Programmable material systems are emerging architectural structures but the co-design of structure, material, and external stimuli present grand challenges. A team with Northwestern Engineering’s Wei ...

From 11.5 million alloy candidates to AI-guided perovskites, this piece unpacks how materials informatics is speeding up ...

A new study proposed a deep neural network-based forward design approach that enables an efficient search for superior materials far beyond the domain of the initial training set. This approach ...

The course is designed to provide engineering students a view of optimization as a tool for engineering decision making. Students will be given a fundamental introduction to the optimization ...

This comprehensive guide covers must-know Google Material Design details, including features, core principles, components, and and an introduction to best practices. First announced at the 2014 Google ...