Modeling SWCNT bandgap and effective mass variation using a Monte Carlo approach

Karim El Shabrawy*, Koushik Maharatna, Darren Bagnall, Bashir M. Al-Hashimi

*Corresponding author for this work

Research output: Contribution to journalArticle

46 Citations (Scopus)

Abstract

Synthesizing single-walled carbon nanotubes (SWCNTs) with accurate structural control has been widely acknowledged as an exceedingly complex task culminating in the realization of CNT devices with uncertain electronic behavior. In this paper, we apply a statistical approach in predicting the SWCNT bandgap and effective mass variation for typical uncertainties associated with the geometrical structure. This is first carried out by proposing a simulation-efficient analytical model that evaluates the bandgap (Eg) of an isolated SWCNT with a specified diameter (d) and chirality (θ). Similarly, we develop an SWCNT effective mass model, which is applicable to CNTs of any chirality and diameters >1 nm. A Monte Carlo method is later adopted to simulate the bandgap and effective mass variation for a selection of structural parameter distributions. As a result, we establish analytical expressions that separately specify the bandgap and effective mass variability (Egσ, m*σ) with respect to the CNT mean diameter (dμ) and standard deviation (dσ). These expressions offer insight from a theoretical perspective on the optimization of diameter-related process parameters with the aim of suppressing bandgap and effective mass variation.

Original languageEnglish
Pages (from-to)184-193
Number of pages10
JournalIEEE Transactions on Nanotechnology
Volume9
Issue number2
DOIs
Publication statusPublished - Mar 2010
Externally publishedYes

Keywords

  • bandgap variation
  • carbon-nanotube (CNT) device models
  • effective mass variation
  • single-walled CNT (SWCNT)
  • third-nearest-neighbor tight-binding (TB) model

Fingerprint Dive into the research topics of 'Modeling SWCNT bandgap and effective mass variation using a Monte Carlo approach'. Together they form a unique fingerprint.

Cite this