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The electrical properties of polycrystalline graphene grown by chemical vapor deposition (CVD) are determined by grain-related parameters—average grain size, single-crystalline grain sheet resistance, and grain boundary (GB) resistivity. However, extracting these parameters still remains challenging because of the difficulty in observing graphene GBs and decoupling the grain sheet resistance and GB resistivity. In this work, we developed an electrical characterization method that can extract the average grain size, single-crystalline grain sheet resistance, and GB resistivity simultaneously. We observed that the material property, graphene sheet resistance, could depend on the device dimension and developed an analytical resistance model based on the cumulative distribution function of the gamma distribution, explaining the effect of the GB density and distribution in the graphene channel. We applied this model to CVD-grown monolayer graphene by characterizing transmission-line model patterns and simultaneously extracted the average grain size (~5.95 μm), single-crystalline grain sheet resistance (~321 Ω/sq), and GB resistivity (~18.16 kΩ-μm) of the CVD-graphene layer. The extracted values agreed well with those obtained from scanning electron microscopy images of ultraviolet/ozone-treated GBs and the electrical characterization of graphene devices with sub-micrometer channel lengths.
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Study of the evolution of the crystallographic texture and the grain boundary network of the microstructure during grain growth: Supplemental data
This dataset contain the results of 426 anisotropic grain growth simulations in 2D. Every microstructure was stored as an 800x800 label matrix, where the label in a given pixel indicates the grain orientation at that point from the accompanying list of initial orientations (represented as quaternions) assigned to each grain.
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- Award ID(s):
- 1654700
- PAR ID:
- 10533066
- Publisher / Repository:
- Mendeley Data
- Date Published:
- Subject(s) / Keyword(s):
- Materials Science Grain Growth
- Format(s):
- Medium: X
- Right(s):
- Creative Commons Attribution 4.0 International
- Sponsoring Org:
- National Science Foundation
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