[paper] Electron Mobility Distribution in FD-SOI MOSFETs

Nima Dehdashti Akhavan^a, Gilberto Antonio Umana-Membreno^a, Renjie Gu^a, Jarek Antoszewski^a, Lorenzo Faraone^a and Sorin Cristoloveanu^b

Electron mobility distribution in FD-SOI MOSFETs using a NEGF-Poisson approach

Solid-State Electronics; Available online 14 March 2022, 108283

DOI: 10.1016/j.sse.2022.108283

   
a The University of Western Australia, Crawley (AU)
b IMEP-LAHC, INP Minatec, Grenoble (F)

Abstract: Modern electronic devices consist of several semiconductor layers, where each layer exhibits a unique carrier transport properties that can be represented by a unique mobility characteristic. To date, the mobility spectrum analysis technique is the main approach that has been developed and applied to the analysis of conductivity mechanisms of multi-carrier semiconductor structures and devices. Currently, there are no theoretical calculations of the mobility distribution in semiconductor structures or devices and specifically in MOSFET devices. In this article, we present a theoretical study of the electron mobility distribution in planar fully-depleted silicon-on-insulator (FD-SOI) transistors employing quantum mechanical modelling. The simulation results indicate that electronic transport in the 10 nm thick Si channel layer at room-temperature is due to two distinct and well-defined electron species for channel length varying from 50 nm to 200 nm. The two electron mobility distributions provide clear evidence of sub-band modulated transport in 10-nm thick Si planar FD-SOI MOSFETs that are associated with primed and non-primed valleys of silicon. The potential of the top gate electrode has been modulated, and thus only the top channel inversion-layer electron population transport parameters have been investigated employing self-consistent non-equilibrium Green’s function (NEGF)–Poisson numerical calculations. The numerical framework presented can be used to interpret experimental results obtained by magnetic-field dependent geometrical magnetoresistance measurements and mobility spectrum analysis, and provides greater insight into electron mobility distributions in nanostructured FET devices.

Fig: Qinv is defined as the electron density per unit length at the maximum 

of the first subband (top of the barrier) often referred to as a “virtual source”

Acknowledgements: This work was supported by the Australian Research Council (DP170104555), the Horizon 2020 ASCENT EU project (Access to European Nanoelectronics Network – Project no. 654384), the Western Australian node of the Australian National Fabrication Facility (ANFF), and the Western Australian Government’s Department of Jobs, Tourism, Science and Innovation.