Computational prediction and characterization of two-dimensional pentagonal arsenopyrite FeAsS

Research output: Contribution to journalArticle

Abstract

Two-dimensional (2D)pentagonal materials emerge as a new group of 2D materials with pentagonal rather than the more common hexagonal structure. Most of the existing and predicted 2D pentagonal materials are binary compounds, whereas adding more elements is likely to bring in extra properties. We apply a datamining process in the Materials Project to search for 3D ternary compounds, where one can derive 2D materials with pentagonal structure. We identify 34 ternary compounds that exhibit negative formation energies. We focus on one of these compounds, FeAsS, and we find that its single-layer counterpart exhibits an almost completely planar structure with dynamically stable phonon modes. This single-layer material is also a semiconductor with the antiferromagnetic (AFM)ordering. We also find that the Fe-As-Fe and Fe-S-Fe exchange couplings are of antiferromagnetic and ferromagnetic types, respectively, and the former exchange coupling strength is significantly stronger, leading to the AFM ordering. Finally, we account for the spin-orbit coupling (SOC)in the computational characterization. We find strong magnetocrystalline anisotropy as a result of the SOC. We further compute the Berry curvature for single-layer pentagonal FeAsS and find that at the Y point of the reciprocal space, the Berry curvature is both sizable and asymmetric. We expect more theoretical efforts to be spent towards designing 2D ternary pentagonal materials as a result of this work.

Original languageEnglish (US)
Pages (from-to)105-110
Number of pages6
JournalComputational Materials Science
Volume166
DOIs
StatePublished - Aug 1 2019
Externally publishedYes

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Prediction
predictions
Ternary
Spin-orbit Coupling
curvature
Exchange coupling
orbits
planar structures
energy of formation
Orbits
Curvature
Magnetocrystalline anisotropy
anisotropy
Phonon
arsenopyrite
Hexagon
Anisotropy
Semiconductors
Data Mining
Likely

Keywords

  • Datamining
  • Magnetism
  • Pentagonal geometries
  • Two-dimensional materials

ASJC Scopus subject areas

  • Computer Science(all)
  • Chemistry(all)
  • Materials Science(all)
  • Mechanics of Materials
  • Physics and Astronomy(all)
  • Computational Mathematics

Cite this

Computational prediction and characterization of two-dimensional pentagonal arsenopyrite FeAsS. / Liu, Lei; Zhuang, Houlong.

In: Computational Materials Science, Vol. 166, 01.08.2019, p. 105-110.

Research output: Contribution to journalArticle

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