Physics Guided Exponential Model Design of High Ge Content SiGe Selective Epitaxy for Gate All Around Source/Drain Applications
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arXiv
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| Autori principali: | , , , , , , , , , , , |
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| Natura: | Preprint |
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2026
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| _version_ | 1866918327496998912 |
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| author | Li, Zhigang Bai, Guobin Cui, Hengwei Yao, Wenlong Gao, Jianfeng Jiang, Qifeng Li, Junjie Li, Junfeng Li, Yongliang Yin, Huaxiang Wang, Xiaolei Luo, Jun |
| author_facet | Li, Zhigang Bai, Guobin Cui, Hengwei Yao, Wenlong Gao, Jianfeng Jiang, Qifeng Li, Junjie Li, Junfeng Li, Yongliang Yin, Huaxiang Wang, Xiaolei Luo, Jun |
| contents | High germanium content silicon germanium (SiGe) epitaxy is critical for strain engineering in advanced gate all around (GAA) transistors. This paper demonstrates a physics guided exponential function model that quantitatively links selective epitaxial growth (SEG) parameters to Ge incorporation kinetics in nanoscale trenches. By coupling surface diffusion limited transport, gradient strain, and competitive adsorption dynamics, the model predicts optimal conditions for bottom-up filling with maximal Ge content. For trenches with widths of approximately 60 nm, the optimized process achieved a maximum Ge content of 57.93% and demonstrated 100% selectivity against silicon nitride (SiN) and silicon dioxide (SiO). Cross sectional TEM and EDS analyses reveal a graded Ge profile that minimizes interfacial defects and strain energy. Our results show that the established process physics correlation will significantly facilitate the development of GAA devices with 5nm CMOS technology nodes and beyond. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_07925 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Physics Guided Exponential Model Design of High Ge Content SiGe Selective Epitaxy for Gate All Around Source/Drain Applications Li, Zhigang Bai, Guobin Cui, Hengwei Yao, Wenlong Gao, Jianfeng Jiang, Qifeng Li, Junjie Li, Junfeng Li, Yongliang Yin, Huaxiang Wang, Xiaolei Luo, Jun Applied Physics High germanium content silicon germanium (SiGe) epitaxy is critical for strain engineering in advanced gate all around (GAA) transistors. This paper demonstrates a physics guided exponential function model that quantitatively links selective epitaxial growth (SEG) parameters to Ge incorporation kinetics in nanoscale trenches. By coupling surface diffusion limited transport, gradient strain, and competitive adsorption dynamics, the model predicts optimal conditions for bottom-up filling with maximal Ge content. For trenches with widths of approximately 60 nm, the optimized process achieved a maximum Ge content of 57.93% and demonstrated 100% selectivity against silicon nitride (SiN) and silicon dioxide (SiO). Cross sectional TEM and EDS analyses reveal a graded Ge profile that minimizes interfacial defects and strain energy. Our results show that the established process physics correlation will significantly facilitate the development of GAA devices with 5nm CMOS technology nodes and beyond. |
| title | Physics Guided Exponential Model Design of High Ge Content SiGe Selective Epitaxy for Gate All Around Source/Drain Applications |
| topic | Applied Physics |
| url | https://arxiv.org/abs/2602.07925 |