Drift-Diffusion Versus Monte Carlo Simulated ON-Current Variability in Nanowire FETs

TítuloDrift-Diffusion Versus Monte Carlo Simulated ON-Current Variability in Nanowire FETs
AutoresNagy D., Indalecio G., García-Loureiro A., Espiñeira G., Elmessary M., Kalna K., Seoane N.
TipoArtículo de revista
Fonte IEEE Access, IEEE, Vol. 7, pp. 12790-12797 , 2019.
RankProvisionally ranked Q1 in Computer Science (all) by SJR 2018
ISSN2169-3536
DOI10.1109/ACCESS.2019.2892592
Abstract© 2013 IEEE. Variability of semiconductor devices is seriously limiting their performance at nanoscale. The impact of variability can be accurately and effectively predicted by computer-aided simulations in order to aid future device designs. Quantum corrected (QC) drift-diffusion (DD) simulations are usually employed to estimate the variability of state-of-the-art non-planar devices but require meticulous calibration. More accurate simulation methods, such as QC Monte Carlo (MC), are considered time consuming and elaborate. Therefore, we predict TiN metal gate work-function granularity (MGG) and line edge roughness (LER) induced variability on a 10-nm gate length gate-all-around Si nanowire FET and perform a rigorous comparison of the QC DD and MC results. In case of the MGG, we have found that the QC DD predicted variability can have a difference of up to 20% in comparison with the QC MC predicted one. In case of the LER, we demonstrate that the QC DD can overestimate the QC MC simulation produced variability by a significant error of up to 56%. This error between the simulation methods will vary with the root mean square (RMS) height and maximum source/drain n -type doping. Our results indicate that the aforementioned QC DD simulation technique yields inaccurate results for the ON-current variability.
Palabras chaveDrift-diffusion, line edge roughness, metal gate granularity, Monte Carlo, nanowire FET, quantum corrections