Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

Found in knee replacements and bone plates, aircraft components, and catalytic converters, the exceptionally strong metals known as multiple principal element alloys (MPEA) are about to get even ...

The team developed a computational framework using robotic path planning algorithms to rapidly identify optimal composition gradients between dissimilar materials. The framework enables the creation ...

This workshop on Autonomous Materials Science will discuss where the weak links are in future systems that will reduce, and eventually eliminate, the need for human intervention in the design and ...

In October 2015 the National Academies of Sciences, Engineering, and Medicine convened a workshop of experts from diverse communities to examine predictive theoretical and computational approaches for ...

A machine learning method developed by researchers from the Institute of Science Tokyo, the Institute of Statistical Mathematics, and other institutions accurately predicts liquid crystallinity of ...

Materials informatics sits at the intersection of experimental science, computation, and data analytics. The aim is simple: use data and models to make discovering, designing, and deploying new ...

NASA’s Transformational Tools and Technologies project integrates AI, advanced materials, and computational methods to accelerate aerospace design and improve aircraft and space systems.