News

AI uses extrapolative learning to master materials prediction beyond existing data
A research group has developed an innovative machine learning technology that enables predictions beyond the distribution of training data and demonstrated its effectiveness in materials research. The ...
AI enhances molecular design with uncertainty quantification
In a major step toward more reliable AI-assisted molecular design, researchers from National Taiwan University have ...
Tech Xplore on MSN18h
Predicting material failure: Machine learning spots early abnormal grain growth signs for safer designs
A team of Lehigh University researchers has successfully predicted abnormal grain growth in simulated polycrystalline ...
Science Daily9h
Novel machine learning model can predict material failure before it happens
A team of researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time -- a development that could lead to the creation of stronger, more ...