Advanced Physical Models for Silicon Device Simulation
- Indbinding:
- Paperback
- Sideantal:
- 376
- Udgivet:
- 21. oktober 2012
- Størrelse:
- 170x21x244 mm.
- Vægt:
- 648 g.
- 8-11 hverdage.
- 11. december 2024
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Forlænget returret til d. 31. januar 2025
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Ingen binding og kan opsiges når som helst.
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af Advanced Physical Models for Silicon Device Simulation
Device simulation has two main purposes: to understand and depict the physical processes in the interior of a device, and to make reliable predictions of the behavior of an anticipated new device generation. Towards these goals the quality of the physical models is decisive. The introductory chapter of this book contains a critical review on models for silicon device simulators, which rely on moments of the Boltzmann equation. With reference to fundamental experimental and theoretical work an extensive collection of widely used models is discussed in terms of physical accuracy and application results. This review shows that the quality and efficiency of the phys ical models, which have been developed for the purpose of numerical simulation over the last three decades, is sufficient for many applications. Nevertheless, the basic understanding of the microscopic processes, as well as the uniqueness and accuracy of the models are still unsatisfactory. Hence, the following chapters of the book deal with the derivation of physics-based models from a microscopic level, also using new approaches of "taylored quantum-mechanics". Each model is compared with experimental data and applied to a number of simulation exam ples. The problems when starting from "first principles" and making the models suitable for a device simulator will also be demonstrated. We will show that demands for rapid computation and numerical robustness require a compromise between physical soundness and analytical simplicity, and that the attainable accuracy is limited by the complexity of the problems.
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