Computational Electronics

By Dragica Vasileska1, Gerhard Klimeck2, Stephen M. Goodnick1

1. Arizona State University 2. Purdue University

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As semiconductor feature sizes shrink into the nanometer scale regime, device behavior becomes increasingly complicated as new physical phenomena at short dimensions occur, and limitations in material properties are reached. In addition to the problems related to the actual operation of ultra-small devices, the reduced feature sizes require more complicated and time-consuming manufacturing processes. This fact signifies that a pure trial-and-error approach to device optimization will become impossible since it is both too time consuming and too expensive. Since computers are considerably cheaper resources, simulation is becoming an indispensable tool for the device engineer. Besides offering the possibility to test hypothetical devices which have not (or could not) yet been manufactured, simulation offers unique insight into device behavior by allowing the observation of phenomena that can not be measured on real devices. Computational Nanoelectronics in this context refers to the physical simulation of nanoscale devices in terms of charge transport and the corresponding electrical behavior. It is related to, but usually separate from process simulation, which deals with various physical processes such as material growth, oxidation, impurity diffusion, etching, and metal deposition inherent in device fabrication leading to integrated circuits. Device simulation is distinct from another important aspect of computer-aided design (CAD), device modeling, which deals with compact behavioral models for devices and sub-circuits relevant for circuit simulation in commercial packages such as SPICE.

In this course we give an overview of the basic techniques used in the field of computational electronics related to device simulation. Topics covered include:

  • Introduction to Computational Electronics
  • Simplified Band Structure Model
  • Empirical Pseudopotential Method Description
  • Choice of the Distribution Function
  • Relaxation Time Approximation
  • Drift-Diffusion Model: Introduction
  • Drift-Diffusion Model: Solution Details
  • Drift-Diffusion Model: Sharfetter-Gummel Discretization
  • Drift-Diffusion Model: Mobility Modeling
  • Numerical Analysis
  • Introduction to Drift-Diffusion Modeling with PADRE
  • Introduction to SILVACO Simulation Software
  • Scattering Mechanisms
  • Why Particle-Based Device Simulations?
  • Ensemble Monte Carlo Method Described
  • Particle-Based Device Simulators Description
  • What is CMOS Technology Facing?

  • Credits

    Dragica Vasileska and Stephen M. Goodnick, Computational Electronics, Morgan and Claypool, 2006.

    Sponsored by

    NSF, Arizona Institute for Nano Electronics

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