Conceptio › Archive › arXiv (All)
arXiv (All) open access

Process-Technology Co-optimization for 2D-FETs

Yang, Shao-Heng et al.
arXiv (All) · Papers
Open Source ↗Direct PDF ↓
materials-sciencemesoscale-and-nanoscale-physics
We present the first experimental machine learning (ML)-enabled Process-Technology Co-Optimization (PTCO) framework for optimizing 2D transition metal dichalcogenide (TMD) FET fabrication directly from statistically meaningful experimental data rather than pure simulation data. We first introduce a
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 820736
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive