Superconductive materials with MgB2-like structures from data-driven screening

TL;DR

This paper demonstrates a comprehensive data-driven approach to discover new MgB2-like superconductors, successfully identifying and experimentally confirming several promising compounds with superconducting properties.

Contribution

The study introduces an end-to-end data-driven method for discovering MgB2-like superconductors, including computational screening and experimental validation of new materials.

Findings

Identified several new MgB2-like superconductors with predicted Tc values.

Experimentally confirmed BaGa2 as a BCS superconductor with Tc = 0.36 K.

Showcased the feasibility of discovering new superconductors through data-driven techniques.

Abstract

Finding viable superconducting materials is of interest to the physics community as the superconductors are the playground to manifest many appealing quantum phenomena. This work exemplifies an end-to-end materials discovery towards novel MgB2-like superconductors, starting from the data-driven compound screening all the way to the experimental materialization. In addition to the known superconducting compounds, CaB2 (Tc = 9.4 ~ 28.6 K), SrGa2 (Tc = 0.1 ~ 2.4 K), BaGa2 (Tc = 0.3 ~ 3.3 K), BaAu2 (Tc = 0.0 ~ 0.5 K), and LaCu2 (Tc = 0.1 ~ 2.2 K) are newly discovered, out of ~182,000 starting structures, to be the most promising superconducting compounds that share similar atomic structures with MgB2. Moreover, BaGa2 is experimentally synthesized and measured to confirm that the compound is a BCS superconductor with Tc = 0.36 K, in good agreement with our theoretical predictions. This work provides a "once and for all" study for the MgB2-like superconductors and showcases that it is feasible to discover new materials via a data-driven approach.