Journal
ACS POLYMERS AU
Volume 3, Issue 3, Pages 239-258Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acspolymersau.2c00053
Keywords
Polymers; Machine Learning; Artificial Intelligence; Autonomous Experimentation; Transfer Learning; Explainability; Optimization; Inverse Design; Deep Learning; Open Science
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Over the past five years, machine learning and artificial intelligence have experienced tremendous growth in polymer science. This article highlights the unique challenges of polymers and how the field is addressing them. It focuses on emerging trends, particularly those that have received less attention in the review literature. Lastly, it provides an outlook for the field, outlining important growth areas in machine learning and artificial intelligence for polymer science and discussing significant advances from the broader material science community.
In the last five years, there has been tremendous growth in machine learning and artificial intelligence as applied to polymer science. Here, we highlight the unique challenges presented by polymers and how the field is addressing them. We focus on emerging trends with an emphasis on topics that have received less attention in the review literature. Finally, we provide an outlook for the field, outline important growth areas in machine learning and artificial intelligence for polymer science and discuss important advances from the greater material science community.
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