Doctoral Dissertations

Date of Award

12-2008

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Industrial Engineering

Major Professor

Way Kuo, Yue Kuo

Committee Members

Alberto Garcia, Myong. K. Jeong, Frank Guess

Abstract

With the physical dimensions ever scaling down, the increasing level of sophistication in nano-electronics requires a comprehensive and multidisciplinary reliability investigation. A kind of nano-devices, HfO2-based high-k dielectric films, are studied in the statistical aspect of reliability as well as electrical and physical aspects of reliability characterization, including charge trapping and degradation mechanisms, breakdown modes and bathtub failure rate estimation.

This research characterizes charge trapping and investigates degradation mechanisms in high-k dielectrics. Positive charges trapped in both bulk and interface contribute to the interface state generation and flat band voltage shift when electrons are injected from the gate under a negative gate bias condition.A negligible number of defects are generated until the stress voltage increases to a certain level. As results of hot electrons and positive charges trapped in the interface region, the difference in the breakdown sequence is attributed to the physical thickness of the bulk high-k layer and the structure of the interface layer.

Time-to-breakdown data collected in the accelerated life tests are modeled with a bathtub failure rate curve by a 3-step Bayesian approach. Rather than individually considering each stress level in accelerating life tests (ALT), this approach derives the change point and the priors for Bayesian analysis from the time-to-failure data under neighborhood stresses, based on the relationship between the lifetime and stress voltage. This method can provide a fast and reliable estimation of failure rate for burn-in optimization when only a small sample of data is available.

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