E3S Theme II: Nanomechanics eBook
22 Feb 2020 | Contributor(s):: Center for Energy Efficient Electronics Science (editor), Tsu-Jae King Liu, Farnaz Niroui, Edgar Acosta, Sergio Fabian Almeida, Vladimir Bulovic, Sara Faithpour, Jinchi Han, Jeffrey H. Lang, Mariana Martinez, Jose Mireles, Rawan Naous, Benjamin Osoba, Jatin Patil, Bivas Saha, Mayuran Saravanapavanantham, Urmita Sikder, Vladimir Stojanovic, Timothy Swager, Aldo Vidana, Junqiao Wu, Alice Ye, David Zubia
This eBook was written by faculty, postdoctoral researchers, students, and staff of the Center for Energy Efficient Electronics Science (E3S). The Center is a consortium of five world-class academic institutions: University of California at Berkeley, Massachusetts Institute of Technology,...
FeFET Memory Window Analytical Calculator
16 Dec 2019 | | Contributor(s):: Nicolo Zagni, Paolo Pavan, Muhammad A. Alam
This code computes the Memory Window of a FeFET by using the Landau-Devonshire theory. The aim of this code is to illustrate: the derivation of the switching conditions the trends of MW scaling with ferroelectric thickness the design constraints to guarantee hysteresis the effect of...
Big Data in Reliability and Security: Some Basics
30 May 2019 | | Contributor(s):: Saurabh Bagchi
Big Data in Reliability and Security: Applications
Robust Computing Systems: From Today to the N3XT 1,000×
08 May 2019 | | Contributor(s):: Subhasish Mitra
This talk presents an overview of my group’s research in the above areas, and particularly emphasizes complexity and performance.
04 Jun 2018 | | Contributor(s):: Xingshu Sun, Raghu Vamsi Krishna Chavali, Muhammad Ashraful Alam
This package contains the Matlab scripts to perform the Suns-Vmp method. The code has been tested in Matlab R2016a.
Too hot to handle? The emerging challenge of reliability/variability in self-heated FintFET, ETSOI, and GAA-FET
11 Jan 2016 | | Contributor(s):: Muhammad A. Alam, Sang Hoon Shin, Muhammad Abdul Wahab, Jiangjiang Gu, Jingyun Zhang, Peide "Peter" Ye
This presentation is part of the 8th IEEE/ACM Workshop on Variability Modeling and Characterization (VMC) 2015. It is difficult to control the geometry, doping, and thicknesses of small transistors. Moreover, nanoscale transistors degrade due to NBTI and HCI at vastly different...
Failures in Photovoltaic Modules
21 Apr 2015 | | Contributor(s):: Peter Bermel
In this talk, I will discuss some of the major sources of performance degradation for common glass-encapsulated PV modules, including crystalline silicon and thin films. The greatest reliability challenges have occurred in the latter, with recent studies showing that thin-film modules operating...
Long term Aging of Autonomous STructures (LAAST) Seminar Series
07 Apr 2015 | | Contributor(s):: Ali Shakouri
The Long term Aging of Autonomous STructures (LAAST) seminar series focuses on reliability and aging of devices for energy conversion, information processing or sensing.
A Blind Fish in a River with a Waterfall
23 Mar 2010 | | Contributor(s):: Muhammad Alam, Sajia Sadeque
Prototype for a reliability problem defined as Stochastic Process with a Threshold
ECE 695A Lecture 37: Radiation Induced Damage – An overview
19 Apr 2013 | | Contributor(s):: Muhammad Alam
Outline:Introduction and short history of radiation damageRadiation damage in various types of componentsSources of radiationA basic calculation and simulation approachesConclusions
ECE 695A Lecture 37R: Review Questions
Review Questions:Why is SOI more radiation hard compared to bulk devices? What do you feel about radiation hardness of FINFET?What type of radiation issues could arise for thin-body devices like FINFET?What is error correction code? Why does it correct for MBU?What is the difference between SEE...
ECE 695A Lecture 34: Scaling Theory of Design of Experiments
18 Apr 2013 | | Contributor(s):: Muhammad Alam
Outline:IntroductionBuckingham PI TheoremAn Illustrative ExampleRecall the scaling theory of HCI, NBTI, and TDDBConclusions
ECE 695A Lecture 34A: Appendix - Variability by Bootstrap Method
ECE 695A Lecture 33: Model Selection/Goodness of Fit
Outline:The problem of matching data with theoretical distributionParameter extractions: Moments, linear regression, maximum likelihoodGoodness of fit: Residual, Pearson, Cox, AkikaConclusion
ECE 695A Lecture 33R: Review Questions
Review Questions:With higher number of model parameters, you can always get a good fit – why should you minimize the number of parametersLeast square method is a subset of maximum likelihood approach to data fitting. Is this statement correct?What aspect of the distribution function does...
ECE 695A Lecture 32R: Review Questions
15 Apr 2013 | | Contributor(s):: Muhammad Alam
Review Questions:Why do people use Normal, log-normal, Weibull distributions when they do not know the exact physical distribution?What is the problem of using empirical distributions? What are the advantages?If you must choose an empirical distribution, what should be your criteria? (Nos. of...
ECE 695A Lecture 32: Physical vs. Empirical Distribution
Outline:Physical Vs. empirical distributionProperties of classical distribution functionMoment-based fitting of dataConclusions