A Gaussian approximation potential was trained using density-functional theory data to enable a global geometry optimization of low-index rutile IrO 2 facets through simulated annealing. Ab initio thermodynamics identifies ( 101) and ( 111) (1 × 1) terminations competitive with (110) in reducing environments. Experiments on single crystals find that (101) facets dominate and exhibit the theoretically predicted (1 × 1) periodicity and x-ray photoelectron spectroscopy core-level shifts. The obtained structures are analogous to the complexions discussed in the context of ceramic battery materials.

Machine-learning interatomic potentials, such as Gaussian Approximation Potentials (GAPs), constitute a powerful class of surrogate models to computationally involved first-principles calculations. At a similar predictive quality but significantly reduced cost, they could leverage otherwise barely tractable extensive sampling as in global surface structure determination (SSD). This efficiency is jeopardized though, if an a priori unknown structural and chemical search space as in SSD requires an excessive number of first-principles data for the GAP training. To this end, we present a general and data-efficient iterative training protocol that blends the creation of new training data with the actual surface exploration process. Demonstrating this protocol with the SSD of low-index facets of rutile IrO2 and RuO2, the involved simulated annealing on the basis of the refining GAP identifies a number of unknown terminations even in the restricted sub-space of (1 × 1) surface unit cells. Particularly in an O-poor environment, some of these, then metal-rich terminations, are thermodynamically most stable and are reminiscent of complexions as discussed for complex ceramic materials.

The knowledge of dielectric response properties of the environment is of paramount importance in many theoretical embedding methods and studies of solutes and of catalytic sites and processes in condensed phases. In particular, the realistic embedding of active sites into solid/liquid and liquid/liquid interfaces is a crucial point in the context of modeling energy conversion (e.g., electrochemical, photochemical, power-to-X) processes. Recently, the finding that the dielectric permeability of liquids near solid/liquid interfaces is far from being constant but deviates strongly from the bulk value within several nanometers from the interface has raised the interest in a more fundamental understanding of the response properties near interfaces. As these questions are hard to study experimentally, reliable theoretical models are required. Here we describe a careful first-principles based reparametrization of nonpolarizable molecular mechanics force fields for a class of technological relevant organic chlorinated hydrocarbon solvents which are immiscible with water. For the solvent 1,2-dichloroethane (1,2-DCE) we also present a new polarizable force field based on the Drude oscillator model. Its parametrization needs particular attention to avoid unphysical couplings between the internal torsional degree of freedom and the Drude oscillators, which could severely skew the response properties. The performance of this new set of force fields is critically assessed based on a comprehensive molecular dynamics study.