Optimization of deconvoluted parameter for the quantification of high-resolution SIMS depth profiles

• Published in: Vacuum Vol. 215; p. 112342
• Main Authors: Li, T.T., Zhuang, X.M., Li, H.M., Xu, Y.X., Ma, Z.Q., Zheng, J.Q., Geng, Y.Q., Wang, C.L., Lian, S.Y., Wang, J.Y., Xu, C.K.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.09.2023
• Subjects: Deconvolution; High-resolution depth profiling; MRI model; One-dimensional search algorithm; Quantitative analysis; TV-Tikhonov algorithm; One-dimensional search algorithm; Deconvolution; High-resolution depth profiling; TV-Tikhonov algorithm; MRI model; Quantitative analysis
• ISSN: 0042-207X; 1879-2715
• DOI: 10.1016/j.vacuum.2023.112342

It is demonstrated in this paper that the searching step τ in the TV-Tikhonov algorithm plays an important role for determining the original layer structure directly from measured high-resolution depth profiling data. The optimization of τ is very necessary for obtaining a reliable deconvoluted result. Considering a large increase of simulated data points by decreasing the depth interval for quantification of high-resolution depth profiling data, the optimization of τ is performed simply by one-dimensional search algorithm. Furthermore, the noise effects from “measured” depth profiling data on the deconvoluted profile with different optimal τ values are also quantitatively evaluated. Finally, as examples, the measured SIMS depth profiling data of the two In nano-layers embedded in InGaAs thin films and the 28Si/30Si isotope nano-superlattices are deconvoluted directly and the respective original layer structures are obtained accordingly. •A method for deconvolution of measured high-resolution depth profiling data is proposed.•The optimization of searching step τ in the method is very necessary and is performed by one-dimensional search algorithm.•The noise effects on the deconvoluted profile with different optimal τvalues are quantitatively evaluated.•The original layer structures of In nano-layers and Si isotope nano-superlattices are obtained by the developed method.