Machine Learning Method Accurately Predicts Metallic Defects
Saturday, February 4, 2017 - 00:02
in Physics & Chemistry
For the first time, Berkeley Lab researchers have built and trained machine learning algorithms to predict defect behavior in certain intermetallic compounds with high accuracy. This method will accelerate research of new advanced alloys and lightweight new materials for applications spanning automotive to aerospace and much more.