A systematic approach to correlation analysis of in-line process parameters for process variation effect on electrical characteristic of 16-nm HKMG Bulk FinFET devices

Ping Hsun Su*, Yi-ming Li

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

This paper reports a systematic method to discover and optimize key fabrication in-line process of 16-nm high-κ metal gate bulk FinFET to improve device's performance and variability. The sensitivity analysis is utilized to prioritize key in-line process parameters which significantly boost device's performance and effectively reduce its variations. To extract hidden correlations among complex and a large number of in-line process parameters, data mining technique is applied to highlight and group-associated in-line process parameters. The source of variations of in-line process parameters in each group is revealed and the optimized solution is proposed to reduce its sensitivity to devices' fluctuation. Results show the dual gate-spacer, the source/drain (S/D) proximity, the S/D depth, and the S/D implant are grouped to the same cluster and significantly affect the threshold voltage (Vt,sat), the on-state current (Id,sat), and the off-state current (Id,off), but the key variation source of these parameters is the thickness of the dual gate-spacer. By replacing dual spacers with single spacers, the fluctuation of threshold voltage is 30% dropped.

Original languageEnglish
Article number7500068
Pages (from-to)209-216
Number of pages8
JournalIEEE Transactions on Semiconductor Manufacturing
Volume29
Issue number3
DOIs
StatePublished - Aug 2016

Keywords

  • bulk FinFETs
  • characteristic fluctuation
  • data mining
  • die-to-die variation
  • In-line process parameters
  • performance booster
  • process sequence
  • sensitivity analysis

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