Researchers at the University of Illinois Urbana-Champaign, in collaboration with the National Center for Supercomputing Applications, have developed a new AI-based tool to model materials more efficiently. This method employs machine learning to simulate frontal polymerization, reducing the time required for computations. By focusing on error-prone areas during training, they minimize data needs and enhance model accuracy. This approach speeds up the process, particularly beneficial for complex manufacturing problems like 3D printing, paving the way for broader applications in various scientific fields.
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