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Statistical basis and physical evidence for clustering model in FinFET degradation
Conference proceeding

Statistical basis and physical evidence for clustering model in FinFET degradation

S Mei, N Raghavan, M Bosman and K L Pey
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings, p.3C-1.1
01/01/2017

Abstract

Analogies Architecture Clustering Corners Degradation Devices Dielectric breakdown Epitaxy Failure mechanisms Inhomogeneity Reliability Silicon Stacks Statistical analysis Statistical methods Variability Weibull distribution
Conference Title: 2017 IEEE International Reliability Physics Symposium (IRPS) Conference Start Date: 2017, April 2 Conference End Date: 2017, April 6 Conference Location: Monterey, CA, USA In this study, we present physical and statistical evidence to highlight the similarities and differences in the kinetics of the dielectric breakdown mechanism in FinFET devices, in comparison to their planar analogues. From a physical perspective, the mechanism of breakdown in FinFET devices still involves epitaxial silicon protrusion into the oxide during the progressive and hard breakdown stages, while the location of breakdown appears more confined to the bottom fin corners in almost all cases examined. From a statistical perspective, the Weibull distribution is no longer suitable for TDDB and residual time analysis. Instead, the clustering model becomes essential not only for wafer-level TDDB studies (due to process variations) but also for device-level studies, considering the field inhomogeneity and oxide thickness non-uniformity in the non-planar fin architecture. Bimodal distribution is observed in all stacks indicating the presence of two different failure mechanisms, possibly extrinsic and intrinsic. However, STEM-EELS and -EDX based examinations on several samples do not show any evidence for more than one physical process driving the degradation.

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