AI helps microscopes find the most informative nanoscale features in a sample
Researchers at Oak Ridge National Laboratory have developed an AI framework called SimuScan to automate atomic force microscopy. The system helps identify significant nanoscale features and autonomously targets areas for study, reducing the need for expert manual operation.
Why it matters
This technology increases the efficiency and consistency of high-throughput nanoscale research, potentially accelerating discoveries in materials science and biology.
by Scott Gibson, Oak Ridge National Laboratory
edited by Lisa Lock , reviewed by Robert Egan
This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility:
Add as preferred source AI-assisted atomic force microscopy identifies tiny surface structures such as nanostructures, DNA assemblies and bacterial cells, and directs follow-up scans to regions most likely to contain scientifically relevant information. Credit: Andrew Sproles/ORNL, U.S. Dept. of Energy Researchers at the Department of Energy's 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.
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