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

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. •γ-FeSi2 nanostructures were grown on Si(111) with (2 × 2) and 3×3R30° surfaces.•STS acquired DOS were interpreted by DFT simulations, to identify the grown structures.•The topmost (reconstruction) and third (iron) layers impact the acquired DOS the most.•Surface effects dominate the DOS in γ-FeSi2/Si(111) films with 30 layers or less.