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.

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.

Prof. Daniel LAU, Chair Professor of Nanomaterials and Head of the Department of Applied Physics of PolyU (left) collaborated with the team of Prof YUNG Kai-leung, Director of PolyU’s Research Centre ...

Material science, at its core, is an interdisciplinary field focusing on the discovery and design of new materials. It combines elements of physics, chemistry and engineering to understand and ...

Startups flush with cash are building AI-assisted laboratories to find materials far faster and more cheaply, but are still ...

When you need tools or parts for something you’re working on around the house, you head to the nearest hardware store. Space travelers don’t have that luxury and may have to make their own tools and ...

We are entering a new era in science — the fourth paradigm, according to Kristin Persson, a professor in materials science at the University of California in Berkeley, United States. The first ...

Science experiments that push materials and reactions to dramatic limits. So this is why Trump didn’t want to release the ...

Create your own magnetic slime and discover how ferromagnetic materials interact with magnetic fields. You'll learn about magnetism, viscosity, and chemical reactions while making a fascinating ...

An introductory course focused on the new and existing materials that are crucial for mitigating worldwide anthropogenic CO2 emissions and associated greenhouse gases. Emphasis will be placed on how ...