AI-assisted Human-in-the-Loop Web Platform for Structural Characterization in Hard drive design
Scanning transmission electron microscopy (STEM) has become a cornerstone instrument for semiconductor materials metrology, enabling nanoscale analysis of complex multilayer structures that define device performance. Developing effective metrology workflows for such systems requires balancing automation with flexibility; rigid pipelines are brittle to sample variability, while purely manual approaches are slow and subjective. Here, we present a tunable human-AI-assisted workflow framework that enables modular and adaptive analysis of STEM images for device characterization. As an illustrative example, we demonstrate a workflow for automated layer thickness and interface roughness quantifi...
| Authors | Utkarsh Pratiush, Huaixun Huyan, Maryam Zahiri Azar et al. |
|---|---|
| Primary category | cond-mat.mtrl-sci |
| Published | 1 April 2026 |
| Last updated at source | 1 April 2026 |
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