Data-driven design of high-temperature superconductivity among ternary hydrides under pressure

TL;DR

This paper introduces a data-driven approach to efficiently identify high-temperature superconducting ternary hydrides under pressure, significantly expanding the known prototypes and predicting structures with Tcs near room temperature.

Contribution

It presents a novel, efficient strategy combining generated frameworks and quick stability and Tc estimations, uncovering more prototypes and promising high-Tc structures than previous methods.

Findings

Identified 14 new hydrogen frameworks for clathrate hydrides.

Predicted 11 structures with Tcs above 250 K at 300 GPa.

Li2NaH17 and ThY2H24 are thermodynamically stable with Tcs near room temperature.

Abstract

Recently, ternary clathrate hydrides are promising candidates for high-temperature superconductor. However, it is a formidable challenge to effectively hunt high-temperature superconductivity among multinary hydrides due to the expensive computational cost associated with large unit cells and huge stoichiometric choices. Here we present an efficiently data-driven strategy, including generated clathrate frameworks, the quick estimation of stability for each framework and superconducting critical temperature (Tc) for each hydride structure, to accelerate the discovery of high-temperature superconducting hydrides. Our strategy was initialized with more than one million input structures via zeolite databases and our generated dataset. As a result, such a strategy hitherto uncovered 14 prototypical hydrogen frameworks for clathrate hydrides, which is 1.5 times greater than the number (9) of previously reported prototypes. Remarkably, eleven ternary clathrate structures were predicted to have Tcs above 250 K at 300 GPa. Further extensive global structure-searching simulations support that Li2NaH17 and ThY2H24 are thermodynamically stable at 220 and 150 GPa, respectively, with Tcs approaching room temperature of 297 K and 303 K, which are promising for future synthesis. These results offer a platform to explore high-temperature superconductors via a great number of databases.