Abstract
A precise understanding of the diffusion of metal atoms into thin semiconductor films during metal-induced crystallization (MIC) is difficult to be achieved, because the metal profiles do not follow standard Gaussian- or Error-distribution-based diffusion theory. In order to fit the abnormal metal profiles in poly-Ge films obtained by MIC, a new diffusion model consisting of two oppositely directed Error distribution functions is proposed and validated through a statistical estimation. In particular, we experimentally investigate the characteristics and metal profiles of the different thick poly-Ge films crystallized by MIC at various temperatures (250, 300, and 350°C) through atomic force microscopy (AFM), Raman spectroscopy, and secondary ion mass spectroscopy (SIMS) measurements.
Original language | English |
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Pages (from-to) | 12900-12903 |
Number of pages | 4 |
Journal | Journal of Nanoscience and Nanotechnology |
Volume | 16 |
Issue number | 12 |
DOIs | |
State | Published - 1 Dec 2016 |
Keywords
- Fitting method
- Germanium
- Metal profile
- MIC