Scanning Electron Microscopy Dopant Contrast Imaging of Phosphorus-Diffused Silicon

Phosphorous dopant diffusion profiles feature in many silicon semiconductor devices, including the vast majority of silicon solar cells. Accurate spatially resolved dopant profiling is crucial for understanding the performance of these diffused regions, however, it is very challenging to obtain such profiles in non-planar samples. Scanning electron microscopy for dopant contrast imaging (SEMDCI), where the secondary electron (SE) image contrast is used to determine the dopant level of a semiconductor sample, is an ideal candidate for Si dopant profiling, especially for silicon samples with surface nanotexturing or black silicon (BSi) technology. However, in previous SEMDCI studies, the dopant concentration of heavily doped n-type layers in silicon samples have shown a poor correlation with the SE signal contrast. In this work, 1) good contrast for n-type diffused silicon without contrast-enhancing techniques; 2) a new contrast definition to account for imaging non-uniformities; 3) clear correlations between SE contrast and sample work function for phosphorus-diffused planar silicon specimens across a wide range of emitter profiles; 4) implementation of an empirical baseline correction to normalize scanning electron microscopy image condition variations, are presented. This SEMDCI method is subsequently used for the first time to obtain 2D electron concentration maps for both planar and BSi samples.

Automated summary

Phosphorous dopant diffusion profiles are important in many silicon semiconductor devices, and accurate spatially resolved dopant profiling is crucial for understanding their performance. The scanning electron microscopy for dopant contrast imaging (SEMDCI) method is effective in obtaining these profiles, especially for silicon samples with surface nanotexturing or black silicon (BSi) technology. However, previous studies have shown a poor correlation between the dopant concentration and the secondary electron (SE) signal contrast. This work presents improvements in contrast, correlation, and image condition normalization, and applies the SEMDCI method for the first time to obtain 2D electron concentration maps for planar and BSi samples.