Categories: AI/ML News

Machine learning method speeds up discovery of green energy materials

Researchers at Kyushu University, in collaboration with Osaka University and the Fine Ceramics Center, have developed a framework that uses machine learning to speed up the discovery of materials for green energy technology.

Efficient machine learning: Predicting material properties with limited data

Researchers at the Indian Institute of Science (IISc), with collaborators at University College London, have developed machine learning-based methods to predict material properties even with limited data. This can aid in the discovery of materials with desired properties, such as semiconductors.

December 31, 2024

In "AI/ML News"

Introducing the Microsoft Climate Research Initiative

August 31, 2022

Machine-learning models help discover a material for film capacitors with record-breaking performance

The Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) and several collaborating institutions have successfully demonstrated a machine-learning technique to accelerate the discovery of materials for film capacitors—crucial components in electrification and renewable energy technologies. The technique was used to screen a library of nearly 50,000 chemical structures to…

December 6, 2024

In "AI/ML News"

AI Generated Robotic Content