Variability Study of MWCNT Local Interconnects Considering Defects and Contact Resistances-Part II: Impact of Charge Transfer Doping
In this paper, the impact of charge transfer doping on the variability of multiwalled carbon nanotube (MWCNT) local interconnects is studied by experiments and simulations. We calculate the number of conducting channels of both metallic and semiconducting carbon nanotubes as a function of Fermi leve...
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Published in | IEEE transactions on electron devices Vol. 65; no. 11; pp. 4963 - 4970 |
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Main Authors | , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.11.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Institute of Electrical and Electronics Engineers |
Subjects | |
Online Access | Get full text |
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Summary: | In this paper, the impact of charge transfer doping on the variability of multiwalled carbon nanotube (MWCNT) local interconnects is studied by experiments and simulations. We calculate the number of conducting channels of both metallic and semiconducting carbon nanotubes as a function of Fermi level shift due to doping based on the calculation of transmission coefficients. By using the MWCNT compact model proposed in Part I of this paper, we study the charge transfer doping of MWCNTs employing Fermi level shift to reduce the performance variability due to changes in diameter, chirality, defects, and contact resistance. Simulation results show that charge transfer doping can significantly improve MWCNT interconnect performance and variability by increasing the number of conducting channels of shells and degenerating semiconducting shells to metallic shells. As a case study on an MWCNT of 11 nm outer diameter, when the Fermi level shifts to 0.1 eV, up to ~80% of performance and standard deviation improvements are observed. Furthermore, a good match between experimental data and simulation results is observed, demonstrating the effectiveness of doping, the validity of the MWCNT compact model and proposed simulation methodology. |
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ISSN: | 0018-9383 1557-9646 |
DOI: | 10.1109/TED.2018.2868424 |