Scientists Fuse Simulations and Machine Learning to Accelerate Novel Additively Manufactured Materials

Researchers at the Johns Hopkins Applied Physics Laboratory (APL) in Laurel, Maryland, have demonstrated a novel approach for applying machine learning to predict microstructures produced by a widely used additive manufacturing technique. Their approach promises to dramatically reduce the time and cost of developing materials with tailored physical properties and will soon be implemented on a NASA-funded effort focused on creation of a digital twin.