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Hierarchical automation of scanning probe microscopy through agentic orchestration and algorithmic control
Rapid advances in agentic artificial intelligence enable scientific systems to interpret open-ended objectives, combine heterogeneous information, invoke specialized tools, and revise experimental strategies as evidence accumulates. However, physical experimentation also contains many tasks for whic
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