AI-equipped scanning probe microscopy for autonomous site-specific atomic-level characterization at room temperature
arxiv(2024)
摘要
We present an advanced scanning probe microscopy system enhanced with
artificial intelligence (AI-SPM) designed for self-driving atomic-scale
measurements. This system expertly identifies and manipulates atomic positions
with high precision, autonomously performing tasks such as spectroscopic data
acquisition and atomic adjustment. An outstanding feature of AI-SPM is its
ability to detect and adapt to surface defects, targeting or avoiding them as
necessary. It's also engineered to address typical challenges such as
positional drift and tip apex atomic variations due to the thermal effect,
ensuring accurate, site-specific surface analyses. Our tests under the
demanding conditions of room temperature have demonstrated the robustness of
the system, successfully navigating thermal drift and tip fluctuations. During
these tests on the Si(111)-(7x7) surface, AI-SPM autonomously identified
defect-free regions and performed a large number of current-voltage
spectroscopy measurements at different adatom sites, while autonomously
compensating for thermal drift and monitoring probe health. These experiments
produce extensive data sets that are critical for reliable materials
characterization and demonstrate the potential of AI-SPM to significantly
improve data acquisition. The integration of AI into SPM technologies
represents a step toward more effective, precise and reliable atomic-level
surface analysis, revolutionizing materials characterization methods.
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