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Table · dataset · 2026

Surface-Periodicity-Guided Structure Mapping for Automated Scanning Tunneling Microscopy

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Automating scanning tunneling microscopy (STM) is essential for scaling atomically precise characterization and, ultimately, fabrication of next-generation materials and devices.

Description

A key challenge is to maintain atomic precision across extended surface regions, where local structures must be aligned, identified, and revisited in a common lattice frame. Here we use surface periodicity as an intrinsic reference frame to transform lattice-resolved STM images into lattice-registered unit-cell maps.

Using Ag/Si(111)-(7×7) as a model system, the framework preserves lattice indices and neighborhood relationships while standardizing local structural units. This representation enables data-efficient supervised recognition of Ag adsorption configurations from one or a few reference images and supports environment-aware target-site selection. We further implement the framework in a continuous automated STM workflow, demonstrating autonomous scanning, target identification, and structure-specific characterization.

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Our results show that crystalline surface periodicity can provide a transferable basis for automated STM operations on lattice-resolved surfaces.

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Inferred from text
Image 65% · Microscopy 75%
Provenance · 1 source records, 15 field assertions
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