Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
9672316 | Microelectronics Reliability | 2005 | 5 Pages |
Abstract
A critical aspect of integrated circuit manufacturing is the reliability of the components, in particular the gate oxide of transistors and capacitors. There are two statistical distributions, which can be applied to accelerated stress test failure data, namely the Lognormal or the Weibull distributions. The failure data can fit each distribution equally well. However both distributions will give vastly different lifetime predictions and their correct use is crucial for accurate lifetime prediction. A statistical based test, developed with Monte Carlo data, which is designed to decide if a failure data set has an underlying Lognormal or Weibull distribution is applied to empirical Time Dependent Dielectric Breakdown (TDDB) failure tests. The TDDB tests are carried out on 7 nm, 15 nm and 20 nm thick gate oxides. The results generated show the importance of making the correct choice between the two distributions for accurate lifetime prediction and validate the test for different oxide thickness. Also investigated are the effects of choosing the incorrect statistical distribution has on the voltage and temperature acceleration factors.
Related Topics
Physical Sciences and Engineering
Computer Science
Hardware and Architecture
Authors
James Prendergast, Eoin O'Driscoll, Ed Mullen,