ORNL demonstrates AI-guided targeting for atomic-force microscopy

Researchers at Oak Ridge National Laboratory developed SimuScan, an AI framework for atomic-force microscopy that uses synthetic training images to identify nanoscale features and direct follow-up scans. In demonstrations involving fabricated nanostructures, DNA assemblies and bacterial cells, models trained mainly on simulated data transferred to real images. The system supports a closed-loop workflow in which scientists define the targets and constraints while the AI ranks regions for closer imaging. Researchers said integration with microscope software and reliability checks remain necessary.