Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Physics > Applied Physics

arXiv:2411.13448 (physics)
[Submitted on 20 Nov 2024]

Title:Taylor Modeling and Comparative Research Containing Aspect-Ratio Dependent Optimization of Three-Dimensional Hk Superjunction MOSFETs

Authors:Zhentao Xiao, Haimeng Huang, Zonghao Zhang, Chenxing Wang
View PDF HTML (experimental)
Abstract:This paper presents a comprehensive study on aspect-ratio dependent optimization for specific on-resistance of three-dimensional high-k superjunction MOSFETs. The research introduces a Taylor modeling method, overcoming the computational limitations of the Bessel method. It also employs the Chynoweth model for more accurate breakdown voltage determination. The study provides a comparative analysis of four different superjunction structures, across five aspects: electric field, impact ionization integral, aspect ratio dependent optimization, charge imbalance effect and temperature. The findings offer valuable insights for the manufacturing guidance of superjunction structure selection
Subjects: Applied Physics (physics.app-ph)
Cite as: arXiv:2411.13448 [physics.app-ph]
  (or arXiv:2411.13448v1 [physics.app-ph] for this version)
  https://doi.org/10.48550/arXiv.2411.13448

Submission history

From: Zonghao Zhang [view email]
[v1] Wed, 20 Nov 2024 16:42:21 UTC (13,498 KB)
Full-text links:

Access Paper:

  • View PDF
  • HTML (experimental)
  • TeX Source
  • Other Formats
view license
Current browse context:
physics.app-ph
< prev   |   next >
new | recent | 2024-11
Change to browse by:
physics

References & Citations

export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)