IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-981-96-0100-4_20.html
   My bibliography  Save this book chapter

Hydrodynamic Electron Transport and Finite Difference Methods

In: Deterministic, Stochastic, and Deep Learning Methods for Computational Electromagnetics

Author

Listed:
  • Wei Cai

    (Southern Methodist University, Department of Mathematics)

Abstract

Having discussed quantum transport models in the preceding two chapters, we now turn to the semi-classical Boltzmann descriptions and their moment equations in the hydrodynamic model in electron transport in complex media including semiconductors and plasmas. Then, finite difference methods for solving the hydrodynamic equations for semiconductor devices will be discussed. Because of the high field effect in sub-micron devices, the electron velocity may develop a sharp transition profile resembling shock waves [1], as in high-speed gas dynamics. Therefore, shock capturing schemes developed for gas dynamics [2, 3] can be applied for device simulations. Here, we will present three methods: the traditional Godunov methods, the weighted essentially non-oscillatory (ENO) finite difference methods, and the central differencing methods. It should be mentioned that the discontinuous Galerkin method can also be used to compute the semiconductor hydrodynamic equations [4].

Suggested Citation

  • Wei Cai, 2025. "Hydrodynamic Electron Transport and Finite Difference Methods," Springer Books, in: Deterministic, Stochastic, and Deep Learning Methods for Computational Electromagnetics, edition 0, chapter 0, pages 569-593, Springer.
    • Handle: RePEc:spr:sprchp:978-981-96-0100-4_20
    DOI: 10.1007/978-981-96-0100-4_20
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-981-96-0100-4_20. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.