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Tutorial: From Semi-Classical to Quantum Transport Modeling Dragica Vasileska Professor Arizona State University Tempe, AZ USA Outline: What is Computational Electronics? Semi-Classical Transport Theory Drift-Diffusion Simulations Hydrodynamic Simulations Particle-Based Device Simulations Inclusion of Tunneling and Size-Quantization Effects in Semi-Classical Simulators Tunneling Effect: WKB Approximation and Transfer Matrix Approach Quantum-Mechanical Size Quantization Effect Drift-Diffusion and Hydrodynamics: Quantum Correction and Quantum Moment Methods Particle-Based Device Simulations: Effective Potential Approach Quantum Transport Direct Solution of the Schrodinger Equation (Usuki Method) and Theoretical Basis of the Green’s Functions Approach (NEGF) NEGF: Recursive Green’s Function Technique and CBR Approach Atomistic Simulations – The Future Prologue What is Computational Electronics? The need for semiconductor device modeling 1. Increased costs for R&D and production facilities, which are becoming too large for any one company or country to accept. 2. Shorter process technology life cycles. 3. Emphasis on faster characterization of manufacturing processes, assisted by modeling and simulation. With permission from Intel Corp. Computer simulations, often called technology for computer assisted design (TCAD) offer many advantages such as: 1. Evaluating "what-if" scenarios rapidly 2. Providing problem diagnostics 3. Providing full-field, in-depth understanding 4. Providing insight into extremely complex problems/phenomena/product sets 5. Decreasing design cycle time (savings on hardware build lead-time, gain insight for next product/process) 6. Shortening time to market Some TCAD Prerequisites Are: Modeling and simulation require enormous technical depth and expertise not only in simulation techniques and tools but also in the fields of physics and chemistry. Laboratory infrastructure and experimental expertise are essential for both model verification and input parameter evaluations in order to have truly effective and predictive simulations. Software and tool vendors need to be closely tied to development activities in the research and development laboratories. R. Dutton, Stanford University, the father of TCAD. Historical Development of Device Simulation: 1964: Gummel introduced the decupled scheme for the solution of the Poisson and the continuity equations for a BJT 1968: de Mari introduced the scaling of variables that is used even today and prevents effectively overflows and underflows 1969: Sharfetter and Gummel, in their seminal paper that describes the simulation of a 1D Silicon Read (IMPATT) diode, introduced the so-called SharfetterGummel discretization of the continuity equation H. K. Gummel, “A self-consistent iterative scheme for one-dimensional steady state transistor calculation”, IEEE Transactions on Electron Devices, Vol. 11, pp.455-465 (1964). A. DeMari, “An accurate numerical steady state one-dimensional solution of the p-n junction”, Solidstate Electronics, Vol. 11, pp. 33-59 (1968). D. L. Scharfetter and D. L. Gummel, “Large signal analysis of a Silicon Read diode oscillator”, IEEE Transaction on Electron Devices, Vol. ED-16, pp.64-77 (1969). Coupling of Transport Equations to Poisson and Band-Structure Solvers D. Vasileska and S.M. Goodnick, Computational Electronics, published by Morgan & Claypool , 2006. What Transport Models exist? Semiclassical FLUID models (ATLAS, Sentaurus, Padre) Drift – Diffusion Hydrodynamics 1. PARTICLE DENSITY 2. velocity saturation effect 3. mobility modeling crucial Drift velocity [cm/s] 1. Particle density 2. DRIFT VELOCITY, ENERGY DENSITY 3. velocity overshoot effect problems Drain Current [mA/um] 8 7 0.3 ps 6 0.2 ps 5 0.1 ps 4 1020 cm-3 3 2 6 10 Current simulations Yamada simulations Canali exp. data 1019 cm-3 1 0 7 10 1 0 0.2 0.4 0.6 0.8 Drain Voltage [V] 1 1.2 10 Electric field [kV/cm] 100 What Transport Models Exist? Semiclassical PARTICLE-BASED Models: Direct solution of the BTE Using Monte Carlo method Eliminates the problem of Energy Relaxation Time Choice Accurate up to semi-classical limits One can describe scattering very well Can treat ballistic transport in devices Why Quantum Transport? 2. SIZE-QUANTIZATION EFFECT The Van Dort model is activated by specifying N.DORT on the MODEL statement. 1. Quantum Mechanical Energy TUNNELING n(z) Classical density z E1 E0 Quantum-mechanical density z CONV z QM z distance 3. QUANTUM INTERFERNCE EFFECT What Transport Models Exist? Quantum-mechanical WIGNER Function and DENSITY Matrix Methods: Can deal with correlations in space BUT NOT WITH CORRELATIONS IN TIME Advantages: Can treat SCATTERING rather accurately Disadvantages: LONG SIMULATION TIMES What Transport Models Exist? Non-Equilibrium Green’s Functions approach is MOST accurate but also MOST difficult quantum approach FORMULATION OF SCATTERING rather straightforward, IMPLEMENTATION OF SCATTERING rather difficult Computationally INTENSIVE Quantum approaches Semi-classical approaches Approximate Easy, fast Model Improvements Compact models Appropriate for Circuit Design Drift-Diffusion equations Hydrodynamic Equations Boltzmann Transport Equation Monte Carlo/CA methods Good for devices down to 0.5 m, include (E) Velocity overshoot effect can be treated properly Accurate up to the classical limits Quantum Hydrodynamics Keep all classical hydrodynamic features + quantum corrections Quantum Monte Carlo/CA methods Keep all classical features + quantum corrections Quantum-Kinetic Equation (Liouville, Wigner-Boltzmann) Accurate up to single particle description Green's Functions method Includes correlations in both space and time domain Direct solution of the n-body Schrödinger equation Can be solved only for small number of particles Exact D. Vasileska, PhD Thesis, Arizona State University, December 1995. Difficult Range of Validity of Different Methods Summary Different transport models exist with different accuracy and different computational needs for modeling the wide variety of devices that are used in practice every day The goal of Computational Electronics is to teach you what models are appropriate for modeling specific device structure and what are the limitations and the advantages of the model used