Tomographic layer-by-layer analysis of epitaxial iron-silicide nanostructures by DFT-assisted STS

Matan Dascalu, Oswaldo Diéguez, Liwei D. Geng, Ranjit Pati, Yongmei M. Jin, Ilan Goldfarb

Research output: Contribution to journalArticlepeer-review

Abstract

Surface science techniques (STM, STS, and XPS) were combined with ab initio simulations to detect the local crystal structure and chemistry. Solid phase epitaxy of iron on vicinal Si(111) substrate resulted in the formation of 3×3R30° nanoislands and (2×2) films of γ-FeSi2(111). We identify these structures by comparing experimental normalized derivative conductance curves with tomographic simulated local density of states (LDOS). The thermodynamic tendency of γ-FeSi2(111) towards Si rich surfaces is manifested in Si rich termination layers and reconstructions. We show that a weighted average of the LDOS from the Fe layer and the reconstruction layer can explain the main states in the normalized derivative conductance curves, enabling in-situ identification of crystal structure and composition of epitaxial deposits.

Original languageEnglish
Article number143583
JournalApplied Surface Science
Volume496
DOIs
StatePublished - 1 Dec 2019

Keywords

  • Density functional theory
  • Density of states
  • Epitaxial growth
  • Scanning tunneling microscopy and spectroscopy
  • Self-assembled nanostructures

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