Synthetic data-driven deep learning for label-free autonomous atomic force microscopy
Abstract Atomic force microscopy (AFM) is a widely used tool for nanoscale characterization across materials science, energy research, and biology. However, its adoption in high-throughput materials discovery and statistically driven studies remains limited by a strong dependence on expert operator...
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| Hauptverfasser: | , , , , , , , , , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Nature Portfolio
2026-03-01
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| Schriftenreihe: | Nature Communications |
| Online-Zugang: | https://doi.org/10.1038/s41467-026-70421-3 |
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