The recent observation of room-temperature superconductivity will undoubtedly lead to a surge in the discovery of new, dense, hydrogen-rich materials. The rare earth metal superhydrides are predicted to have very high-Tc superconductivity that is tunable with changes in stoichiometry or doping. Here we report the synthesis of a yttrium superhydride that exhibits superconductivity at a critical temperature of 262 K at 182 ± 8 GPa. A palladium thin film assists the synthesis by protecting the sputtered yttrium from oxidation and promoting subsequent hydrogenation. Phononmediated superconductivity is established by the observation of zero resistance, an isotope effect and the reduction of Tc under an external magnetic field. The upper critical magnetic field is 103 T at zero temperature.
Good agreement was found between experimental Vickers hardnesses, Hv, of a wide range of materials and those calculated by three macroscopic hardness models that employ the shear and/or bulk moduli obtained from: (i) first principles via AFLOW-AEL (AFLOW Automatic Elastic Library), and (ii) a machine learning (ML) model trained on materials within the AFLOW repository. Because H ML v values can be quickly estimated, they can be used in conjunction with an evolutionary search to predict stable, superhard materials. This methodology is implemented in the XTALOPT evolutionary algorithm. Each crystal is minimized to the nearest local minimum, and its Vickers hardness is computed via a linear relationship with the shear modulus discovered by Teter. Both the energy/enthalpy and H ML v, Teter are employed to determine a structure's fitness. This implementation is applied towards the carbon system, and 43 new superhard phases are found. A topological analysis reveals that phases estimated to be slightly harder than diamond contain a substantial fraction of diamond and/or lonsdaleite. arXiv:1906.05886v1 [cond-mat.mtrl-sci]
Significant progress has been made
in the field of a priori crystal structure prediction,
with a number of recent remarkable
success stories. Herein, we briefly outline the methods that have
been developed for finding the global minimum structure and interesting
local minima without the need for experimental information. Focus
is placed on describing the XtalOpt evolutionary algorithm (EA) developed
in our group toward this end. XtalOpt is published under well-known
open-source licenses, and the EA searches can be analyzed via the
Avogadro chemical editor and visualizer. We describe new algorithmic
developments that have made it possible to predict the structures
of ever-more complex crystalline lattices. Benchmark tests, which
clearly illustrate how the new developments improve the success rate
and accelerate the discovery of the global minimum structure, are
performed. Finally, we describe how XtalOpt has been employed to predict
novel ternary hydrides that have the propensity for high-temperature
superconductivity under pressure.
Evolutionary searches predicted a number of ternary phases that could be synthesized at pressures of 100-300 GPa. P 6 3 /mmc CaSH 2 , P nma CaSH 2 , Cmc2 1 CaSH 6 , and I4 CaSH 20 were composed of a Ca-S lattice along with H 2 molecules coordinated in a "side-on" fashion to Ca. The H-H bond lengths in these semiconducting phases were elongated because of H 2 σ → Ca d donation, and Ca d→ H 2 σ * back-donation, via a Kubas-like mechanism. P6m2 CaSH 3 , consisting of two-dimensional HS and CaH 2 sheets, was metastable and metallic above 128 GPa. The presence
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