Design of experiment for optimal SiGe-Si selectivity

Zhengning Li; Xing Ke; Jia Song; Fengmei Li; Shiliang Ji; Haiyang Zhang

doi:10.1117/12.2656866

1 May 2023 Design of experiment for optimal SiGe-Si selectivity

Zhengning Li, Xing Ke, Jia Song, Fengmei Li, Shiliang Ji, Haiyang Zhang

Proceedings Volume 12499, Advanced Etch Technology and Process Integration for Nanopatterning XII; 124990M (2023) https://doi.org/10.1117/12.2656866
Event: SPIE Advanced Lithography + Patterning, 2023, San Jose, California, United States

Conference Poster

Abstract

Etching selectivity is the most critical factor in etch process, in which it can reduce non-etching materials loss while removing target materials. Silicon-germanium (SiGe) and silicon etch characteristic are similar, so the method to distinguish them during etching is a popular research topic. CF4-based mixed gases were applied for the SiGe to Silicon offline etch selectivity study. In terms of DoE (Design of Experiment) method, 5 process parameters, like CF4 gas, O2 gas, RF (resonant frequency) power and chamber pressure, were chosen to compose process conditions for SiGe and Si control wafer test. Based on uniform design, 15-run U15(55) design conditions were tested, and then subset selection algorithms was applied in R software to establish linear regression function for the process parameters. The correlation chart and heating map showed that dry plasma energy control was strongly with pressure and power simultaneous tuning direction and helium gas flow had little effect on SiGe-Si selectivity, which offered the tuning suggestion for SiGe-Si selectivity improvement.

Citation Download Citation

Zhengning Li, Xing Ke, Jia Song, Fengmei Li, Shiliang Ji, and Haiyang Zhang "Design of experiment for optimal SiGe-Si selectivity", Proc. SPIE 12499, Advanced Etch Technology and Process Integration for Nanopatterning XII, 124990M (1 May 2023); https://doi.org/10.1117/12.2656866

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