Agentic data science with the Data Agent Kit
cloud.google.com·7h ago
AI Research
arXiv CS.AI·28d ago·5 min read
Agentic TCAD Calibration Workflow for Oxide Semiconductor Transistors
TL;DR
An agentic TCAD calibration workflow was developed for oxide semiconductor transistors, significantly improving model accuracy and reducing calibration time. This approach achieved a 14.3-fold reduction in multi-metric device objective, demonstrating enhanced model transferability across varying conditions.
✦ Why It Matters
Implement this agentic workflow to enhance the accuracy and efficiency of your TCAD model calibrations today.
Key Takeaways
- Adopt agentic workflows for faster TCAD calibration.
- Utilize measurement-TCAD residuals for model refinement.
- Leverage LLM agents to orchestrate calibration processes.
- Focus on model transferability across different testing conditions.
How It Works
The agentic TCAD calibration workflow begins with the measured transfer curve of the transistor and device specifications. It employs measurement-TCAD residuals to identify discrepancies between the model and actual measurements.
Local sensitivity tests are conducted to determine which parameters can be adjusted to improve the model. The LLM agent suggests updates based on these analyses, and only those that enhance device performance metrics are accepted.
This iterative process leads to a more accurate and reliable model.