AI-equipped Scanning Probe Microscopy for Autonomous Site-Specific Atomic-Level Characterization at Room Temperature

We present an advanced scanning probe microscopy system enhanced withartificial intelligence (AI-SPM) designed for self-driving atomic-scalemeasurements. This system expertly identifies and manipulates atomic positionswith high precision, autonomously performing tasks such as spectroscopic dataacquisition and atomic adjustment. An outstanding feature of AI-SPM is itsability to detect and adapt to surface defects, targeting or avoiding them asnecessary. It's also engineered to address typical challenges such aspositional drift and tip apex atomic variations due to the thermal effect,ensuring accurate, site-specific surface analyses. Our tests under thedemanding conditions of room temperature have demonstrated the robustness ofthe system, successfully navigating thermal drift and tip fluctuations. Duringthese tests on the Si(111)-(7x7) surface, AI-SPM autonomously identifieddefect-free regions and performed a large number of current-voltagespectroscopy measurements at different adatom sites, while autonomouslycompensating for thermal drift and monitoring probe health. These experimentsproduce extensive data sets that are critical for reliable materialscharacterization and demonstrate the potential of AI-SPM to significantlyimprove data acquisition. The integration of AI into SPM technologiesrepresents a step toward more effective, precise and reliable atomic-levelsurface analysis, revolutionizing materials characterization methods.