RT Journal Article
T1 Drift-Diffusion Versus Monte Carlo Simulated ON-Current Variability in Nanowire FETs
A1 Nagy, Daniel
A1 Indalecio Fernández, Guillermo
A1 García Loureiro, Antonio Jesús
A1 Espiñeira Deus, Gabriel
A1 Elmessary, Muhammad A.
A1 Kalna, Karol
A1 Seoane Iglesias, Natalia
K1 Drift-diffusion
K1 Line edge roughness
K1 Metal gate granularity
K1 Monte Carlo
K1 Quantum corrections
K1 Nanowire FET
AB 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
PB IEEE
YR 2019
FD 2019
LK http://hdl.handle.net/10347/21967
UL http://hdl.handle.net/10347/21967
LA eng
NO This work was supported in part by the Spanish Government under Project TIN2013-41129-P and Project TIN2016-76373-P, in part byXunta de Galicia and FEDER funds under Grant GRC 2014/008, in part by the Consellería de Cultura, Educación e OrdenaciónUniversitaria (accreditation 2016-2019), under Grant ED431G/08, and in part by the Centro de Supercomputación de Galicia (CESGA) forthe computer resources provided. The work of G. Indalecio was supported by the Programa de Axudas á Etapa Posdoutoral da Xunta deGalicia under Grant 2017/077. The work of N. Seoane was supported by the RyC program of the Spanish Ministerio de Ciencia,Innovación y Universidades under Grant RYC-2017-23312
DS Minerva
RD 28 abr 2026