Optimization of 16 nm DG-FinFET using L25 orthogonal array of Taguchi statistical method

Ameer F. Roslan, F. Salehuddin, A. S.M. Zain, K. E. Kaharudin, I. Ahmad

Research output: Contribution to journalArticle

Abstract

The impact of the optimization using Taguchi statistical method towards the electrical properties of a 16 nm double-gate FinFET (DG-FinFET) is investigated and analyzed. The inclusion of drive current (ION), leakage current (IOFF), and threshold voltage (VTH) as part of electrical properties presented in this paper will be determined by the amendment of six process parameters that comprises the polysilicon doping dose, polysilicon doping tilt, Source/Drain doping dose, Source/Drain doping tilt, VTH doping dose, VTH doping tilt, alongside the consideration of noise factor in gate oxidation temperature and polysilicon oxidation temperature. Silvaco TCAD software is utilized in this experiment with the employment of both ATHENA and ATLAS module to perform the respective device simulation and the electrical characterization of the device. The output responses obtained from the design is then succeeded by the implementation of Taguchi statistical method to facilitate the process parameter optimization as well as its design. The effectiveness of the process parameter is opted through the factor effect percentage on Signal-to-noise ratio with considerations towards ION and IOFF. The most dominant factor procured is the polysilicon doping tilt. The ION and IOFF obtained after the optimization are 1726.88 μA/μm and 503.41 pA/μm for which has met the predictions of International Technology Roadmap for Semiconductors (ITRS) 2013.

Original languageEnglish
Pages (from-to)1207-1214
Number of pages8
JournalIndonesian Journal of Electrical Engineering and Computer Science
Volume18
Issue number3
DOIs
Publication statusPublished - 01 Jan 2020

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Networks and Communications
  • Control and Optimization
  • Electrical and Electronic Engineering

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