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The rising danger of AI-generated images in nanomaterials science and what we can do about it

Nature Nanotechnology volume 20, pages 1174–1177 (2025)Cite this article

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Generative AI has made it trivial to generate fake microscopy images that are indistinguishable from real images, even for experts. As researchers in nanoscience, it is time for us to face this reality and discuss strategies to conserve the integrity of our discipline.

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Fig. 1: A comparison of real experimental images (top row) against AI-generated fakes (middle row) informed by the real images.
Fig. 2: Purely AI-generated images from text prompts through use of ChatGPT.
Fig. 3: The MAIF storage principle.

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Acknowledgements

The authors sincerely thank V. Foliush for initially shocking us with AI replication of experimental images, P. Formanek, K. Werner Stöckelhuber and E. Bittrich for discussions, and all anonymous participants in our online survey. Q.A.B., A.F., G.K.A., L.M.L.-M, and N.A.K. acknowledge support from the Deutsche Forschungsgemeinschaft (DFG) with project IDs 496201730 (Q.A.B), 451785257 (A.F.), 391977956-SFB 1357 (G.K.A), and RTG 451785257 (L.M.L.-M. and N.A.K.). W.J.P. was supported by the Cluster of Excellence 'Advanced Imaging of Matter' of the DFG - EXC 2056 - project ID 390715994. S.B., N.A.K., and L.M.L.-M. acknowledge funding from the European Research Council through ERC Synergy Grant Chiral-Pro (project ID 101166855). E.K. acknowledges funding by the Federal Ministry of Education and Research of Germany (BMBF) in the programme NanoMatFutur (grant no. 13XP5098).

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Authors and Affiliations

  1. Leibniz-Institut für Polymerforschung Dresden e.V., Dresden, Germany

    Nadiia Davydiuk, Elisha Krieg, Jens Gaitzsch, Patrick M. McCall, Günter K. Auernhammer, Andreas Fery & Quinn A. Besford

  2. Faculty of Chemistry and Food Chemistry, Technische Universität Dresden, Dresden, Germany

    Elisha Krieg

  3. Institute of Comparative Medicine, Columbia University Irving Medical Center, New York, NY, USA

    Mu Yang

  4. Department of Materials Science and Engineering, North Carolina State University, Raleigh, NC, USA

    Joseph B. Tracy

  5. EMAT, University of Antwerp, Antwerp, Belgium

    Sara Bals

  6. NANOLight Center of Excellence, University of Antwerp, Antwerp, Belgium

    Sara Bals

  7. Fachbereich Physik, Universität Hamburg, Hamburg, Germany

    Wolfgang J. Parak

  8. Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA

    Nicholas A. Kotov

  9. Biointerfaces Institute and Department of Materials Science and Engineering, University of Michigan, Ann Arbor, MI, USA

    Nicholas A. Kotov

  10. Center for Complex Particle Systems (COMPASS), Ann Arbor, MI, USA

    Nicholas A. Kotov

  11. CIC biomaGUNE, Basque Research and Technology Alliance (BRTA), Donostia-San Sebastián, Spain

    Luis M. Liz-Marzán

  12. Ikerbasque, Basque Foundation for Science, Bilbao, Spain

    Luis M. Liz-Marzán

  13. Cinbio, University of Vigo, Vigo, Spain

    Luis M. Liz-Marzán

  14. Physical Chemistry of Polymeric Materials, Technische Universität Dresden, Dresden, Germany

    Andreas Fery

  15. Department of Biomedical Engineering, The University of Melbourne, Parkville, Victoria, Australia

    Matthew Faria

Authors
  1. Nadiia Davydiuk
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  2. Elisha Krieg
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  10. Nicholas A. Kotov
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  14. Quinn A. Besford
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Corresponding authors

Correspondence to Matthew Faria or Quinn A. Besford.

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The authors declare no competing interests.

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Davydiuk, N., Krieg, E., Gaitzsch, J. et al. The rising danger of AI-generated images in nanomaterials science and what we can do about it. Nat. Nanotechnol. 20, 1174–1177 (2025). https://doi.org/10.1038/s41565-025-02009-9

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