Skip to main content
padlock icon - secure page this page is secure

Exploration of Inter-Die Bulk Fin-Typed Field Effect Transistor Process Variation for Reduction of Device Variability

Buy Article:

$105.00 + tax (Refund Policy)

This work first reports a novel exploration technique to systematically prioritize key fabrication in-line process parameters of 16-nm high-k metal gate (HKMG) bulk FinFET to reduce device’s die-to-die variation. To extract hidden correlations and reduce decision variables among the complex in-line process parameters, a data mining technique is employed to highlight and group associated parameters. To correlate the measured data with the distribution of physical dimension of devices for all in-line processes, a sensitivity analysis is then performed. Because the variability of current process deeply affects the next process, so the sequence of fabrication process is further added into the analyzing procedure to increase the searching efficiency. The source of variation of the initial process can be monitored and traced by the proposed methodology. The result of this study indicates that the gate spacer is a key process factor and will determine the uniformity of process including, such as the source-and-drain proximity, and the depth, lateral offset and overlap of sequential doping implants. The ranked key in-line process parameters can be used to optimize process and minimize the device variability of 16-nm HKMG bulk FinFET devices.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: Data Mining; Die-To-Die Variation; Emerging Device Technology; Fab In-Line Data; FinFET; Process Sequence; Sensitivity; Variability

Document Type: Research Article

Affiliations: Parallel and Scientific Computing Laboratory, National Chiao Tung University, Hsinchu 300, Taiwan

Publication date: 01 June 2016

More about this publication?
  • Journal for Nanoscience and Nanotechnology (JNN) is an international and multidisciplinary peer-reviewed journal with a wide-ranging coverage, consolidating research activities in all areas of nanoscience and nanotechnology into a single and unique reference source. JNN is the first cross-disciplinary journal to publish original full research articles, rapid communications of important new scientific and technological findings, timely state-of-the-art reviews with author's photo and short biography, and current research news encompassing the fundamental and applied research in all disciplines of science, engineering and medicine.
  • Editorial Board
  • Information for Authors
  • Subscribe to this Title
  • Terms & Conditions
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more