Erasmus Langer
Siegfried Selberherr
Oskar Baumgartner
Markus Bina
Hajdin Ceric
Johann Cervenka
Lado Filipovic
Wolfgang Gös
Klaus-Tibor Grasser
Hossein Karamitaheri
Hans Kosina
Hiwa Mahmoudi
Alexander Makarov
Marian Molnar
Mahdi Moradinasab
Mihail Nedjalkov
Neophytos Neophytou
Roberto Orio
Dmitry Osintsev
Vassil Palankovski
Mahdi Pourfath
Karl Rupp
Franz Schanovsky
Anderson Singulani
Zlatan Stanojevic
Ivan Starkov
Viktor Sverdlov
Oliver Triebl
Stanislav Tyaginov
Paul-Jürgen Wagner
Michael Waltl
Josef Weinbub
Thomas Windbacher
Wolfhard Zisser

Klaus-Tibor Grasser
Ao.Univ.Prof. Dipl.-Ing. Dr.techn.
grasser(!at)iue.tuwien.ac.at
Biography:
Tibor Grasser was born in Vienna, Austria, in 1970. He received the Diplomingenieur degree in communications engineering, the PhD degree in technical sciences, and the venia docendi in microelectronics from the Technische Universität Wien, in 1995, 1999, and 2002, respectively. He is currently employed as an Associate Professor at the Institute for Microelectronics. Since 1997 he has headed the Minimos-NT development group, working on the successor to the highly successful MiniMOS program. He was a visiting research engineer for Hitachi Ltd., Tokyo, Japan, and for the Alpha Development Group, Compaq Computer Corporation, Shrewsbury, USA. In 2003 he was appointed head of the Christian Doppler Laboratory for TCAD in Microelectronics, an industry-funded research group embedded in the Institute for Microelectronics. His current scientific interests include circuit and device simulation, device modeling, and reliability issues.

On the Frequency Dependence of the Bias Temperature Instability

Recent studies clearly suggest that two components contribute to the Bias Temperature Instability (BTI). The first component is largely recoverable (R) and usually dominates the dynamics within the experimental window, starting from the microsecond regime up to a period of weeks. The second component is largely permanent (P) and may possibly dominate the long-term degradation. The recoverable component is usually attributed to charge trapping inside the oxide, a process typically assumed to follow first-order kinetics. Due to the amorphous nature of the oxide, the capture and emission times of the defects are widely distributed, explaining the contributions over such a large experimental window.
As a consequence of the first-order reaction, the effective time constants of the defects do not depend on frequency and the built-up degradation must be independent of the frequency. However, a number of groups have recently reported a frequency dependence of the degradation. One problem plaguing such studies is the strong impact of the measurement delay and possible synchronization issues between the AC stress signal and the measurement. By exploiting the properties of first-order kinetics it can be shown that, after a recovery time larger than the stress time, the trapped charge after AC stress must equal the trapped charge after DC stress of the same effective duration. Since these recovery times are very large, any issues with measurement delay and synchronization can be avoided. Studying the remaining degradation using this new method clearly shows that the experimental data is inconsistent with a first-order process. This result was expected given our detailed study on individual defects using the Time-Dependent Defect Spectroscopy (TDDS), which showed that charging occurs via an intermediate metastable state. This metastable state fully explains the frequency dependence of the data.


Top: The experimental recovery curves merge much later than predicted by the first-order model. Also, the degradation predicted by the first-order model is in excess by nearly 25%. Bottom: By using frequency-dependent three-state defects for R, the experimental behavior can be well reproduced.



The first-order model (lines) can only qualitatively reproduce the experimental duty-factor dependence (symbols). Data was recorded for increasing stress-times and measured with a delay of 1ms. Bottom: By using three-state defects for R, the duty-factor dependence can be accurately reproduced (lines).


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