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 Allen, J. B., 1942 author.
 Cham, Switzerland : Springer, [2020]
 Description
 Book — 1 online resource
 Summary

 Introduction
 Number Systems
 Algebraic Equations
 Scalar Calculus
 Vector Calculus.
2. Scientific Foundations of Engineering [2015]
 McKnight, Stephen, author.
 Cambridge : Cambridge University Press, 2015.
 Description
 Book — 1 online resource (398 pages) : digital, PDF file(s).
 Summary

 1. Kinematics and vectors
 2. Newton's laws, energy, and momentum
 3. Rotational motion
 4. Rotation matrices
 5. Material properties  elasticity
 6. Harmonic oscillators
 7. Waves
 8. The quantum puzzle
 9. Quantum mechanics
 10. Quantum electrons
 11. Quantum electrons in solids
 12. Thermal physics
 13. Quantum statistics
 14. Electromagnetic phenomena
 15. Fluids.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
3. COMSOL for engineers [2014]
 Tabatabaian, Mehrzad.
 Dulles, VA : Mercury Learning and Information, ©2014.
 Description
 Book — 1 online resource
 Summary

 Cover page; Half title; LICENSE, DISCLAIMER OF LIABILITY, AND LIMITED WARRANTY; Title Page; Copyright; Dedication; CONTENTS; Preface;
 Chapter 1: Introduction;
 Chapter 2: Finite Element MethodA Summary; Overview; FEM Formulation; Matrix Approach; Example 2.1: Analysis of a 2D Truss; General Procedure for Global Matrix Assembly; Example 2.2: Global Matrix for Triangular Elements; Weighted Residual Approach; Galerkin Method; Shape Functions; Convergence and Stability; Example2.3: Heat Transfer in a Slender Steel Bar; Exercise Problems; References;
 Chapter 3: COMSOLA Modeling Tool for Engineers.
 OverviewCOMSOL Interface; COMSOL Modules; COMSOL Model Library and Tutorials; General Guidelines for Building a Model;
 Chapter 4: COMSOL Models for Physical Systems; Overview; Section 4.1: Static and Dynamic Analysis of Structures; Example 4.1: Stress Analysis for a Thin Plate Under Stationary Loads; Example 4.2: Dynamic Analysis for a Thin Plate: Eigenvalues and Modal Shapes; Example 4.3: Parametric Study for a Bracket Assembly: 3D Stress Analysis; Example 4.4: Buckling of a Column with Triangular Crosssection: Linearized Buckling Analysis.
 Example 4
 .5: Static and Dynamic Analysis for a 2D Bridgesupport TrussExample 4
 .6: Static and Dynamic Analysis for a 3D Truss Tower; Section 4
 .2: Dynamic Analysis and Models of Internal Flows: Laminar and Turbulent; Example 4
 .7: Axisymmetric Flow in a Nozzle: Simplified Waterjet; Example 4
 .8: Swirl Flow Around a Rotating Disk: Laminar Flow; Example 4
 .9: Swirl Flow Around a Rotating Disk: Turbulent Flow; Example 4
 .10: Flow in a Ushape Pipe with Square Crosssectional Area: Laminar Flow; Example 4
 .11: Doubledriven Cavity Flow: Moving Boundary Conditions.
 Example 4
 .12: Water Hammer Model: Transient Flow AnalysisExample 4
 .13: Static Fluid Mixer Model; Section 4
 .3: Modeling of Steady and Unsteady Heat Transfer in Media; Example 4
 .14: Heat Transfer in a Multilayer Sphere; Example 4
 .15: Heat Transfer in a Hexagonal Fin; Example 4
 .16: Transient Heat Transfer Through a Nonprismatic Fin with Convective Cooling; Example 4
 .17: Heat Conduction Through a Multilayer Wall with Contact Resistance; Section 4
 .4: Modeling of Electrical Circuits; Example 4
 .18: Modeling an RC Electrical Circuit; Example 4
 .19: Modeling an RLC Electrical Circuit.
 Section 4
 .5: Modeling Complex and Multiphysics ProblemsExample 4
 .20: Stress Analysis for an Orthotropic Thin Plate; Example 4
 .21: Thermal Stress Analysis and Transient Response of a Bracket; Example 4
 .22: Static Fluid Mixer with Flexible Baffles; Example 4
 .23: Double Pendulum: Multibody Dynamics; Example 4
 .24: Multiphysics Model for Thermoelectric Modules; Example 4
 .25: Acoustic Pressure Wave Propagation in an Automotive Muffler; Exercise Problems; References; Suggested Further Readings; Trademark References; Index.
4. COMSOL for engineers [2014]
 Tabatabaian, Mehrzad.
 Dulles, VA : Mercury Learning and Information, ©2014.
 Description
 Book — 1 online resource
 Summary

 1: Introduction.
 2: Finite Element Method (FEM)A Summary.
 3: COMSOL  A Modeling Tool For Engineers.
 4: Modeling SinglePhysics Problems.
 5: Modeling MultiPhysics Problems.
 6: Modeling Energy Systems With COMSOL.
 7: Advanced Features Of COMSOL.
 Appendices.
 Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Online
 Steinhauser, M. O. (Martin Oliver), author.
 Berlin : Walter de Gruyter GmbH & Co. KG, 2013.
 Description
 Book — 1 online resource (xix, 508 pages) : illustrations
 Summary

 Preface
 1. Introduction to Computer Simulation 1.1 Historical Background 1.2 Theory, Modeling and Simulation in Physics 1.3 Reductionism in Physics 1.4 Basics of Ordinary and Partial Differential Equations in Physics 1.5 Numerical Solution of Differential Equations: MeshBased vs. Particle Methods 1.6 The Role of Algorithms in Scientific Computing 1.7 Remarks on Software Design 1.8 Summary
 2. Fundamentals of Statistical Physics 2.1 Introduction 2.2 Elementary Statistics 2.3 Introduction to Classical Statistical Mechanics 2.4 Introduction to Thermodynamics 2.5 Summary
 3. Inter and Intramolecular ShortRange Potentials 3.1 Introduction 3.2 Quantum Mechanical Basis of Intermolecular Interactions 3.2.1 Perturbation Theory 3.3 Classical Theories of Intermolecular Interactions 3.4 Potential Functions 3.5 Molecular Systems 3.6 Summary
 4. Molecular Dynamics Simulation 4.1 Introduction 4.2 Basic Ideas of MD 4.3 Algorithms for Calculating Trajectories 4.4 Link between MD and Quantum Mechanics 4.5 Basic MD Algorithm: Implementation Details 4.6 Boundary Conditions 4.7 The Cutoff Radius for ShortRange Potentials 4.8 Neighbor Lists: The LinkedCell Algorithm 4.9 The Method of Ghost Particles 4.10 Implementation Details of the Ghost Particle Method 4.11 Making Measurements 4.12 Ensembles and Thermostats 4.13 Case Study: Impact of Two Different Bodies 4.14 Case Study: RayleighTaylor Instability 4.15 Case Study: LiquidSolid Phase Transition of Argon
 5. Advanced MD Simulation 5.1 Introduction 5.2 Parallelization 5.3 More Complex Potentials and Molecules 5.4 Many Body Potentials 5.5 Coarse Grained MD for Mesoscopic Systems
 6. Outlook on Monte Carlo Simulations 6.1 Introduction 6.2 The Metropolis MonteCarlo Method 6.2.1 Calculation of Volumina and Surfaces 6.2.2 Percolation Theory 6.3 Basic MC Algorithm: Implementation Details 6.3.1 Case Study: The 2D Ising Magnet 6.3.2 Trial Moves and Pivot Moves 6.3.3 Case Study: Combined MD and MC for Equilibrating a Gaussian Chain 6.3.4 Case Study: MC of Hard Disks 6.3.5 Case Study: MC of Hard Disk Dumbbells in 2D 6.3.6 Case Study: Equation of State for the LennardJones Fluid 6.4 Rosenbluth and Rosenbluth Method 6.5 Bond Fluctuation Model 6.6 Monte Carlo Simulations in Different Ensembles 6.7 Random Numbers Are Hard to Find
 7. Applications from Soft Matter and Shock Wave Physics 7.1 Biomembranes 7.2 Scaling Properties of Polymers 7.3 Polymer Melts 7.4 Polymer Networks as a Model for the Cytoskeleton of Cells 7.5 Shock Wave Impact in Brittle Solids
 8. Concluding Remarks A Appendix A.1 Quantum Statistics of Ideal Gases A.2 MaxwellBoltzmann, BoseEinstein and FermiDirac Statistics A.3 Stirling's Formula A.4 Useful Integrals in Statistical Physics A.3 Useful Conventions for Implementing Simulation Programs A.4 Quicksort and Heapsort Algorithms A.4 Selected Solutions to Exercises Abbreviations Bibliography Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Steinhauser, M. O. (Martin Oliver), author.
 Berlin : Walter de Gruyter GmbH & Co. KG, 2013.
 Description
 Book — 1 online resource (xix, 508 pages) : illustrations
 Summary

 Preface
 1. Introduction to Computer Simulation 1.1 Historical Background 1.2 Theory, Modeling and Simulation in Physics 1.3 Reductionism in Physics 1.4 Basics of Ordinary and Partial Differential Equations in Physics 1.5 Numerical Solution of Differential Equations: MeshBased vs. Particle Methods 1.6 The Role of Algorithms in Scientific Computing 1.7 Remarks on Software Design 1.8 Summary
 2. Fundamentals of Statistical Physics 2.1 Introduction 2.2 Elementary Statistics 2.3 Introduction to Classical Statistical Mechanics 2.4 Introduction to Thermodynamics 2.5 Summary
 3. Inter and Intramolecular ShortRange Potentials 3.1 Introduction 3.2 Quantum Mechanical Basis of Intermolecular Interactions 3.2.1 Perturbation Theory 3.3 Classical Theories of Intermolecular Interactions 3.4 Potential Functions 3.5 Molecular Systems 3.6 Summary
 4. Molecular Dynamics Simulation 4.1 Introduction 4.2 Basic Ideas of MD 4.3 Algorithms for Calculating Trajectories 4.4 Link between MD and Quantum Mechanics 4.5 Basic MD Algorithm: Implementation Details 4.6 Boundary Conditions 4.7 The Cutoff Radius for ShortRange Potentials 4.8 Neighbor Lists: The LinkedCell Algorithm 4.9 The Method of Ghost Particles 4.10 Implementation Details of the Ghost Particle Method 4.11 Making Measurements 4.12 Ensembles and Thermostats 4.13 Case Study: Impact of Two Different Bodies 4.14 Case Study: RayleighTaylor Instability 4.15 Case Study: LiquidSolid Phase Transition of Argon
 5. Advanced MD Simulation 5.1 Introduction 5.2 Parallelization 5.3 More Complex Potentials and Molecules 5.4 Many Body Potentials 5.5 Coarse Grained MD for Mesoscopic Systems
 6. Outlook on Monte Carlo Simulations 6.1 Introduction 6.2 The Metropolis MonteCarlo Method 6.2.1 Calculation of Volumina and Surfaces 6.2.2 Percolation Theory 6.3 Basic MC Algorithm: Implementation Details 6.3.1 Case Study: The 2D Ising Magnet 6.3.2 Trial Moves and Pivot Moves 6.3.3 Case Study: Combined MD and MC for Equilibrating a Gaussian Chain 6.3.4 Case Study: MC of Hard Disks 6.3.5 Case Study: MC of Hard Disk Dumbbells in 2D 6.3.6 Case Study: Equation of State for the LennardJones Fluid 6.4 Rosenbluth and Rosenbluth Method 6.5 Bond Fluctuation Model 6.6 Monte Carlo Simulations in Different Ensembles 6.7 Random Numbers Are Hard to Find
 7. Applications from Soft Matter and Shock Wave Physics 7.1 Biomembranes 7.2 Scaling Properties of Polymers 7.3 Polymer Melts 7.4 Polymer Networks as a Model for the Cytoskeleton of Cells 7.5 Shock Wave Impact in Brittle Solids
 8. Concluding Remarks A Appendix A.1 Quantum Statistics of Ideal Gases A.2 MaxwellBoltzmann, BoseEinstein and FermiDirac Statistics A.3 Stirling's Formula A.4 Useful Integrals in Statistical Physics A.3 Useful Conventions for Implementing Simulation Programs A.4 Quicksort and Heapsort Algorithms A.4 Selected Solutions to Exercises Abbreviations Bibliography Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Online
7. Engineering physics [2013]
 Naidu, S. Mani Dr.
 New Delhi : Dorling Kindersley (India), ©2013.
 Description
 Book — 1 online resource (1 volume) : illustrations
 Ohtsubo, J. (Junji)
 3rd ed.  Heidelberg ; New York : Springer, 2013.
 Description
 Book — 1 online resource Digital: text file.PDF.
 Summary

 Chaos in Laser Systems
 Semiconductor Lasers and Theory
 Theory of Optical Feedback in Semiconductor Lasers
 Dynamics of Semiconductor Lasers with Optical Feedback
 Dynamics in Semiconductor Lasers with Optical Injection
 Dynamics of Semiconductor Lasers with Optoelectronic Feedback and Modulation
 Instability and Chaos in Various Laser Structures
 Chaos Control and Applications
 Stabilization of Semiconductor Lasers
 Metrology Based on Chaotic Semiconductor Lasers
 Chaos Synchronization in Semiconductor Lasers
 Chaotic Communications in Semiconductor Lasers
 Physical Random Number Generations and Photonic Integrated Circuits for Chaotic Generators.
(source: Nielsen Book Data)
9. Toward quantum FinFET [2013]
 Cham : Springer, 2013.
 Description
 Book — 1 online resource (xi, 363 pages) : illustrations (some color) Digital: text file; PDF.
 Summary

 Preface
 Contents
 Contributors
 Chapter 1: Simulation of Quantum Ballistic Transport in FinFETs
 1.1 Introduction
 1.2 Quantum Effects in FinFETs
 1.2.1 Quantum Confinement
 1.2.2 QuantumMechanical Tunneling
 1.2.3 Ballistic Transport and Quantum Interference
 1.3 SelfConsistent Field Method
 1.4 The NEGF in RealSpace Representation
 1.5 Computationally Efficient Methods in the Real Space
 1.5.1 The Recursive GreenÂ?s Function Algorithm
 1.5.2 The Contact Block Reduction Method
 1.5.3 The Gauss Elimination Method
 1.5.4 Computational Efficiency Comparison1.6 The NEGF in ModeSpace Representation
 1.6.1 Coupled ModeSpace Approach
 1.6.2 PartialCoupled ModeSpace Approach
 1.6.3 Validation of the PCMS Approach
 1.7 Conclusion
 References
 Chapter 2: Model for Quantum Confinement in Nanowires and the Application of This Model to the Study of Carrier Mobility in Na ...
 2.1 Introduction
 2.2 Surface Energy
 2.3 Thermodynamic Imbalance
 2.4 Nanowire Surface Disorder
 2.5 Quantum Confinement
 2.6 Energy Band Gap as Function of Nanowire Diameter
 2.7 Formula for Amorphicity2.8 Models for Carrier Scattering
 2.9 Calculated Carrier Mobility
 2.10 Conclusions
 References
 Chapter 3: Understanding the FinFET Mobility by Systematic Experiments
 3.1 Introduction
 3.2 Impact of Surface Orientation
 3.3 Impact of Strain
 3.4 Impact of Fin Doping
 3.5 Impact of Gate Stack
 3.6 Conclusion
 References
 Chapter 4: Quantum Mechanical Potential Modeling of FinFET
 4.1 Introduction
 4.2 FinFET Structure
 4.2.1 FinFET Design Parameters
 4.3 Quantum Mechanical Potential Modeling
 4.4 Threshold Voltage Modeling4.5 Source/Drain Resistance Modeling
 4.6 Results and Discussion
 4.7 Conclusion
 References
 Chapter 5: Physical Insight and Correlation Analysis of Finshape Fluctuations and WorkFunction Variability in FinFET Devices
 5.1 Introduction
 5.2 Modeling Approach
 5.2.1 LER Modeling
 5.2.2 WFV Modeling
 5.3 Statistical Analysis of LER and WFVInduced Fluctuations
 5.4 CorrelationBased Approaches for Variability Estimation
 5.4.1 Correlations and Sensitivity Analysis
 5.4.2 Simplified Approaches for Variability Estimation5.4.2.1 Threshold Voltage Variability
 5.4.2.2 Drive Current Variability
 5.4.3 Physical Insight of Fin LERInduced Threshold Voltage Increase
 5.5 Asymmetric Impact of Localized Fluctuations
 5.5.1 Impact of Local Fin Thinning
 5.5.2 Impact of Grain Location and Size
 5.6 Conclusions
 References
 Chapter 6: Characteristic and Fluctuation of Multifin FinFETs
 6.1 Introduction
 6.1.1 Random Dopant Fluctuation
 6.1.2 Reduction Techniques of Random Dopant Fluctuation
(source: Nielsen Book Data)
 Steinhauser, M. O. (Martin Oliver)
 Berlin : Walter de Gruyter, [2012]
 Description
 Book — 1 online resource (xix, 508 pages) : illustrations.
 Summary

 Preface
 1. Introduction to Computer Simulation 1.1 Historical Background 1.2 Theory, Modeling and Simulation in Physics 1.3 Reductionism in Physics 1.4 Basics of Ordinary and Partial Differential Equations in Physics 1.5 Numerical Solution of Differential Equations: MeshBased vs. Particle Methods 1.6 The Role of Algorithms in Scientific Computing 1.7 Remarks on Software Design 1.8 Summary
 2. Fundamentals of Statistical Physics 2.1 Introduction 2.2 Elementary Statistics 2.3 Introduction to Classical Statistical Mechanics 2.4 Introduction to Thermodynamics 2.5 Summary
 3. Inter and Intramolecular ShortRange Potentials 3.1 Introduction 3.2 Quantum Mechanical Basis of Intermolecular Interactions 3.2.1 Perturbation Theory 3.3 Classical Theories of Intermolecular Interactions 3.4 Potential Functions 3.5 Molecular Systems 3.6 Summary
 4. Molecular Dynamics Simulation 4.1 Introduction 4.2 Basic Ideas of MD 4.3 Algorithms for Calculating Trajectories 4.4 Link between MD and Quantum Mechanics 4.5 Basic MD Algorithm: Implementation Details 4.6 Boundary Conditions 4.7 The Cutoff Radius for ShortRange Potentials 4.8 Neighbor Lists: The LinkedCell Algorithm 4.9 The Method of Ghost Particles 4.10 Implementation Details of the Ghost Particle Method 4.11 Making Measurements 4.12 Ensembles and Thermostats 4.13 Case Study: Impact of Two Different Bodies 4.14 Case Study: RayleighTaylor Instability 4.15 Case Study: LiquidSolid Phase Transition of Argon
 5. Advanced MD Simulation 5.1 Introduction 5.2 Parallelization 5.3 More Complex Potentials and Molecules 5.4 Many Body Potentials 5.5 Coarse Grained MD for Mesoscopic Systems
 6. Outlook on Monte Carlo Simulations 6.1 Introduction 6.2 The Metropolis MonteCarlo Method 6.2.1 Calculation of Volumina and Surfaces 6.2.2 Percolation Theory 6.3 Basic MC Algorithm: Implementation Details 6.3.1 Case Study: The 2D Ising Magnet 6.3.2 Trial Moves and Pivot Moves 6.3.3 Case Study: Combined MD and MC for Equilibrating a Gaussian Chain 6.3.4 Case Study: MC of Hard Disks 6.3.5 Case Study: MC of Hard Disk Dumbbells in 2D 6.3.6 Case Study: Equation of State for the LennardJones Fluid 6.4 Rosenbluth and Rosenbluth Method 6.5 Bond Fluctuation Model 6.6 Monte Carlo Simulations in Different Ensembles 6.7 Random Numbers Are Hard to Find
 7. Applications from Soft Matter and Shock Wave Physics 7.1 Biomembranes 7.2 Scaling Properties of Polymers 7.3 Polymer Melts 7.4 Polymer Networks as a Model for the Cytoskeleton of Cells 7.5 Shock Wave Impact in Brittle Solids
 8. Concluding Remarks A Appendix A.1 Quantum Statistics of Ideal Gases A.2 MaxwellBoltzmann, BoseEinstein and FermiDirac Statistics A.3 Stirling's Formula A.4 Useful Integrals in Statistical Physics A.3 Useful Conventions for Implementing Simulation Programs A.4 Quicksort and Heapsort Algorithms A.4 Selected Solutions to Exercises Abbreviations Bibliography Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)