Time Dependent Variability in Advanced FinFET Technology for End-of-Lifetime Reliability Prediction

Time dependent variability has become a significant concern for End-of-lifetime(EOL) reliability prediction for advanced technology with continuous scaling. In this work, we explore time dependent variability of BTI and HCI on our advanced FinFET technology to demonstrate that Defect-Centric model is a good candidate to describe both of them and there is no obvious difference between 8nm and 7nm for BTI and HCI variation η parameter. Thus, a framework is proposed for BTI and HCI EOL degradation prediction with given ppm criteria.

[1]  Naoto Horiguchi,et al.  Origins and implications of increased channel hot carrier variability in nFinFETs , 2015, 2015 IEEE International Reliability Physics Symposium.

[2]  A. Visconti,et al.  Comprehensive Analysis of Random Telegraph Noise Instability and Its Scaling in Deca–Nanometer Flash Memories , 2009, IEEE Transactions on Electron Devices.

[3]  Jong Shik Yoon,et al.  8LPP Logic Platform Technology for Cost-Effective High Volume Manufacturing , 2018, 2018 IEEE Symposium on VLSI Technology.

[4]  Tibor Grasser,et al.  Stochastic charge trapping in oxides: From random telegraph noise to bias temperature instabilities , 2012, Microelectron. Reliab..

[5]  Francky Catthoor,et al.  The defect-centric perspective of device and circuit reliability — From individual defects to circuits , 2015, 2015 45th European Solid State Device Research Conference (ESSDERC).

[6]  T. Nigam,et al.  Challenges in the characterization and modeling of BTI induced variability in metal gate / High-k CMOS technologies , 2013, 2013 IEEE International Reliability Physics Symposium (IRPS).

[7]  Naoto Horiguchi,et al.  Extraction of the Random Component of Time-Dependent Variability Using Matched Pairs , 2015, IEEE Electron Device Letters.

[8]  A. Asenov,et al.  Intrinsic parameter fluctuations in decananometer MOSFETs introduced by gate line edge roughness , 2003 .

[9]  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.

[10]  F. Cacho,et al.  Comparison of variability of HCI induced drift for SiON and HKMG devices , 2020, 2020 IEEE International Reliability Physics Symposium (IRPS).

[11]  M. D. Giles,et al.  Process Technology Variation , 2011, IEEE Transactions on Electron Devices.

[12]  S. Jung,et al.  True 7nm Platform Technology featuring Smallest FinFET and Smallest SRAM cell by EUV, Special Constructs and 3rd Generation Single Diffusion Break , 2018, 2018 IEEE Symposium on VLSI Technology.

[13]  J.P. Campbell,et al.  Random telegraph noise in highly scaled nMOSFETs , 2009, 2009 IEEE International Reliability Physics Symposium.

[14]  S. Pae,et al.  Enhanced Reliability of 7-nm Process Technology Featuring EUV , 2019, IEEE Transactions on Electron Devices.

[15]  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).

[16]  R. Degraeve,et al.  Origin of NBTI variability in deeply scaled pFETs , 2010, 2010 IEEE International Reliability Physics Symposium.

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

[18]  Andrew R. Brown,et al.  Statistical variability and reliability in nanoscale FinFETs , 2011, 2011 International Electron Devices Meeting.

[19]  Ieee Staff.  ESSDERC 2013 - 43rd European Solid State Device Research Conference , 2013 .

[20]  Francky Catthoor,et al.  Characterization of time-dependent variability using 32k transistor arrays in an advanced HK/MG technology , 2015, 2015 IEEE International Reliability Physics Symposium.

[21]  B. Kaczer,et al.  Degradation of time dependent variability due to interface state generation , 2013, 2013 Symposium on VLSI Technology.