Understanding the properties of different materials is an important step in material design. X-ray absorption spectroscopy (XAS) is an important technique for this, as it reveals detailed insights ...

A research team led by Prof. Yousung Jung of the Department of Chemical and Biological Engineering at Seoul National University (SNU) has developed an innovative AI-based technology that uses large ...

AI is changing how we create, deliver and measure learning. But in my experience working in professional development, the seismic shifts we’re seeing in this sector aren't rooted in AI tool adoption ...

Tohoku University and Fujitsu Limited have successfully used AI to derive new insights into the superconductivity mechanism of a new superconducting material. Their findings demonstrate an important ...

Princeton University will be one of five higher education partners in a new National Science Foundation Artificial Intelligence Materials Institute (NSF AI-MI), marking a major investment in AI-driven ...

In almost every lab at the Institute, researchers are delving into AI. And the tools they’re developing and deploying have already turbocharged existing methods and opened new pathways to discovery.

Design engineering is running headfirst into a materials bottleneck. Industries such as automotive, aerospace, electronics, and semiconductors now depend on increasingly complex materials. Yet ...

AI helps packaging teams design faster, use less material and improve performance through data-driven modelling, simulation and optimisation tools.

Materials research relies on intuition-driven exploration, where chemists and engineers tweak tiny elements in compositions or processes and then wait to see the result. This approach is powerful - ...