High-Throughput Density Functional Theory Screening of Double Transition Metal MXene Precursors

TL;DR

This paper presents a large-scale computational study of 8,712 MAX phases using density functional theory to facilitate the discovery and design of new MXene materials for various applications.

Contribution

It provides the first extensive dataset of MAX phase properties, enabling targeted synthesis and exploration of double transition metal MXenes.

Findings

Calculated energetics and structures for 8,712 MAX phases

Created an open, queryable database for materials research

Facilitates design of new MXenes with tailored properties

Abstract

MXenes are an emerging class of 2D materials of interest in applications ranging from energy storage to electromagnetic shielding. MXenes are synthesized by selective etching of layered bulk MAX phases into sheets of 2D MXenes. Their chemical tunability has been significantly expanded with the successful synthesis of double transition metal MXenes. While knowledge of the structure and energetics of double transition metal MAX phases is critical to designing and optimizing new MXenes, only a small subset of these materials been explored. We present a comprehensive dataset of key properties of MAX phases obtained using density functional theory within the generalized gradient approximation exchange-correlation functionals. Energetics and structure of 8,712 MAX phases have been calculated and stored in a queryable, open database hosted at nanoHUB.