This document summarizes research into using density functional theory to discover new low-dimensional and topologically non-trivial materials. Key aspects include screening over 600 2D materials and 30,000 3D bulk materials to identify promising candidates, calculating exfoliation energies to confirm stability of low-dimensional forms, and using a spillage criterion to identify over 1,800 potential topological materials by comparing wavefunctions with and without spin-orbit coupling. Ongoing work focuses on characterizing elemental contributions to topological materials and identifying other classes of topological phases like Weyl and Dirac semimetals.

1. High-throughput discovery of low-dimensional and topologically non-trivial
materials
Publications
▪ “High-throughput Identification and Characterization of Two-dimensional
Materials using Density functional theory,” Scientific Reports 7, 5179 (2017).
▪ “Computational screening of high-performance optoelectronic materials
using OptB88vdW and TBmBJ formalisms “, accepted Scientific Data (2018).
▪ “Elastic properties of bulk and low-dimensional materials using van der
Waals density functional”, Physical Review B 98 (1), 014107 (2018).
▪ “High-throughput discovery of topological materials using spin-orbit
spillage”, https://arxiv.org/abs/1810.10640
MML/MSED
Motivation
• Accelerated discovery of technologically interesting
materials using density functional theory, especially
2D and Topologically non-trivial materials
• Final computational confirmation with exfoliation
energy calculations: difference in energy per atom
of bulk and monolayer systems (Ef<200 meV/atom)
• 637 exfoliation energies data, 89% success
• Easy web-page integration and screening
• 2D-monolayer topological materials search
• Extending spillage criteria to magnetic materials
• Identifying Chern-insulators
Dimensionality of materials
• vdW bonding in zero, one, two, and three dimensions
imply 3D-bulk, 2D-bulk, 1D-bulk and 0D-bulk solids
• ~ 600 2D monolayer & 30000 3D bulk materials
• Lattice constant criteria and data-mining approaches
Low-dimensional topological
materials
Screening topologically non-trivial mats.
Exfoliation energy calculations
Screening low-dimensional materials
• Lattice constant approach (if error in lattice parameter
>5% in one, two, three crystallographic directions,
then the material is predicted to be 2D, 1D and 0D
• Using ICSD and materials-project data
• 1514 (2D), 1575 (1D) and 792 (0D) materials predicted
• Combining data-mining approaches
• Compare wavefunctions from SOC/NSOC calculations
• Spillage ( 𝜂)>0.5 for 1868 materials out of 4835
• Physical significance: band-inverted electrons
SOC properties of topological mats.
• Spillage related material property distributions
Wannier-calculations
• Verification of Spillage criteria using conventional
Wannier-calculations
• Spillage method is a much faster tool
• Identifying low-dimensional topological materials
• Most of the topological materials are 3D-bulk, but
~8 % low-dimensional
Ongoing work
bulk
bulk
L
L
f
N
E
N
E
E −=
1
1
𝜂 𝐤 = 𝑛 𝑜𝑐𝑐(𝐤) − Tr 𝑃 ෨𝑃
𝑃 𝐤 = ෍
𝑛=1
)𝑛 𝑜𝑐𝑐(𝐤
ۧ|𝜓 𝑛𝐤 ൻ𝜓 𝑛𝐤|
Elemental contributions for
high-spillage materials
• Based on probability of finding an element in a
material, which has high-spillage
Topological insulator
PbS LiBiS2 KHgAs GaSb
K. Choudhary1, K. Garrity1, I. Kalish1, R. Beams1, G. Cheon2, E. Reed2, F. Tavazza1
1Materials Science and Engineering Division, National Institute of Standards and Technology, MD, USA
2Department of Materials Science and Engineering, Stanford University, Stanford, California, USA
Other classes of topological materials
Weyl semi-metal Dirac semi-metal Crystalline topological insulator
JARVIS-websites
• Homepage: https://jarvis.nist.gov
• DFT page:
https://www.ctcms.nist.gov/~knc6/JVASP.html