학술논문

Array-Based Statistical Characterization of CMOS Degradation Modes and Modeling of the Time-Dependent Variability Induced by Different Stress Patterns in the $\{\boldsymbol{V_{G}}, \boldsymbol{V_{D}}\}$ bias space
Document Type
Conference
Source
2019 IEEE International Reliability Physics Symposium (IRPS) Reliability Physics Symposium (IRPS), 2019 IEEE International. :1-6 Mar, 2019
Subject
Components, Circuits, Devices and Systems
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Degradation
Stress
Field effect transistors
Logic gates
Negative bias temperature instability
Thermal variables control
Hot carriers
Language
ISSN
1938-1891
Abstract
Degradation mechanisms, such as Bias Temperature Instabilities (BTI) and Hot Carrier Degradation (HCD), as well as the associated time-dependent variability, dictate the limit on the acceptable operating voltage conditions in modern deeply-scaled VLSI devices. Based on large statistical datasets, acquired using specifically designed on-chip arrays, we experimentally obtain DC degradation maps for both $\boldsymbol{n}$ - and $\boldsymbol{p}$-type FETs. Defect-centric based analysis of the statistical parameters at every $\boldsymbol{V_{G}}, \boldsymbol{V_{D}}$ bias point provides physical insights in the underlying single- and multi-carrier degradation processes. As a result, we can separate the defect charging contributions of each degradation mechanism and describe to which extent these mechanisms co-interact. We finally present a simplified model (the “3-bucket” model) that is able to describe the degradation statistics up to $3\boldsymbol{\sigma}$ of a device population subject to an arbitrary combination of BTI and HCD stress.