Static and low frequency noise characterization of N-type random network of carbon nanotubes thin film transistors

Min Kyu Joo; Mireille Mouis; Dae Young Jeon; Gyu Tae Kim; Un Jeong Kim; Gérard Ghibaudo

doi:10.1063/1.4825221

Static and low frequency noise characterization of N-type random network of carbon nanotubes thin film transistors

Min Kyu Joo, Mireille Mouis, Dae Young Jeon, Gyu Tae Kim, Un Jeong Kim, Gérard Ghibaudo

Research output: Contribution to journal › Article › peer-review

11 Citations (Scopus)

Abstract

Static and low frequency noise (LFN) characterizations in two-dimensional (2D) N-type random network thin film transistors (RN-TFTs) based on single-walled carbon nanotubes were presented. For the electrical parameter extraction, the Y-function method was used to suppress the series resistance (R_sd) influence. The gate-to-channel capacitance (C_gc) was directly measured by the split capacitance-to-voltage method and compared to 2D metal-plate capacitance model (C_2D). In addition, to account for the percolation-dominated 2D RN-TFTs, a numerical percolation simulation was performed. LFN measurements were also carried out and the results were well interpreted by the carrier number and correlated mobility fluctuation model. Finally, one-dimensional (1D) cylindrical analytical capacitance based model (C_1D) was suggested and applied to provide better consistency between all electrical parameters based on experimental and simulation results.

Original language	English
Article number	154503
Journal	Journal of Applied Physics
Volume	114
Issue number	15
DOIs	https://doi.org/10.1063/1.4825221
Publication status	Published - 2013 Oct 21

ASJC Scopus subject areas

Physics and Astronomy(all)

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10.1063/1.4825221

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@article{baf91aa874034bd4a56f62579c53efde,

title = "Static and low frequency noise characterization of N-type random network of carbon nanotubes thin film transistors",

abstract = "Static and low frequency noise (LFN) characterizations in two-dimensional (2D) N-type random network thin film transistors (RN-TFTs) based on single-walled carbon nanotubes were presented. For the electrical parameter extraction, the Y-function method was used to suppress the series resistance (Rsd) influence. The gate-to-channel capacitance (Cgc) was directly measured by the split capacitance-to-voltage method and compared to 2D metal-plate capacitance model (C2D). In addition, to account for the percolation-dominated 2D RN-TFTs, a numerical percolation simulation was performed. LFN measurements were also carried out and the results were well interpreted by the carrier number and correlated mobility fluctuation model. Finally, one-dimensional (1D) cylindrical analytical capacitance based model (C1D) was suggested and applied to provide better consistency between all electrical parameters based on experimental and simulation results.",

author = "Joo, {Min Kyu} and Mireille Mouis and Jeon, {Dae Young} and Kim, {Gyu Tae} and Kim, {Un Jeong} and G{\'e}rard Ghibaudo",

note = "Funding Information: This research was financially supported by Converging Research Center Program through the Ministry of Science, ICT and Future Planning, Korea (2013K000175). It has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement NANOFUNCTION n°257375.",

year = "2013",

month = oct,

day = "21",

doi = "10.1063/1.4825221",

language = "English",

volume = "114",

journal = "Journal of Applied Physics",

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T1 - Static and low frequency noise characterization of N-type random network of carbon nanotubes thin film transistors

AU - Joo, Min Kyu

AU - Mouis, Mireille

AU - Jeon, Dae Young

AU - Kim, Gyu Tae

AU - Kim, Un Jeong

AU - Ghibaudo, Gérard

N1 - Funding Information: This research was financially supported by Converging Research Center Program through the Ministry of Science, ICT and Future Planning, Korea (2013K000175). It has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement NANOFUNCTION n°257375.

PY - 2013/10/21

Y1 - 2013/10/21

N2 - Static and low frequency noise (LFN) characterizations in two-dimensional (2D) N-type random network thin film transistors (RN-TFTs) based on single-walled carbon nanotubes were presented. For the electrical parameter extraction, the Y-function method was used to suppress the series resistance (Rsd) influence. The gate-to-channel capacitance (Cgc) was directly measured by the split capacitance-to-voltage method and compared to 2D metal-plate capacitance model (C2D). In addition, to account for the percolation-dominated 2D RN-TFTs, a numerical percolation simulation was performed. LFN measurements were also carried out and the results were well interpreted by the carrier number and correlated mobility fluctuation model. Finally, one-dimensional (1D) cylindrical analytical capacitance based model (C1D) was suggested and applied to provide better consistency between all electrical parameters based on experimental and simulation results.

AB - Static and low frequency noise (LFN) characterizations in two-dimensional (2D) N-type random network thin film transistors (RN-TFTs) based on single-walled carbon nanotubes were presented. For the electrical parameter extraction, the Y-function method was used to suppress the series resistance (Rsd) influence. The gate-to-channel capacitance (Cgc) was directly measured by the split capacitance-to-voltage method and compared to 2D metal-plate capacitance model (C2D). In addition, to account for the percolation-dominated 2D RN-TFTs, a numerical percolation simulation was performed. LFN measurements were also carried out and the results were well interpreted by the carrier number and correlated mobility fluctuation model. Finally, one-dimensional (1D) cylindrical analytical capacitance based model (C1D) was suggested and applied to provide better consistency between all electrical parameters based on experimental and simulation results.

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VL - 114

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JF - Journal of Applied Physics

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M1 - 154503

ER -

Static and low frequency noise characterization of N-type random network of carbon nanotubes thin film transistors

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