Data-driven Discovery of New Two- and One-dimensional Materials and Lattice-commensurate Heterostructures

ORAL

Abstract

We employ data-driven methods to discover new two- and one-dimensional materials. Layered materials have attracted interest for technological applications and fundamental physics. But only a few van der Waals solids have been subject to considerable research focus. Through data mining, we identify 1173 two-dimensional layered materials and 487 weakly bonded one-dimensional molecular chains. This is an order of magnitude increase in the number of known materials. Moreover, we discover 98 heterostructures of two-dimensional and one-dimensional subcomponents that are found within bulk materials, opening new possibilities for van der Waals heterostructures.
To identify these materials, we present a novel data mining algorithm that determines the dimensionality of weakly bonded subcomponents. Chemical families, band gaps, and point groups and single-layer piezoelectricity of the materials identified with data mining are presented. Moreover, we expand on this work to new material compositions that can form layered materials.

*Supported by Army Research Office W911NF-15-1-0570, Office of Naval Research N00014-15-1-2697, U.S. Army Research Laboratory W911NF-07-0027, NSF Grant DMR-1455050 & EECS-1436626, Stanford Graduate Fellowship

Presenters

  • Gowoon Cheon

    • Stanford University
    • Stanford Univ

Authors

  • Gowoon Cheon

    • Stanford University
    • Stanford Univ
  • Karel-Alexander N. Duerloo

    • Boston Consulting Group
    • Stanford Univ
  • Austin Sendek

    • Stanford University
    • Stanford Univ
  • Chase Porter

    • Stanford University
  • Yuan Chen

    • Department of Applied Physics, Stanford University
    • Stanford University
  • Evan Reed

    • Stanford University
    • Stanford Univ
    • Materials Sciences and Engineering, Stanford