Published in

American Institute of Physics, Journal of Vacuum Science and Technology B, 2(41), p. 024003, 2023

DOI: 10.1116/6.0002302

Links

Tools

Export citation

Search in Google Scholar

Restoration of the original depth distribution from experimental SIMS profile using the depth resolution function in framework of RMR model

Journal article published in 2023 by Y.-U. Kudriavtsev ORCID, R. Asomoza ORCID, K. D. Moiseev ORCID
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

Full text: Unavailable

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Orange circle
Published version: archiving restricted
Data provided by SHERPA/RoMEO

Abstract

In this paper, the problem of depth profiling analysis of nanoscale heterostructures containing doped delta layers and quantum wells using the SIMS method is considered. Based on computer simulation data and previously obtained experimental data, we demonstrated that the RMR model most accurately and completely describes the redistribution of the analyzed element in ultrathin layers that occurs during ion sputtering. A comparative analysis of the surface roughness–ion mixing–recoil implantation (RMR) model with MRI (mixing-roughness-information depth) and UDS (up-and-down slope) models proposed by Hoffman and Dowsett, respectively, was performed. It was shown that the introduction into the MRI model of a parameter describing some layer of constant thickness, in which the components of the analyzed layer and matrix elements are uniformly mixed, is not quite justified. It is concluded that during depth profiling of a monoatomic layer, the center of mass of this layer shifts away from the surface, as predicted by the RMR model, rather than toward the surface, as predicted by the MRI model. It is found that preferential sputtering does not affect the experimental depth distribution of elements obtained by the SIMS method.