arXiv Artificial Intelligence

Agentic TCAD Calibration Workflow for Oxide Semiconductor Transistors

Agentic TCAD Calibration Workflow for Oxide Semiconductor Transistors

Quick summary

arXiv:2609.12184v2 Announce Type: replace-cross Abstract: Experimental TCAD calibration is essential for predictive technology modeling of emerging oxide semiconductor transistors. However, it remains time-consuming and expert dependent because of model ambiguity. Multiple physical models and parameter sets can reproduce the same measured transfer characteristics, while local fitting alone cannot uniquely identify the underlying device physics. We present the first demonstration of an agentic TCAD calibration workflow for a fabricated bottom-gate In--W--O (BG-IWO) transistor. Starting from the

Key takeaways

  • arXiv:2609.12184v2 Announce Type: replace-cross Abstract: Experimental TCAD calibration is essential for predictive technology modeling of emerging oxide semiconductor transistors.
  • However, it remains time-consuming and expert dependent because of model ambiguity.
  • Multiple physical models and parameter sets can reproduce the same measured transfer characteristics, while local fitting alone cannot uniquely identify the underlying device physics.

Why it matters

“Agentic TCAD Calibration Workflow for Oxide Semiconductor Transistors” exposes the compute, energy and supply-chain layer behind model competition. Capacity shifts can influence model costs, service availability and the ability of smaller companies to compete.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗