Machine-learning models can speed up the discovery of new materials by making predictions and suggesting experiments. But most models today only consider a few specific types of data or variables.

Recombinant spider silk produced by living organisms, ultra-light carbon fiber composites, and next-generation aerogels are no longer lab curiosities, they are already in hospitals, on battlefields, ...

The hope for quantum computers is that the devices will be able to solve complex tasks such as predicting how chemicals react or cracking encrypted text. One of the main reasons that the machines are ...

A new artificial intelligence (AI) tool that could make it much easier to discover better materials for clean energy ...

Materials databases lie at the heart of future data-driven discovery in energy-related fields, say researchers from Tohoku ...

Machine-learning models can speed up the discovery of new materials by making predictions and suggesting experiments. But most models today only consider a few specific types of data or variables.

From creating lightweight yet durable prosthetics to designing new types of solar panels and batteries, materials engineers combine their expertise in physics, chemistry, biology, and engineering to ...

The Materials Science Laboratory is primarily used by the Mechanical Engineering students to support relevant courses and research activities. The Material Science laboratory consists of equipment ...