Fermi-Level Tuning of G-Doped Layers
Avto Tavkhelidze1, Amiran Bibilashvili2, Larissa Jangidze1,2
1Center of Nanotechnology for Renewable Energy, Ilia State University, Cholokashvili Ave. 3-5, Tbilisi, GA 0162, USA.
Nanomaterials (Basel, Switzerland)
|March 6, 2021
Summary
Geometry-induced doping in silicon nanogratings (NG) tunes the Fermi level. Optimal doping occurs at 10 nm NG depth, with effects varying by silicon substrate type and decreasing with greater depths.
Area of Science:
- Semiconductor physics
- Materials science
- Nanotechnology
Background:
- Periodic nanostructures exhibit geometry-induced quantum effects.
- Nanograting (NG) geometry influences electronic, magnetic, and optical properties of semiconductors.
- Silicon NG layers demonstrate geometry-induced doping, a phenomenon termed G-doping.
Purpose of the Study:
- Investigate Fermi-level tuning in G-doped silicon layers by varying nanograting depth.
- Fabricate and characterize G-doped silicon junctions.
- Analyze the impact of nanograting geometry on G-doping efficiency.
Main Methods:
- Fabrication of silicon samples with nanogratings of varying depths (10, 20, 30, 40 nm) using laser interference lithography and reactive ion etching.
- Utilized Kelvin probe microscopy to map work function and determine Fermi level.
- Tested on p-, n-, p+, and n+ type silicon substrates.
Main Results:
- Observed a significant Fermi-level increase in G-doped silicon, with the maximum effect at a 10 nm nanograting depth.
- Fermi-level increase diminished with increasing nanograting depth, particularly in p-type substrates.
- Negligible Fermi-level shifts were recorded in heavily doped n+ and p+ silicon substrates.
Conclusions:
- Demonstrated effective Fermi-level tuning in silicon via geometry-induced doping (G-doping) through nanograting fabrication.
- The nanograting depth is a critical parameter for controlling G-doping efficiency.
- Results align with established G-doping theory and provide insights into nanostructure-based semiconductor property modulation.
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