From predicting to correlating the bonding properties of iron sulfide phases

  • Jinjia Liu
  • , Aiju Xu
  • , Yu Meng
  • , Yurong He
  • , Pengju Ren
  • , Wen Ping Guo
  • , Qing Peng
  • , Yong Yang
  • , Haijun Jiao
  • , Yongwang Li
  • , Xiao Dong Wen*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Iron sulfides have emerged as a fascinating class of materials in electromagnetics and catalysis areas, which however are challenging in first-principles modeling because of the strongly-correlated interactions between Fe 3d and S 3p electrons. Here, we assess the performances of 14 density functionals on the structural, electronic, and magnetic properties of five iron sulfides. The PBE + U with U eff = 2.0 eV has the overall best performance. After evaluating functionals and obtaining reliable properties, our final goal is from predicting to correlating in order to do high throughput screening for the systems since the complex structures and phases of iron sulfides, to put it in another way, to hunting a reliable descriptor for predicting their properties. In the work, we demonstrate that the crystal orbital Hamilton population (COHP) and Bader charge of Fe atoms presents a good correlation with the empirical bond valence. Our results open a new avenue to effectively investigate phases and properties for various structures of iron sulfides. Indeed, the correlations between COHP/Bader charge and bond valence can be extended to other systems.

Original languageEnglish
Pages (from-to)99-107
Number of pages9
JournalComputational Materials Science
Volume164
DOIs
StatePublished - 15 Jun 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019 Elsevier B.V.

Keywords

  • Bond valence
  • Density functional theory
  • Iron sulfide
  • Strongly-correlated system

ASJC Scopus subject areas

  • General Computer Science
  • General Chemistry
  • General Materials Science
  • Mechanics of Materials
  • General Physics and Astronomy
  • Computational Mathematics

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