Computation and data driven discovery of topological phononic materials

TL;DR

This paper presents a data-driven high-throughput method to identify and classify over 5000 topological phononic materials, expanding the library for future research and device applications in topological phononics.

Contribution

It introduces a large-scale computational screening approach to discover and classify topological phononic materials, providing a valuable resource for future studies.

Findings

Identified 5014 topological phononic materials

Classified materials into Weyl and nodal-line types

Suggested 322 materials with potential surface states

Abstract

The discovery of topological quantum states marks a new chapter in both condensed matter physics and materials sciences. By analogy to spin electronic system, topological concepts have been extended into phonons, boosting the birth of topological phononics (TPs). Here, we present a high-throughput screening and data-driven approach to compute and evaluate TPs among over 10,000 materials. We have clarified 5014 TP materials and classified them into single Weyl, high degenerate Weyl, and nodal-line (ring) TPs. Among them, three representative cases of TPs have been discussed in detail. Furthermore, we suggest 322 TP materials with potential clean nontrivial surface states, which are favorable for experimental characterizations. This work significantly increases the current library of TP materials, which enables an in-depth investigation of their structure-property relations and opens new avenues for future device design related to TPs.