Statistics Based Modeling and Analysis of Ultra-Low Impedance Carbon Nanotube MOS Capacitors

We report the first direct extraction of CNT MOS interface metrics normalized to CNT length or CNT surface area using statistical impedance modeling and analysis of lateral capacitors measured between 100 and 300 K. Direct $D_{\text{it}}$ extraction from impedance is a crucial step towards high performance CNT MOSFETs and is enabled by (1) a statistical approach towards modeling of CNT impedance, (2) a capacitor architecture meeting the requirements for $D_{\text{it}}$ extraction, and (3) the extension of impedance acquisition to below 1 $\text{fF}$. A rigorous model treatment of surface potential fluctuations $\Delta\psi_{\mathrm{s}}$ in depletion due to fixed charge and CNT diameter variations allows to reproduce C-V features, to elucidate the physics, and to reconcile SS obtained from I-V curves with impedance data by extending the standard SS equation. CNT midgap $D_{\text{it}}$ normalized to CNT surface area of $\cong 7\times 10^{12}\text{cm}^{-2}\text{eV}^{-1}$ and increasing towards the band edge to above $5\times 10^{13}\text{cm}^{-2}\text{eV}^{-\mathrm{I}},\psi_{\mathrm{S}}$ standard deviation $\sigma_{\mathrm{s}}\cong 2.5\text{kT}$, and a midgap capture length of 0.01 nm are extracted. Preliminary process optimizations demonstrate a positive impact on the $D_{\text{it}}$ vs $E$ curve.