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Recent advances and challenges in experiment-oriented polymer informatics

Polymer Journal volume 55, pages 117–131 (2023)Cite this article

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Abstract

This review summarizes recent advances in experimental polymer chemistry supported by data science. The area of polymer informatics is rapidly growing based on cheminformatics, materials informatics, and data science platforms. Data-driven analyses, predictions, and suggestions for experimental polymer research are becoming more practical, and machine learning models can now predict various macromolecular properties with reasonable accuracy. At the same time, the limitations of current polymer informatics are being revealed. Developing appropriate treatments for higher-order structures and experimental procedures is critical to adequately process the hierarchical relationships of polymer systems. Recent attempts to treat this advanced information and future challenges in polymer informatics are discussed.

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Funding

This work was partially supported by Grants-in-Aid for Scientific Research (Grant Nos. 22H04623 and 21H02017) from MEXT, Japan, and the JST FOREST Program (Grant No. JPMJFR213V).

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    Kan Hatakeyama-Sato

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Hatakeyama-Sato, K. Recent advances and challenges in experiment-oriented polymer informatics. Polym J 55, 117–131 (2023). https://doi.org/10.1038/s41428-022-00734-9

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