2$. In contrast to the more widely-studied TiO$_2$ rutile, O vacancies (V$_\mathrm O$'s) are not stable at the anatase (101) surface. Low-temperature STM shows that surface V$_\mathrm O$'s, created by electron bombardment at 105 K, start migrating to subsurface sites at temperatures $\geq$ 200 K. After an initial decrease of the V$_\mathrm O$ density, a temperature-dependent dynamic equilibrium is established where V$_\mathrm O$'s move to subsurface sites and back again, as seen in time-lapse STM images. We estimate that activation energies for subsurface migration lie between 0.6 and 1.2 eV; in comparison, DFT calculations predict a barrier of ca. 0.75 eV. The wide scatter of the experimental values might be attributed to inhomogeneously-distributed subsurface defects in the reduced sample.

We use density functional theory (DFT) calculations to investigate structural models consisting of anatase TiO2(101) slabs covered by reduced overlayers formed by (101) crystallographic shear planes (CSPs). Ab initio thermodynamics supports the stability of these structures under a wide range of experimental conditions. The overlayers are found to have Ti2O3 stoichiometry with a crystal structure different from the known corundum-like Ti2O3 (here denoted {\alpha}-Ti2O3) phase. DFT calculations predict this new "csp-Ti2O3" phase to be energetically close to {\alpha}-Ti2O3 and to have also a similar band gap. These results suggest a possible role of the csp-Ti2O3 phase in the properties of black TiO2, a promising photocatalytic material made of nanoparticles with a crystalline TiO2 core and a highly reduced TiOx shell that is capable of absorbing the whole spectrum of visible light.

Water is of the utmost importance for life and technology. However, a genuinely predictive ab initio model of water has eluded scientists. We demonstrate that a fully ab initio approach, relying on the strongly constrained and appropriately normed (SCAN) density functional, provides such a description of water. SCAN accurately describes the balance among covalent bonds, hydrogen bonds, and van der Waals interactions that dictates the structure and dynamics of liquid water. Notably, SCAN captures the density difference between water and ice I{\it h} at ambient conditions, as well as many important structural, electronic, and dynamic properties of liquid water. These successful predictions of the versatile SCAN functional open the gates to study complex processes in aqueous phase chemistry and the interactions of water with other materials in an efficient, accurate, and predictive, ab initio manner.