Transforming Atomic Force Microscopy With Autonomous AI Driven Imaging Tools
Researchers at Oak Ridge National Laboratory have developed an AI framework called SimuScan to automate atomic force microscopy. This tool helps identify nanoscale features and targets informative areas, reducing the need for expert manual operation.
Why it matters
Automating complex scientific instrumentation accelerates high-throughput research and reduces human error in nanotechnology.
Ask our AI Assistant Search Menu Posted in | News | Modeling and Simulation | Automotive Materials | Software Transforming Atomic Force Microscopy With Autonomous AI Driven Imaging Tools Download PDF Copy Add AZoM on Google as a preferred source Oak Ridge National Laboratory (ORNL) Sep 11 2026 Reviewed Researchers at the Department of Energy's (DOE) Oak Ridge National Laboratory (ORNL) have developed an artificial intelligence framework that helps researchers use atomic force microscopes to identify important nanoscale features while autonomously targeting the most informative areas of a sample for closer study.
Although atomic force microscopy (AFM) reveals structures as small as molecules, operating the instrument still requires expert judgment about where to scan, how to adjust settings and which features deserve closer study. SimuScan reduces that burden, making AFM faster, more consistent and better suited for high-throughput research.
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