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Computational materials science

Enhancing synthesis prediction via machine learning

Identifying promising synthesis targets and designing routes to their synthesis is a grand challenge in chemistry and materials science. Recent work employing machine learning in combination with traditional approaches is opening new ways to address this truly Herculean task.

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Fig. 1: Schematic representation of the approach by Aykol et al.4.

References

  1. Schön, J. C. & Jansen, M. Angew. Chem. Int. Ed. 35, 1286–1304 (1996).

    Article  Google Scholar 

  2. Pickards, C. J. & Needs, R. J. J. Phys. Cond. Matt. 23, 053201 (2011).

    Article  Google Scholar 

  3. Chen, C. & Ong, S. P. Nat. Comput. Sci. 2, 718–728 (2023).

    Article  Google Scholar 

  4. Aykol, M., Merchant, A., Batzner, S., Wei, J. N. & Cubuk, E. D. Nat. Comput. Sci. https://doi.org/10.1038/s43588-024-00752-y (2024).

    Article  Google Scholar 

  5. Schön, J. C. In Comprehensive Inorganic Chemistry III Vol. 3 (eds Reedijk, J. & Poeppelmeier, K.) Ch. 3.11, 262–392 (Elsevier, 2023).

  6. Behler, J. et al. Phys. Rev. Lett. 100, 185501 (2008).

    Article  Google Scholar 

  7. Hannemann, A. et al. Phys. Rev. B 70, 144201 (2004).

    Article  Google Scholar 

  8. Liebold-Ribeiro, Y. et al. Angew. Chem. Int. Ed. 47, 4428–4431 (2008).

    Article  Google Scholar 

  9. Schön, J. C. J. Chem. Phys. 161, 050901 (2024).

    Article  Google Scholar 

  10. Chou, P. Y. & Fasman, G. D. Adv. Enzymol. Relat. Areas Mol. Biol. 47, 45–148 (1978).

    Google Scholar 

Download references

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Schön, J.C. Enhancing synthesis prediction via machine learning. Nat Comput Sci 5, 95–96 (2025). https://doi.org/10.1038/s43588-025-00771-3

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