Index
Next: About this document
Up: PhD Thesis Nadim Khalil
Previous: Curriculum Vitae
- meta-simulation
- 6 Technology Characterization
- meta-simulation
- 6.4 Conclusion
L- 6.2 Analytical Model Parameter
- 6.3 MOSFET Gate Length
- B-spline
- 4.6 One-Dimensional Source/Drain Doping , 7 Conclusion
- B-splines Knots placement
- 4.5.1 An Algorithm for
- B-splines nonlinear regression
- 4.5 One-Dimensional MOS Doping
- B-splines representation
- 4.1 Background
- Boron
- 5.3 Implant Model Calibration
- Broyden update scheme
- 2.1.2 Calculation of the
- C-V characteristics:experimental
- 5.1.3 Comparisons with Experimental
- C-V characteristics:simulated
- 5.1.3 Comparisons with Experimental
- CMOS
- 4 MOSFET Profiling Using , 4.4 Methodology Overview, 6.1 Statistically Based Worst
- CMOS ULSI technology
- 7 Conclusion
- CMOS technology
- 6.1.2 Worst Case Condition
- CV measurements
- 4.4 Methodology Overview
- Debye length limitation
- 4.9.4 On the Subject
- EASE
- 1.1 Review of Previous
- Gauß -Newton
- 2.1 Nonlinear Least Squares
- Hessian
- 2.1.3 Eigenvalues Analysis of
- Hessian matrix
- 2.1.1 Algorithm Description
- I-V and C-V characteristics
- 6.2.1 PCIM Model fit
- I-V characteristics:experimental
- 5.1.3 Comparisons with Experimental
- I-V characteristics:simulated
- 5.1.3 Comparisons with Experimental
- Jacobian
- 2.1.1 Algorithm Description
- Jacobian calaculation
- 2.1.2 Calculation of the
- LISP
- 1.2 VISTA
- Levenberg-Marquardt
- 2.1 Nonlinear Least Squares
- Levenberg-Marquardt algorithm
- 5.4 Conclusion
- MASTIF
- 1.1 Review of Previous
- MECCA
- 1.1 Review of Previous
- MINIMOS
- 5 TCAD Simulators Calibration, 5.1.2 Parameters Extraction, 5.1.3 Comparisons with Experimental , 5.2.1 Modeling Equations, 6.1.1 Device Variation Analysis, 6.2 Analytical Model Parameter , 6.3.1 An empirical model
- MOSFET
- 6.3 MOSFET Gate Length
- MOSFET device reliability
- 5.2 Avalanche Model Calibration
- MOSFET length determination
- 4.4 Methodology Overview
- Monte Carlo
- 2.3 Empirical Model Building, 2.4 The Monte Carlo , 5.3 Implant Model Calibration, 6 Technology Characterization
- Monte Carlo simulation
- 6.1.1 Device Variation Analysis
- N- and P-channel devices
- 6.2.1 PCIM Model fit
- P-channel MOSFET
- 5.1 Mobility Model Calibration
- PCIM
- 6.2.1 PCIM Model fit
- PN diode
- 4.6 One-Dimensional Source/Drain Doping
- Pearson IV functions
- 5.3 Implant Model Calibration
- Poisson's equation
- 4.1 Background, 4.2 Capacitance Calculation, 4.5 One-Dimensional MOS Doping , 4.8 Two-Dimensional Extraction Results, 4.9.3 Method Limitations
- Profile Interchange Format
- 1.1 Review of Previous
- SIMS
- 4.4 Methodology Overview, 4.6 One-Dimensional Source/Drain Doping , 5.3.2 Fit to SIMS
- SRP
- 4.6 One-Dimensional Source/Drain Doping
- SUPREM-III
- 5 TCAD Simulators Calibration, 5.3.2 Fit to SIMS
- Semiconductor Wafer Representation
- 1.1 Review of Previous
- TCAD Frameworks
- 1.1 Review of Previous
- TCAD Frameworks architecture
- 1.1 Review of Previous
- TCAD framework
- 5.4 Conclusion
- TCAD model
- 2 Mathematical Considerations, 2.3 Empirical Model Building
- TCAD simulation
- 6 Technology Characterization, 6.2 Analytical Model Parameter
- TCAD systems
- 1.1 Review of Previous
- TCAD tasks
- 1.1 Review of Previous , 1.2 VISTA, 2 Mathematical Considerations, 7 Conclusion
- TPS MOSFET profile representation
- 4.7 Starting Two-Dimensional Profile
- TPS representation
- 4.1 Background, 4.4 Methodology Overview
- TPS: multivariate approximation
- 2.5.2 Tensor Product Spline
- ULSI
- 6.3 MOSFET Gate Length
- VISTA
- 1.1 Review of Previous , 7 Conclusion
- VISTA User Interface
- 1.2 VISTA
- analytical mosfet model
- 6.2.1 PCIM Model fit
- callback function
- 1.2 VISTA
- capacitance calculation
- 4.2 Capacitance Calculation
- carriers mobility
- 5.1 Mobility Model Calibration
- characterization
- 2.1 Nonlinear Least Squares
- chi-square
- 2.1 Nonlinear Least Squares
- co-design
- 6 Technology Characterization
- confidence region
- 2.1.5 Parameters Accuracy and , 4.9.2 Confidence Region of
- confidence regions
- 6.1.2 Worst Case Condition
- correlation
- 2.4.1 Statistical Background, 6.1.1 Device Variation Analysis
- covariance
- 2.4.1 Statistical Background
- covariance matrix
- 6.1.3 Corner Parameter Values
- deep depletion approximation
- 4.5 One-Dimensional MOS Doping
- deep depletion approximation, limitations
- 4.5 One-Dimensional MOS Doping
- deep depletion approximation: Diode
- 4.6 One-Dimensional Source/Drain Doping
- design of experiments (DOE)
- 2.3.1 Run Matrix Generation
- design through optimization
- 2.2 Nonlinear Programming
- device simulation
- 6.1.1 Device Variation Analysis
- discretization errors
- 4.2 Capacitance Calculation
- dopant profiling: SIMS
- 4.1 Background
- dopant profiling: SRP
- 4.1 Background
- dopant profiling: inverse modeling
- 4 MOSFET Profiling Using
- dual Pearson distribution functions
- 5.3.1 Dual Pearson Distribution
- effective channel length (
) - 6.3 MOSFET Gate Length
- effective mobility
- 5.1.1 Model Equations
- eigenvalues analysis
- 2.1.3 Eigenvalues Analysis of
- empirical model building
- 6 Technology Characterization, 6.3.1 An empirical model
- error reduction potential
- 4.5.1 An Algorithm for
- general nonlinear spline approximation
- 2.5.1 One Dimensional Spline
- hot carriers
- 5.2 Avalanche Model Calibration
- impact ionization rate
- 5.2 Avalanche Model Calibration
- inter-die variation
- 6.3 MOSFET Gate Length
- inter-wafer variation
- 6.3 MOSFET Gate Length
- intra-die variation
- 6.3 MOSFET Gate Length
- inverse modeling
- 4.1 Background, 4.1 Background
- ion implantation
- 5.3 Implant Model Calibration
- joint probability density function (jpdf)
- 2.4.1 Statistical Background
- knot placement
- 2.5.1 One Dimensional Spline
- knot placements: results
- 4.5.2 Results
- linear programming
- 2.2.1 Sequential Linear Programming
- maximum probability probability
- 6.1.3 Corner Parameter Values
- mean
- 2.4.1 Statistical Background
- multi-dimensional normal jpdf
- 2.4.1 Statistical Background
- multinormal distribution
- 6.1.3 Corner Parameter Values
- multinormal jpdf
- 2.4.3 Multinormal Distribution
- non-parametric modeling
- 2.5.1 One Dimensional Spline
- nonlinear least-squares optimization
- 5 TCAD Simulators Calibration, Nonlinear Least-Squares Optimizer
- nonlinear least-squares optimizer
- 7 Conclusion
- normal pdf
- 2.4.2 Normal Distribution
- numerical differentiation
- 4.2 Capacitance Calculation
- numerical differentiation,errors in
- 4.2 Capacitance Calculation
- numerical differentiations
- 2.1.2 Calculation of the
- one-dimensional MOS profile extraction
- 4.5 One-Dimensional MOS Doping
- optimization
- 1.2 VISTA
- optimization - constraints
- 2.1.4 Parameters Constraints
- optimization - nonlinear programming
- 2.2 Nonlinear Programming
- optimization design
- Technology Design Through
- optimization initial guess
- 4.4 Methodology Overview
- optimization nonlinear least-squares
- 4.4 Methodology Overview
- optimization: nonlinear least-squares
- 2.1 Nonlinear Least Squares
- parameters extraction
- 5.1.2 Parameters Extraction
- polynomial piecewise approximation
- 2.5 Splines and TPS
- polynomials
- 2.3 Empirical Model Building
- polysilicon depletion effects
- 6.3 MOSFET Gate Length
- polysilicon doping concentration
- 5.1.3 Comparisons with Experimental
- principal components
- 6.1.1 Device Variation Analysis
- probability
- 6.1.2 Worst Case Condition
- probability density function (pdf)
- 2.4.1 Statistical Background
- probability distribution functions
- 6.1.2 Worst Case Condition
- process flow representation
- 1.1 Review of Previous
- quadratic programming
- 2.2.2 Sequential Quadratic Programming
- quantum mechanical effects
- 6.3 MOSFET Gate Length
- random numbers
- 2.4 The Monte Carlo
- response surface models
- 6.1.1 Device Variation Analysis
- reverse short-channel effects
- 4.9.3 Method Limitations
- saturation current
- 6.1 Statistically Based Worst
- screening algorithms
- 2.3 Empirical Model Building
- simulation flow controller
- 1.1 Review of Previous
- simulators calibration
- 5 TCAD Simulators Calibration
- space charge density
- 4.2 Capacitance Calculation
- spline - B-spline
- 2.5.1 One Dimensional Spline
- spline - one-dimensional
- 2.5.1 One Dimensional Spline
- spline interpolation
- 2.5 Splines and TPS
- spline parametrizations
- 4.3 Profile Representation
- spline representation: artifacts
- 4.5.2 Results
- spline: knots placement
- 4.3 Profile Representation
- splines
- 2.5 Splines and TPS
- standard deviation
- 2.1.5 Parameters Accuracy and , 2.4.1 Statistical Background, 6.1.1 Device Variation Analysis
- statistical analysis
- 2.3 Empirical Model Building, 2.4 The Monte Carlo , 6.1.1 Device Variation Analysis
- statistical input variables
- 6.2 Analytical Model Parameter
- statistical variation
- 6.1.2 Worst Case Condition
- statistics
- 2.4.1 Statistical Background
- steepest descent
- 2.1 Nonlinear Least Squares
- substrate current (
) - 5.2 Avalanche Model Calibration
- sum of squares objective
- 2.1 Nonlinear Least Squares
- technology characetrization
- 7 Conclusion
- technology characterization
- 2.2 Nonlinear Programming
- tensor product spline
- 2.5 Splines and TPS, 7 Conclusion
- two-dimensional dopant profiling
- 5 TCAD Simulators Calibration, 5.1.3 Comparisons with Experimental
- two-dimensional doping profile of a MOSFET
- 7 Conclusion
- two-dimensional profile extraction
- 4.8 Two-Dimensional Extraction Results
- two-dimensional profile extraction: accuracy
- 4.9.2 Confidence Region of
- two-dimensional profile extraction: characteristics
- 4.9 Discussion
- two-dimensional profile extraction: limitations
- 4.9.3 Method Limitations
- two-dimensional profile extraction: resolution
- 4.8 Two-Dimensional Extraction Results
- two-dimensional profile extraction: results
- 4.8 Two-Dimensional Extraction Results
- two-dimensional profile extraction: validation
- 4.9.1 Validation
- universal mobility model
- 5.1.1 Model Equations
- velocity saturation
- 5.1.1 Model Equations
- virtual fab
- 6 Technology Characterization
- virtual factory
- 5 TCAD Simulators Calibration
- worst case characterization
- 6.1 Statistically Based Worst
- worst case technology characterization
- 5 TCAD Simulators Calibration
Martin Stiftinger
Tue Aug 1 19:07:20 MET DST 1995