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Microscopy

Combining computer vision and atomic force microscopy for 3D reconstruction

Nature Reviews Materials volume 9, page 673 (2024)Cite this article

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Atomic force microscopy (AFM) is a versatile and non-destructive characterization tool that works by scanning a sharp probe across a sample’s surface to generate high-resolution images of its topography at the nanoscale. However, traditional AFM techniques struggle with accurately reconstructing complex 3D structures owing to incomplete surface capture and to the introduction of artefacts. Now, writing in Communications Engineering, Guofeng Zhang, Yuan-Liu Chen and colleagues present a method that leverages computer vision algorithms to improve the 3D reconstruction of intricate nanostructures without requiring costly modifications or specialized probes.

Existing AFM-based methods that attempt to overcome the limitations encountered by conventional AFM during 3D rendering require hardware modifications or the use of specially designed probes. These approaches, however, are difficult to implement widely owing to their complexity and cost. “By contrast, our method requires only a conventional commercial AFM and a standard probe,” comments Chen. The method proposed here involves three main steps. First, multi-view AFM scanning is performed by rotating the sample on a specially designed stage, allowing scans from multiple angles to capture surface data. The process does not require modifications to the AFM hardware itself, as the rotatable stage functions as an external accessory. Next, the data from these different angles is aligned into a single coordinate system, and an iterative process is used to automatically remove artefacts, ensuring only the true geometric features of the sample are preserved. Finally, a technique called neural implicit surface reconstruction is used to combine the aligned data into a continuous 3D model, accurately reconstructing complex micro- and nanostructures with high detail.

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  1. Nature Reviews Materials http://www.nature.com/natrevmats/

    Charlotte Allard

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  1. Charlotte Allard
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Correspondence to Charlotte Allard.

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Allard, C. Combining computer vision and atomic force microscopy for 3D reconstruction. Nat Rev Mater 9, 673 (2024). https://doi.org/10.1038/s41578-024-00733-7

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