skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Computational Search for Strong Topological Insulators: An Exercise in Data Mining and Electronic Structure

Journal Article · · Applied Physics Research
DOI:https://doi.org/10.5539/apr.v6n4p31· OSTI ID:1321732
 [1];  [2];  [3]
  1. Uppsala Univ. (Sweden)
  2. James Madison Univ., Harrisonburg, VA (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States); NORDITA, Stockholm (Sweden)
+ Show Author Affiliations

In this paper, we report a data-mining investigation for the search of topological insulators by examining individual electronic structures for over 60,000 materials. Using a data-mining algorithm, we survey changes in band inversion with and without spin-orbit coupling by screening the calculated electronic band structure for a small gap and a change concavity at high-symmetry points. Overall, we were able to identify a number of topological candidates with varying structures and composition. Lastly, our overall goal is expand the realm of predictive theory into the determination of new and exotic complex materials through the data mining of electronic structure.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
Grant/Contract Number:
AC52-06NA25396
OSTI ID:
1321732
Report Number(s):
LA-UR-13-25985
Journal Information:
Applied Physics Research, Vol. 6, Issue 4; ISSN 1916-9639
Publisher:
Canadian Center of Science and EducationCopyright Statement
Country of Publication:
United States
Language:
English

Cited By (12)

Materials Informatics for Dark Matter Detection journal September 2018
Online search tool for graphical patterns in electronic band structures journal August 2018
From DFT to machine learning: recent approaches to materials science–a review journal May 2019
Three-dimensional organic Dirac-line materials due to nonsymmorphic symmetry: A data mining approach journal January 2017
Computational search for Dirac and Weyl nodes in f -electron antiperovskites journal May 2019
Evolution of band topology by competing band overlap and spin-orbit coupling: Twin Dirac cones in Ba 3 SnO as a prototype journal November 2017
Towards novel organic high- T c superconductors: Data mining using density of states similarity search journal February 2018
Organic materials database: An open-access online database for data mining journal February 2017
Organic materials database: An open-access online database for data mining text January 2017
Three-dimensional organic Dirac-line materials due to nonsymmorphic symmetry: a data mining approach text January 2016
Computational search for Dirac and Weyl nodes in $f$-electon antiperovskites text January 2019
Materials Informatics for Dark Matter Detection text January 2018

Similar Records

Site Mixing for Engineering Magnetic Topological Insulators
Journal Article · Wed May 12 00:00:00 EDT 2021 · Physical Review. X · OSTI ID:1321732
+9 more
Magneto-transport evidence for strong topological insulator phase in ZrTe5
Journal Article · Fri Nov 19 00:00:00 EST 2021 · Nature Communications · OSTI ID:1321732
+8 more
Controllable topological insulator phases in litharge-phase InBi monolayer
Journal Article · Mon Jul 17 00:00:00 EDT 2023 · Physical Review Materials · OSTI ID:1321732

Related Subjects

36 MATERIALS SCIENCE
97 MATHEMATICS AND COMPUTING
electronic structure
data mining
topological insulators
predictive theory