NanoNET is a tool to simulate the Nanobundle Network Thin Film Transistors (NB-TFTs). Random networks of carbon nanotubes with thousands of tubes and random orientation can be simulated using this tool. The final answer can be compactly formulated in the formula shown in the picture. Here ID is current and LC and LS is channel length and tube length of the transistor and m is the current exponent.

For a normal Si MOSFET, m = 1 and the current is simply inversely proportional to channel length. But for these nanotube networks, m > 1 is also possible. Indeed, m = 1 for very high density networks but the value of m increases with decreasing tube density of the network

This abnormal behavior can be simply understood as follows:

When the density of tubes is very high, most of the tubes take part in conduction and the current simply doubles on halving the channel length. But for a lower density network, there are some islands of pools of nanotubes that are not taking part in the conduction which start to connect as channel length is reduced. So not only the average path length reduces, but the number of paths also goes up with decreasing channel length which causes this super-linear increase in the current with channel length or m > 1.

The smaller the density, the more pronounced is this effect and higher is the m.

This work was supported by Network for Computational Nanotechnology (NCN) and Lilly Foundation.

• C. Kocabas, N. Pimparkar, M. A. Alam, and J. A. Rogers,“ Experimental and Theoretical Studies of Transport Through Large Scale, Partially Aligned Arrays of Single Walled Carbon Nanotubes in Thin Film Type Transistors,” Nano Letters, advanced online (2007). (C. Kocabas, N. Pimparkar have equal contribution to this paper)
• Seong Jun Kang, Coskun Kocabas, Taner Ozel, Moonsub Shim, N. Pimparkar, Ashraf Alam, Slava Rotkin and John A. Rogers, “High Performance Electronics Based on Dense, Perfectly Aligned Arrays of Single Walled Carbon Nanotubes”, Nature Nanotechnology, 2, 230-236 (2007)
• N. Pimparkar, C. Kocabas, S. J. Kang, J. Rogers and M. A. Alam,“ Limits of Performance Gain of Aligned CNT over Randomized Network: Theoretical Predictions and Experimental Validation,” Electron Device Letters (In Press).
• N. Pimparkar, J. Guo, and M. A. Alam,“Performance Assessment of Sub-Percolating Nanobundle Network Transistors by an Analytical Model,” IEEE Transactions of Electron Devices (April 2007).
• N. Pimparkar, S. Kumar, J. Y. Murthy, and M. A. Alam,“ Current-Voltage Characteristics of Long-Channel Nanobundle Thin-Film Transistors: A 'Bottom-up' Perspective,” Electron Device Letters (Feb 2007).
• M. A. Alam, N. Pimparkar, S. Kumar, and J. Y. Murthy, “ Theory of Nanocomposite Network Transistors for Macroelectronics Applications ,” MRS Bulletin: Macroelectronics, June 2006. (Invited)
• S. Kumar, N. Pimparkar, J. Y. Murthy, and M. A. Alam,“ Theory of Transfer Characteristics of Nanotube Network Transistors,” Applied Physics Letters, 88, 2006.

If you reference this work in a publication, please cite as follows:

• C. Kocabas, N. Pimparkar, M. A. Alam, and J. A. Rogers,“ Experimental and Theoretical Studies of Transport Through Large Scale, Partially Aligned Arrays of Single Walled Carbon Nanotubes in Thin Film Type Transistors,” Nano Letters, advanced online (2007). (C. Kocabas, N. Pimparkar have equal contribution to this paper)

• N. Pimparkar, C. Kocabas, S. J. Kang, J. Rogers and M. A. Alam,“ Limits of Performance Gain of Aligned CNT over Randomized Network: Theoretical Predictions and Experimental Validation,” Electron Device Letters (In Press).

• Pimparkar, Ninad; Kumar, Satish; Murthy, Jayathi; Alam, Muhammad A. (2007), "NanoNet," doi: 10254/nanohub-r2262.2.

  BibTex | EndNote

In addition, we would appreciate it if you would add the following acknowledgment to your publication:

• Simulation services for results presented here were provided by the Network for Computational Nanotechnology (NCN) at nanoHUB.org

1. carbon nanotubes
2. characterization
3. nano-transistors
4. nanoelectronics