Researchers from Carnegie Mellon University and the University of North Carolina at Chapel Hill have innovated a method to create advanced rubber-like polymers swiftly using artificial intelligence (AI) and human expertise. Traditional polymer development often sacrifices flexibility for strength, but this approach allows the creation of materials that are both resilient and pliable. By employing a machine learning model, the team input desired properties into a design tool, leading to experiments that refined these polymers effectively. This synergy of AI and human input streamlines the material discovery process, reducing costs and time while enhancing performance for applications in industries like footwear, medical devices, and automotive parts. The open-source nature of the model invites broader laboratory adoption, promising a revolutionary step forward in materials engineering. This collaboration between AI and chemists highlights the potential for significant advancements in creating tailored materials for diverse applications.
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