Limits of performance gain of aligned CNT over randomized network: Theoretical predictions and experimental validation

Ninad Pimparkar, Coskun Kocabas, Seong Jun Kang, John A Rogers, Muhammad Ashraful Alam

Research output: Contribution to journalArticle

Abstract

Nanobundle thin-film transistors (NB-TFTs) that are based on random networks of single-walled carbon nanotubes are often regarded as high performance alternative to amorphous-Si technology for various macroelectronic applications involving sensors and displays. Here, we use stick-percolation model to study the effect of collective (stick) alignment on the performance of NB-TFTs. For long-channel TFT, small degree of alignment improves the drain current due to the reduction of average path length; however, near-parallel alignment degrades the current rapidly, reflecting the decrease in the number of connecting paths bridging the source/drain. In this paper, we 1) use a recently developed alignment technique to fabricate NB-TFT devices with multiple densities D, alignment θ, stick length LS, and channel length LC; 2) interpret the experimental data with a stick-percolation model to develop a comprehensive theory of NB-TFT for arbitrary D, θ, LS, and LC; and 3) demonstrate theoretically and experimentally the feasibility of fivefold enhancement in current gain with optimized transistor structure.

Original languageEnglish (US)
Pages (from-to)593-595
Number of pages3
JournalIEEE Electron Device Letters
Volume28
Issue number7
DOIs
StatePublished - Jul 1 2007

Keywords

  • Aligned carbon nanotube (CNT) networks
  • Percolation threshold
  • Random CNT networks
  • Stick percolation
  • Thin-film transistors (TFTs)
  • Transistor models

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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