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ECE 695A Lecture 36: Radiation Induced Damage – an overview

29 Apr 2013 | Online Presentations | Contributor(s): Muhammad Alam

ECE 695A Lecture 35R: Review Questions

24 Apr 2013 | Online Presentations | Contributor(s): Muhammad Alam

Review Questions:What role did Fisher play in developing the design of experiment?If you have 3 variables at two levels, what Taguchi array would you choose?How does one find correlation among variables in Full factorial method?What is the role of linear graphs in Taguchi method?In what ways...

ECE 695A Lecture 35: Design of Experiments

Outline:Context and backgroundSingle factor and full factorial methodOrthogonal vector analysis: Taguchi/Fisher modelCorrelation in dependent parametersConclusions

ECE 695A Lecture 37R: Review Questions

20 Apr 2013 | Online Presentations | Contributor(s): Muhammad Alam

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 37: Radiation Induced Damage – An overview

Outline:Introduction and short history of radiation damageRadiation damage in various types of componentsSources of radiationA basic calculation and simulation approachesConclusions

ECE 695A Lecture 34A: Appendix - Variability by Bootstrap Method

18 Apr 2013 | Online Presentations | Contributor(s): Muhammad Alam

ECE 695A Lecture 34: Scaling Theory of Design of Experiments

Outline:IntroductionBuckingham PI TheoremAn Illustrative ExampleRecall the scaling theory of HCI, NBTI, and TDDBConclusions

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 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 32R: Review Questions

17 Apr 2013 | Online Presentations | 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

ECE 695A Lecture 31R: Review Questions

15 Apr 2013 | Online Presentations | Contributor(s): Muhammad Alam

Review Questions:What is the difference between parametric estimation vs. non-parametric estimation?What principle did Tacho Brahe’s approach assume?What is the difference between population and sample? When we collect data for TDDB or NBTI, what type of data are we collecting?What problem does...

ECE 695A Lecture 31A: Appendix - Bootstrap Method Introduction

ECE 695A Lecture 31: Collecting and Plotting Data

Outline:Origin of data, Field Acceleration vs. Statistical InferenceNonparametric informationPreparing data for projection: Hazen formula Preparing data for projection: Kaplan formulaConclusion

ECE 695A Lecture 30R: Review Questions

08 Apr 2013 | Online Presentations | Contributor(s): Muhammad Alam

Outline:What is the difference between extrinsic vs. intrinsic breakdown?Does gas dielectric have extrinsic breakdown? Why or why not?What does ESD damage and the plasma damage to thin oxides?Can you explain the physical meaning of infant mortality ? How does it relate to yield of semiconductor...

ECE 695A Lecture 30: Breakdown in Dielectrics with Defects

Outline:IntroductionTheory of pre-existing defects: Thin oxidesTheory of pre-existing defects: thick oxidesConclusions

ECE 695A Lecture 29R: Review Questions

Review Questions:Mention a few differences between thick and thin oxide breakdown.Is breakdown in thick oxides contact dominated? Can I use AHI theory here?How does the Paschen’s cascade initiate?What does it mean to have a fractal dimension of 1.7 for 2D breakdown? Why does the number suggest...

ECE 695A Lecture 29A: Appendix - Dimension of a Surface

ECE 695A Lecture 29: Breakdown of Thick Dielectrics

Outline:IntroductionSpatial and temporal dynamics during breakdownBreakdown in bulk oxides: puzzleConclusions

ECE 695A Lecture 28: Circuit Implications of Dielectric Breakdown

Outline:Part 1 - Understanding Post-BD FET behaviorBD position determinationHard and Soft BD in FETsDistinguishing leakage and intrinsic FET parameters shiftsPart 2 - Impact of breakdown on digital circuit operationBD in ring oscillatorBDinSR AMcellTiming, BD into soft node

ECE 695A Lecture 27R: Review Questions

29 Mar 2013 | Online Presentations | Contributor(s): Muhammad Alam

ECE 695A Lecture 27: Correlated TDDB in Off-State HCI

ECE 695A Lecture 26R: Review Questions

28 Mar 2013 | Online Presentations | Contributor(s): Muhammad Alam

ECE 695A Lecture 26-2: Statistics of Soft Breakdown (Breakdown Position correlation)

Outline:Position and time correlation of BD spotHow to determine the position of the BD SpotPosition correlation in BD spotsWhy is localization so weak?Conclusions

ECE 695A Lecture 26-1: Statistics of Soft Breakdown via Methods of Markov Chains

Outline:Spatial vs. Temporal correlationTheory of correlated Dielectric BreakdownExcess leakage as a signature of correlated BDConclusions