The design of new functional polymers depends on the successful navigation of their structure-function landscapes. Advances in combinatorial polymer chemistry and machine learning provide exciting opportunities for the engineering of fit-for-purpose polymeric materials.
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A.J.G. was supported by NSF CBET award number 2009942 and NIH NIGMS award number 1R35GM138296-01. M.A.W. acknowledges support from Princeton University.
The authors declare no competing interests.
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Gormley, A.J., Webb, M.A. Machine learning in combinatorial polymer chemistry. Nat Rev Mater 6, 642–644 (2021). https://doi.org/10.1038/s41578-021-00282-3