Failure Analysis of Large Area Pt/HfO2/Pt Capacitors Using Multilayer Perceptrons

J. Munoz-Gorriz, S. Monaghan, K. Cherkaoui, J. Sune, P. K. Hurley, E. Miranda

Research output: Contribution to journalArticleResearchpeer-review

Abstract

In this work, we investigated the spatial distribution of failure sites in large area Pt/HfO2/Pt capacitors using simple neural networks as classifiers. When an oxide breakdown (BD) occurs due to severe electrical stress, a mark shows up in the top metal electrode at the location where the failure event took place. The mark is the result of a microexplosion occurring inside the dielectric film. Large area devices need to be studied because the number of generated spots must be the required for statistical analysis. The obtained results using multilayer perceptrons with different number of neurons and hidden layers indicate that the largest breakdown spots tend to concentrate towards the center of the device. This observation is consistent with previous exploratory analysis carried out using spatial statistics techniques. This exercise shows the suitability of multilayer perceptrons for investigating the distribution of failure sites or defects on a given surface.

Original languageEnglish
Number of pages5
JournalProceedings of the International Symposium on the Physical and Failure Analysis of Integrated Circuits, IPFA
DOIs
Publication statusPublished - 2021

Keywords

  • dielectric breakdown
  • MIM
  • neural networks
  • perceptron
  • reliability
  • spatial statistics

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