Simulation and Modeling of Novel Electronic Device Architectures with NESS (Nano-Electronic Simulation Software): A Modular Nano TCAD Simulation Framework.

The modeling of nano-electronic devices is a cost-effective approach for optimizing the semiconductor device performance and for guiding the fabrication technology. In this paper, we present the capabilities of the new flexible multi-scale nano TCAD simulation software called Nano-Electronic Simulation Software (NESS). NESS is designed to study the charge transport in contemporary and novel ultra-scaled semiconductor devices. In order to simulate the charge transport in such ultra-scaled devices with complex architectures and design, we have developed numerous simulation modules based on various simulation approaches. Currently, NESS contains a drift-diffusion, Kubo-Greenwood, and non-equilibrium Green's function (NEGF) modules. All modules are numerical solvers which are implemented in the C++ programming language, and all of them are linked and solved self-consistently with the Poisson equation. Here, we have deployed some of those modules to showcase the capabilities of NESS to simulate advanced nano-scale semiconductor devices. The devices simulated in this paper are chosen to represent the current state-of-the-art and future technologies where quantum mechanical effects play an important role. Our examples include ultra-scaled nanowire transistors, tunnel transistors, resonant tunneling diodes, and negative capacitance transistors. Our results show that NESS is a robust, fast, and reliable simulation platform which can accurately predict and describe the underlying physics in novel ultra-scaled electronic devices.

Variability Predictions for the Next Technology Generations of n-type SixGe1-x Nanowire MOSFETs.

Using a state-of-the-art quantum transport simulator based on the effective mass approximation, we have thoroughly studied the impact of variability on Si x Ge 1 - x channel gate-all-around nanowire metal-oxide-semiconductor field-effect transistors (NWFETs) associated with random discrete dopants, line edge roughness, and metal gate granularity. Performance predictions of NWFETs with different cross-sectional shapes such as square, circle, and ellipse are also investigated. For each NWFETs, the effective masses have carefully been extracted from s p 3 d 5 s ∗ tight-binding band structures. In total, we have generated 7200 transistor samples and performed approximately 10,000 quantum transport simulations. Our statistical analysis reveals that metal gate granularity is dominant among the variability sources considered in this work. Assuming the parameters of the variability sources are the same, we have found that there is no significant difference of variability between SiGe and Si channel NWFETs.