LLM-Guided Open Hypothesis Learning from Autonomous Scanning Probe Microscopy Experiments

ArXi:2605.06839v1 Announce Type: cross Autonomous experimentation has transformed microscopy and materials discovery by enabling closed-loop optimization including imaging and spectroscopy tuning, strucutre property relationship discovery, and exploration of combinatorial libraries. However, most current workflows remain limited to selecting measurements within fixed objective or hypothesis spaces, rather than generating new physical models from experimental data. Here, we