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Machine-learned interatomic potentials are fast becoming an indispensable tool in computational materials science. One approach is the ephemeral data-derived potential (EDDP), which was designed to accelerate atomistic structure prediction. The EDDP is simple and cost-efficient. It relies on training data generated in small unit cells and is fit using a lightweight neural network, leading to smooth interactions which exhibit the robust transferability essential for structure prediction. Here, we present a variety of applications of EDDPs, enabled by recent developments of the open-source EDDP software. New features include interfaces to phonon and molecular dynamics codes, as well as deployment of the ensemble deviation for estimating the confidence in EDDP predictions. Through case studies ranging from elemental carbon and lead to the binary scandium hydride and the ternary zinc cyanide, we demonstrate that EDDPs can be trained to cover wide ranges of pressures and stoichiometries, and used to evaluate phonons, phase diagrams, superionicity, and thermal expansion. These developments complement continued success in accelerated structure prediction. [ABSTRACT FROM AUTHOR]

Fluorite-perovskite heterointerfaces garner great interest for enhanced ionic conductivity for application in electronic and energy devices. However, the origin of observed enhanced ionic conductivity as well as the details of the atomic structure at these interfaces remain elusive. Here, systematic, multi-stoichiometry computational searches and experimental investigations are performed to obtain stable and exact atomic structures of interfaces between CeO2 and SrTiO3—two archetypes of the corresponding structural families. Local reconstructions take place at the interface because of mismatched lattices. TiO2 terminated SrTiO3 causes a buckled rock salt CeO interface layer to emerge. In contrast, SrO terminated SrTiO3 maintains the fluorite structure at the interface compensated by a partially occupied anion lattice. Moderate enhancement in oxygen diffusion is found along the interface by simulations, yet evidence to support further significant enhancement is lacking. Our findings demonstrate the control of interface termination as an effective pathway to achieve desired device performance. [ABSTRACT FROM AUTHOR]

Hydrogen, the simplest and most abundant element in the Universe, develops a remarkably complex behaviour upon compression.sup.1. Since Wigner predicted the dissociation and metallization of solid hydrogen at megabar pressures almost a century ago.sup.2, several efforts have been made to explain the many unusual properties of dense hydrogen, including a rich and poorly understood solid polymorphism.sup.1,3-5, an anomalous melting line.sup.6 and the possible transition to a superconducting state.sup.7. Experiments at such extreme conditions are challenging and often lead to hard-to-interpret and controversial observations, whereas theoretical investigations are constrained by the huge computational cost of sufficiently accurate quantum mechanical calculations. Here we present a theoretical study of the phase diagram of dense hydrogen that uses machine learning to 'learn' potential-energy surfaces and interatomic forces from reference calculations and then predict them at low computational cost, overcoming length- and timescale limitations. We reproduce both the re-entrant melting behaviour and the polymorphism of the solid phase. Simulations using our machine-learning-based potentials provide evidence for a continuous molecular-to-atomic transition in the liquid, with no first-order transition observed above the melting line. This suggests a smooth transition between insulating and metallic layers in giant gas planets, and reconciles existing discrepancies between experiments as a manifestation of supercritical behaviour. Simulations using machine-learning-based interatomic potentials in dense hydrogen overcome system size and timescale limitations, providing evidence of a supercritical behaviour of high-pressure liquid hydrogen and reconciling theoretical and experimental discrepancies., Author(s): Bingqing Cheng [sup.1] [sup.2] [sup.3] , Guglielmo Mazzola [sup.4] , Chris J. Pickard [sup.5] [sup.6] , Michele Ceriotti [sup.7] [sup.8] Author Affiliations: (1) Department of Chemistry, University of Cambridge, [...]

Titanium dioxide has been extensively studied in the rutile or anatase phase, while its high-pressure phases are less well-understood, despite that many are thought to have interesting optical, mechanical, and electrochemical properties. First-principles methods, such as density functional theory (DFT), are often used to compute the enthalpies of TiO2 phases at 0 K, but they are expensive and, thus, impractical for long time scale and large system-size simulations at finite temperatures. On the other hand, cheap empirical potentials fail to capture the relative stabilities of various polymorphs. To model the thermodynamic behaviors of ambient and high-pressure phases of TiO2, we design an empirical model as a baseline and then train a machine learning potential based on the difference between the DFT data and the empirical model. This so-called Δ-learning potential contains long-range electrostatic interactions and predicts the 0 K enthalpies of stable TiO2 phases that are in good agreement with DFT. We construct a pressure–temperature phase diagram of TiO2 in the range 0 < P < 70 GPa and 100 < T < 1500 K. We then simulate dynamic phase transition processes by compressing anatase at different temperatures. At 300 K, we predominantly observe an anatase-to-baddeleyite transformation at about 20 GPa via a martensitic two-step mechanism with a highly ordered and collective atomic motion. At 2000 K, anatase can transform into cotunnite around 45–55 GPa in a thermally activated and probabilistic manner, accompanied by diffusive movement of oxygen atoms. The pressures computed for these transitions show good agreement with experiments. Our results shed light on how to synthesize and stabilize high-pressure TiO2 phases, and our method is generally applicable to other functional materials with multiple polymorphs. [ABSTRACT FROM AUTHOR]

Using first-principles calculations and crystal structure search methods, we found that many covalently bonded molecules such as H2, N2, CO2, NH3, H2O and CH4 may react with NaCl, a prototype ionic solid, and form stable compounds under pressure while retaining their molecular structure. These molecules, despite whether they are homonuclear or heteronuclear, polar or non-polar, small or large, do not show strong chemical interactions with surrounding Na and Cl ions. In contrast, the most stable molecule among all examples, N2, is found to transform into cyclo-N5− anions while reacting with NaCl under high pressures. It provides a new route to synthesize pentazolates, which are promising green energy materials with high energy density. Our work demonstrates a unique and universal hybridization propensity of covalently bonded molecules and solid compounds under pressure. This surprising miscibility suggests possible mixing regions between the molecular and rock layers in the interiors of large planets. [ABSTRACT FROM AUTHOR]

Through a series of high-pressure x-ray diffraction experiments combined with in situ laser heating, we explore the pressure–temperature phase diagram of germanium (Ge) at pressures up to 110 GPa and temperatures exceeding 3000 K. In the pressure range of 64–90 GPa, we observe orthorhombic Ge-IV transforming above 1500 K to a previously unobserved high-temperature phase, which we denote as Ge-VIII. This high-temperature phase is characterized by a tetragonal crystal structure, space group I4/mmm. Density functional theory simulations confirm that Ge-IV becomes unstable at high temperatures and that Ge-VIII is highly competitive and dynamically stable at these conditions. The existence of Ge-VIII has profound implications for the pressure–temperature phase diagram, with melting conditions increasing to much higher temperatures than previous extrapolations would imply. [ABSTRACT FROM AUTHOR]

Cathodes are critical components of rechargeable batteries. Conventionally, the search for cathode materials relies on experimental trial-and-error and a traversing of existing computational/experimental databases. While these methods have led to the discovery of several commercially viable cathode materials, the chemical space explored so far is limited and many phases will have been overlooked, in particular, those that are metastable. We describe a computational framework for battery cathode exploration based on ab initio random structure searching (AIRSS), an approach that samples local minima on the potential energy surface to identify new crystal structures. We show that by delimiting the search space using a number of constraints, including chemically aware minimum interatomic separations, cell volumes, and space group symmetries, AIRSS can efficiently predict both thermodynamically stable and metastable cathode materials. Specifically, we investigate LiCoO2, LiFePO4, and LixCuyFz to demonstrate the efficiency of the method by rediscovering the known crystal structures of these cathode materials. The effect of parameters, such as minimum separations and symmetries, on the efficiency of the sampling is discussed in detail. The adaptation of the minimum interatomic distances on a species-pair basis, from low-energy optimized structures to efficiently capture the local coordination environment of atoms, is explored. A family of novel cathode materials based on the transition-metal oxalates is proposed. They demonstrate superb energy density, oxygen-redox stability, and lithium diffusion properties. This article serves both as an introduction to the computational framework and as a guide to battery cathode material discovery using AIRSS. [ABSTRACT FROM AUTHOR]

The quantum nature of the proton can crucially affect the structural and physical properties of hydrogen compounds. For example, in the high-pressure phases (1,2) of [H.sub.2]O, quantum proton fluctuations lead to symmetrization of the hydrogen bond and reduce the boundary between asymmetric and symmetric structures in the phase diagram by 30 gigapascals (ref. 3). Here we show that an analogous quantum symmetrization occurs in the recently discovered (4) sulfur hydride superconductor with a superconducting transition temperature [T.sub.c] of 203 kelvin at 155 gigapascals--the highest [T.sub.c] reported for any superconductor so far. Superconductivity occurs via the formation of a compound with chemical formula [H.sub.3]S (sulfur trihydride) with sulfur atoms arranged on a body-centred cubic lattice (5-9). If the hydrogen atoms are treated as classical particles, then for pressures greater than about 175 gigapascals they are predicted to sit exactly halfway between two sulfur atoms in a structure with Im[bar.3]m symmetry. At lower pressures, the hydrogen atoms move to an off-centre position, forming a short H-S covalent bond and a longer H***S hydrogen bond in a structure with R3m symmetry (5-9). X-ray diffraction experiments confirm the [H.sub.3]S stoichiometry and the sulfur lattice sites, but were unable to discriminate between the two phases (10). Ab initio density-functional-theory calculations show that quantum nuclear motion lowers the symmetrization pressure by 72 gigapascals for [H.sub.3]S and by 60 gigapascals for [D.sub.3]S. Consequently, we predict that the Im[bar.3]m phase dominates the pressure range within which the high [T.sub.c] was measured. The observed pressure dependence of [T.sub.c] is accurately reproduced in our calculations for the Im[bar.3]m phase, but not for the R3m phase. Therefore, the quantum nature of the proton fundamentally changes the superconducting phase diagram of [H.sub.3]S., The recent discovery of high-temperature superconductivity in compressed hydrogen sulfide (4) has led to a number of theoretical studies aimed at understanding the phase diagram of the H-S system and [...]

Most metals adopt simple structures such as body-centered cubic (BCC), face-centered cubic (FCC), and hexagonal close-packed (HCP) structures in specific groupings across the periodic table, and many undergo transitions to surprisingly complex structures on compression, not expected from conventional free-electron-based theories of metals. First-principles calculations have been able to reproduce many observed structures and transitions, but a unified, predictive theory that underlies this behavior is not yet in hand. Discovered by analyzing the electronic properties of metals in various lattices over a broad range of sizes and geometries, a remarkably simple theory shows that the stability of metal structures is governed by electrons occupying local interstitial orbitals and their strong chemical interactions. The theory provides a basis for understanding and predicting structures in solid compounds and alloys over a broad range of conditions. [ABSTRACT FROM AUTHOR]

KSiH3 exhibits 4.1 wt% experimental hydrogen storage capacity and shows reversibility under moderate conditions, which provides fresh impetus to the search for other complex hydrides in the K–Si–H system. Here, we reproduce the stable Fm3¯m phase of K2SiH6 and uncover two denser phases, space groups P3¯m1 and P63mc at ambient pressure, by means of first-principles structure searches. We note that P3¯m1-K2SiH6 has a high hydrogen content of 5.4 wt% and a volumetric density of 88.3 g L−1. Further calculations suggest a favorable dehydrogenation temperature Tdes of −20.1/55.8 °C with decomposition into KSi + K + H2. The higher hydrogen density and appropriate dehydrogenation temperature indicate that K2SiH6 is a promising hydrogen storage material, and our results provide helpful and clear guidance for further experimental studies. We found three further potential hydrogen storage materials stable at high pressure: K2SiH8, KSiH7 and KSiH8. These results suggest the need for further investigations into hydrogen storage materials among such ternary hydrides at high pressure. [ABSTRACT FROM AUTHOR]