Tokyo University of Science researchers use machine learning to enhance CNT yarn 3D printing precision

A new study from the Tokyo University of Science reveals a machine-learning-assisted method that dramatically improves the accuracy of carbon nanotube (CNT) yarn 3D printing, reducing geometric errors by nearly 80%. Published in Composites Part C: Open Access, the research by Junro Sano and Ryosuke Matsuzaki demonstrates how an explainable AI model can automatically correct […]