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Agentic TCAD Calibration Workflow for Oxide Semiconductor Transistors

Published 16 Sept 2026arXiv:2609.12184

data quality89

Updated 7 h ago · first seen 14 Sept 2026

paper_01M2F4Z1NSSFPVGN5REJNYF1KW

Abstract

-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 measured transfer curve and device information, the workflow uses measurement--TCAD residuals and local sensitivity tests to select bounded parameter corrections or evaluate additional physical models, and accept only updates that improve device metrics. The LLM agent orchestrates the workflow, while Sentaurus governs the device physics. For the 2\%-W reference device, five agent-suggested updates yield a fixed calibrated model, reducing the multi-metric device objective $J$ by 14.3$\times$. Maximum $V_{\mathrm{th}}$/$I_{\mathrm{on}}$ errors are 36.1~mV/0.022 decade for varying-drain-bias tests and 46.2~mV/0.062 decade for varying-channel-length tests, demonstrating model transferability across bias and geometry rather than a local parameter fit. W-composition tests provide process-sensitive insight. This agentic workflow provides a faster route to model development for emerging device technologies.

Authors

Authors 14

Asif KhanDaewon HaGyujun JeongJunmo LeeKihang YounKwangyou SeoRam CherukuriRishi RanadeShimeng YuSuhwan LimSungwon ChoWanki KimWoohyun HwangYiyi Wang

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arXiv (Atom API + RSS)rss.arxiv.org/rss/cs.AI feedT1· Official7 h ago5
arXiv (Atom API + RSS)rss.arxiv.org/rss/cs.LG feedT1· Official7 h ago4

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