On the distribution of the FET threshold voltage shifts due to individual charged gate oxide defects

The factors contributing to the FET threshold voltage shift Δν<inf>th</inf> caused by charging of an individual trap, such as during Random Telegraph Noise (RTN), are discussed by analyzing device-calibrated simulation data. The Δν<inf>th</inf> distribution is observed to be a convolution of i) the position of the trap along the channel, randomized by ii) the random dopant distribution (RDD) responsible for percolative transport in the FET channel. In our TCAD simulation data the RDD component is observed to be roughly log-normally distributed. “Meta-simulations” varying this log-normal component are able to qualitatively reproduce a range of observed Δν<inf>th</inf> distribution shapes. In longer devices and/or in devices with high channel doping (or otherwise highly randomized channel potentials), the Δν<inf>th</inf> distribution tends toward log-normal. In the other, more relevant cases, the exponential Δν<inf>th</inf> distribution appears to be an acceptable approximation.

[1]  N. Horiguchi,et al.  Interplay Between Statistical Variability and Reliability in Contemporary pMOSFETs: Measurements Versus Simulations , 2014, IEEE Transactions on Electron Devices.

[2]  C. Auth,et al.  Bias temperature instability variation on SiON/Poly, HK/MG and trigate architectures , 2014, 2014 IEEE International Reliability Physics Symposium.

[3]  X. Federspiel,et al.  BTI variability fundamental understandings and impact on digital logic by the use of extensive dataset , 2013, 2013 IEEE International Electron Devices Meeting.

[4]  T. Grasser,et al.  Relevance of non-exponential single-defect-induced threshold voltage shifts for NBTI variability , 2013, 2013 IEEE International Integrated Reliability Workshop Final Report.

[5]  K. Shepard,et al.  Analysis of Random Telegraph Noise in 45-nm CMOS Using On-Chip Characterization System , 2013, IEEE Transactions on Electron Devices.

[6]  T. Grasser,et al.  Reduction of the BTI time-dependent variability in nanoscaled MOSFETs by body bias , 2013, 2013 IEEE International Reliability Physics Symposium (IRPS).

[7]  G. Groeseneken,et al.  From mean values to distributions of BTI lifetime of deeply scaled FETs through atomistic understanding of the degradation , 2011, 2011 Symposium on VLSI Technology - Digest of Technical Papers.

[8]  T. Grasser,et al.  The time dependent defect spectroscopy (TDDS) for the characterization of the bias temperature instability , 2010, 2010 IEEE International Reliability Physics Symposium.

[9]  T. Grasser,et al.  Statistics of Multiple Trapped Charges in the Gate Oxide of Deeply Scaled MOSFET Devices—Application to NBTI , 2010, IEEE Electron Device Letters.

[10]  K. Sonoda,et al.  Discrete Dopant Effects on Statistical Variation of Random Telegraph Signal Magnitude , 2007, IEEE Transactions on Electron Devices.

[11]  D. Frank,et al.  Increasing threshold voltage variation due to random telegraph noise in FETs as gate lengths scale to 20 nm , 2006, 2009 Symposium on VLSI Technology.

[12]  Redner,et al.  Anomalous voltage distribution of random resistor networks and a new model for the backbone at the percolation threshold. , 1985, Physical review. B, Condensed matter.