Discovery of High-Temperature Superconducting Ternary Hydrides via Deep Learning

TL;DR

This paper presents a deep learning framework that efficiently explores vast chemical spaces to discover new high-temperature superconducting ternary hydrides, significantly expanding known structures and predicting many candidates with Tc above 200 K.

Contribution

The study introduces a scalable deep-learning approach integrating structure exploration and physics-based screening to identify novel high-Tc hydride superconductors.

Findings

Explored 36 million structures across 29 elements.

Identified 144 potential high-Tc superconductors with Tc > 200 K.

Discovered 129 new compounds with diverse structures.

Abstract

The discovery of novel high-temperature superconductor materials holds transformative potential for a wide array of technological applications. However, the combinatorially vast chemical and configurational search space poses a significant bottleneck for both experimental and theoretical investigations. In this study, we employ the design of high-temperature ternary superhydride superconductors as a representative case to demonstrate how this challenge can be well addressed through a deep-learning-driven theoretical framework. This framework integrates high-throughput crystal structure exploration, physics-informed screening, and accurate prediction of superconducting critical temperatures. Our approach enabled the exploration of approximately 36 million ternary hydride structures across a chemical space of 29 elements, leading to the identification of 144 potential high-Tc superconductors with predicted Tc > 200 K and superior thermodynamic stability at 200 GPa. Among these, 129 compounds spanning 27 novel structural prototypes are reported for the first time, representing a significant expansion of the known structural landscape for hydride superconductors. This work not only greatly expands the known repertoire of high-Tc hydride superconductors but also establishes a scalable and efficient methodology for navigating the complex landscape of multinary hydrides.